<%BANNER%>

Integration of Toll Plaza Modeling into CORSIM

Permanent Link: http://ufdc.ufl.edu/UFE0043034/00001

Material Information

Title: Integration of Toll Plaza Modeling into CORSIM
Physical Description: 1 online resource (121 p.)
Language: english
Creator: FULLER,BRETT A
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2011

Subjects

Subjects / Keywords: CORSIM -- MODELING -- SIMULATION -- TOLL -- TRANSPORTATION
Civil and Coastal Engineering -- Dissertations, Academic -- UF
Genre: Civil Engineering thesis, M.E.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: In the U.S. there currently exists a financial crisis for the funding of necessary roadway maintenance and expansion. It has thus become necessary to find other means to fund transportation based projects. One such solution is public-private partnerships (P3s) in which a private investor funds a public transportation project and in turn the government entity allows the private investor to collect tolls to recoup their investment. As this type of partnership becomes a more popular option it will become necessary to develop tools necessary to assist engineers in the planning and design of the toll plazas placed along these new roadways. Simulation software is one of these tools. Simulation software such as CORSIM, Aimsun, and VISSIM, to name a few, are vital tools to the planning process of roadways as these programs allow engineers a means to analyze and visualize their proposed roadway designs under expected traffic conditions. This allows engineers an opportunity to develop the appropriate toll network design before construction even begins. This can greatly save federal, state, and local entities millions of dollars in expenses to correct or alter already started/completed projects. Unfortunately, few of these simulation programs are capable of properly simulating traditional toll plazas. CORSIM, one of the most widely utilized simulation programs in the U.S., does not currently allow for direct simulation of toll plaza facilities. This project resulted in the implementation of direct toll plaza modeling into CORSIM. This was accomplished through the development of new algorithms and modeling features. This document discusses the development, verification, and validation of the new toll plaza features implemented in CORSIM.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by BRETT A FULLER.
Thesis: Thesis (M.E.)--University of Florida, 2011.
Local: Adviser: Washburn, Scott S.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2011
System ID: UFE0043034:00001

Permanent Link: http://ufdc.ufl.edu/UFE0043034/00001

Material Information

Title: Integration of Toll Plaza Modeling into CORSIM
Physical Description: 1 online resource (121 p.)
Language: english
Creator: FULLER,BRETT A
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2011

Subjects

Subjects / Keywords: CORSIM -- MODELING -- SIMULATION -- TOLL -- TRANSPORTATION
Civil and Coastal Engineering -- Dissertations, Academic -- UF
Genre: Civil Engineering thesis, M.E.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: In the U.S. there currently exists a financial crisis for the funding of necessary roadway maintenance and expansion. It has thus become necessary to find other means to fund transportation based projects. One such solution is public-private partnerships (P3s) in which a private investor funds a public transportation project and in turn the government entity allows the private investor to collect tolls to recoup their investment. As this type of partnership becomes a more popular option it will become necessary to develop tools necessary to assist engineers in the planning and design of the toll plazas placed along these new roadways. Simulation software is one of these tools. Simulation software such as CORSIM, Aimsun, and VISSIM, to name a few, are vital tools to the planning process of roadways as these programs allow engineers a means to analyze and visualize their proposed roadway designs under expected traffic conditions. This allows engineers an opportunity to develop the appropriate toll network design before construction even begins. This can greatly save federal, state, and local entities millions of dollars in expenses to correct or alter already started/completed projects. Unfortunately, few of these simulation programs are capable of properly simulating traditional toll plazas. CORSIM, one of the most widely utilized simulation programs in the U.S., does not currently allow for direct simulation of toll plaza facilities. This project resulted in the implementation of direct toll plaza modeling into CORSIM. This was accomplished through the development of new algorithms and modeling features. This document discusses the development, verification, and validation of the new toll plaza features implemented in CORSIM.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by BRETT A FULLER.
Thesis: Thesis (M.E.)--University of Florida, 2011.
Local: Adviser: Washburn, Scott S.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2011
System ID: UFE0043034:00001


This item has the following downloads:


Full Text

PAGE 1

1 I NTEGRATION OF TOLL PLAZA MODELING INTO CORSIM By BRETT ALLEN FULLER A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUI REMENTS FOR THE DEGREE OF MASTER OF ENGINEERI NG UNIVERSITY OF FLORIDA 2011

PAGE 2

2 2011 Brett Allen Fuller

PAGE 3

3 To my family and friends who gave the support needed for me to finish

PAGE 4

4 ACKNOWLEDGMENTS I would like to take this opportunity to thank Professor Scott Washburn for be ing an amazing ad viser. The guidance and assistance he has provided me over these last two years were invaluable in completing this project. I would also like to thank Tom Simmerman, the CORSIM programmer for this tions to CORSIM this project would not have been finished in time for me to graduate on time. Finally, I would like to thank my family and friends who gave me strength and supported me these last two years. Without their love and support none of this woul d have been possible.

PAGE 5

5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ ............ 8 LIST OF FIGURES ................................ ................................ ................................ ........ 11 LIST OF ABBREVIATIONS ................................ ................................ ........................... 13 ABSTRACT ................................ ................................ ................................ ................... 14 CHAPTER 1 INTRODUCTION ................................ ................................ ................................ .... 16 Background ................................ ................................ ................................ ............. 16 Problem Statement ................................ ................................ ................................ 17 Research Objectives ................................ ................................ ............................... 18 Document Organization ................................ ................................ .......................... 18 2 LITERATURE REVIEW ................................ ................................ .......................... 20 Overview ................................ ................................ ................................ ................. 20 Analytical Approach ................................ ................................ ................................ 20 Simulation Approach ................................ ................................ ............................... 26 TPSIM ................................ ................................ ................................ .............. 26 PARAMICS ................................ ................................ ................................ ....... 27 Effect of ETC Lanes ................................ ................................ ................................ 28 Summary ................................ ................................ ................................ ................ 29 3 IMPLEMENTATION OF TOLL PLAZA MODELING IN CORSIM ............................ 33 Overview ................................ ................................ ................................ ................. 33 CORSIM Limitations ................................ ................................ ............................... 33 Changes to CORSIM ................................ ................................ .............................. 34 Toll Plaza Control Device ................................ ................................ ................. 34 Toll plaza characteristics ................................ ................................ ............ 35 Traffic characteristics ................................ ................................ ................. 36 Toll Lane Selection Algorithm ................................ ................................ ........... 37 Additional Improvements to CORSIM ................................ ............................... 40 Accommodating Dedicated ETC Lanes ................................ ............................ 40 Changes Made to TRAFVU ................................ ................................ .............. 41 Performance Measures ................................ ................................ .................... 41 Implementati on of New Record Types in CORSIM ................................ .......... 42 4 VERIFICATION AND VALIDITY TESTING OF CORSIM SIMULATION ................. 47

PAGE 6

6 Verification of CORSIM I mprovements ................................ ................................ ... 47 General Assumptions for Verification Process ................................ ................. 47 Verification of payment distribution ................................ ............................ 48 Verification of service time ................................ ................................ ......... 50 Development of toll plaza pull up time equation ................................ ......... 53 Verification of payment restrictions ................................ ............................ 55 Verification of vehicle type restrictions ................................ ....................... 55 Verification of multi ple time period toll booth changes ............................... 56 Summary ................................ ................................ ................................ .......... 56 Validation of CORSIM Improvements ................................ ................................ ..... 57 Calibration ................................ ................................ ................................ ........ 57 Video Data Collection ................................ ................................ ....................... 58 Leesburg plaza data collection ................................ ................................ ... 58 Beach Line West plaza data collection ................................ ...................... 59 Traditional toll plaza ................................ ................................ ................... 59 Hybrid plaza ................................ ................................ ............................... 60 Results of Validation Testing ................................ ................................ .................. 60 Network Model Development ................................ ................................ ........... 61 Results ................................ ................................ ................................ ............. 62 Leesburg toll plaza results ................................ ................................ ......... 62 Beachline West toll plaza results ................................ ............................... 62 5 SUMMARY AND RECOMENDATIONS ................................ ................................ .. 81 Summary ................................ ................................ ................................ ................ 81 Recommendations ................................ ................................ ................................ .. 82 User Specified Acceleration and Deceleration Rates for Toll Plaza Links ........ 82 Integration of ORT Lanes into Toll Plaza Link ................................ .................. 82 Logit Model for Toll Lane Selection ................................ ................................ .. 83 APPENDIX A CORSIM USER GUIDE FOR TOLL PLAZA MODELING ................................ ....... 85 Overview ................................ ................................ ................................ ................. 85 Toll Plaza Data Discussion ................................ ................................ ..................... 85 Essential Toll Plaza Data ................................ ................................ .................. 85 Secondary Toll Plaza Data ................................ ................................ ............... 86 Queue setback distance ................................ ................................ ............ 87 A verage service time ................................ ................................ ................. 87 Reaction point for toll plaza warning sign ................................ ................... 88 Lane change sensitivity to toll lane selection ................................ ............. 88 Output Processor ................................ ................................ ............................. 90 Record Type Discussion ................................ ................................ ......................... 90 Record Type 82 ................................ ................................ ................................ 91 Record Type 83 ................................ ................................ ................................ 91 Record Type 84 ................................ ................................ ................................ 9 2

PAGE 7

7 Simul ating ORT Lanes ................................ ................................ ............................ 92 Example Problems ................................ ................................ ................................ .. 94 Example 1 ................................ ................................ ................................ ........ 94 Simulation and network setup ................................ ................................ .... 94 Toll plaza setup ................................ ................................ .......................... 95 Output processor ................................ ................................ ....................... 96 Example 2 ................................ ................................ ................................ ........ 96 Simulation and network setup ................................ ................................ .... 97 Toll plaza setup ................................ ................................ .......................... 98 Output processor ................................ ................................ ....................... 99 Example 3 ................................ ................................ ................................ ........ 99 Simulation and network setup ................................ ................................ .. 100 Toll plaza setup ................................ ................................ ........................ 100 Output processor ................................ ................................ ..................... 101 Additional Application of CORSIM Improvements ................................ ................. 101 B EXAMPLE PROBLEMS FILE FORMATS ................................ ............................. 114 Example 1 ................................ ................................ ................................ ............. 114 Example 2 ................................ ................................ ................................ ............. 115 Example 3 ................................ ................................ ................................ ............. 116 LIST OF REFERENCES ................................ ................................ ............................. 119 BIOGRAPHICAL SKETCH ................................ ................................ .......................... 121

PAGE 8

8 LIST OF TABLES Table page 2 1 LOS thresholds for toll plazas ................................ ................................ ............. 30 2 2 Typical toll lane capacities by method of collection and vehicle use ................... 30 2 3 Processing rate at toll facilities by customer group ................................ ............. 31 2 4 LOS table based on delay ................................ ................................ .................. 31 2 5 Delay and v / c ratio scenarios ................................ ................................ .............. 31 2 6 Capacity evaluation of interchange 11A in Westborough, Massachusetts ......... 31 3 1 Typical FDOT service times/processing rates of toll payment types ................... 43 3 2 Color coding for toll booth markings ................................ ................................ ... 43 4 1 Verification scenarios for payment distribution input ................................ ........... 64 4 2 Results 100% ACM payment ................................ ................................ .............. 64 4 3 Results 100% Manual payment ................................ ................................ .......... 65 4 4 Results 100% Ticket paym ent ................................ ................................ ............ 65 4 5 Results 100% ETC payment ................................ ................................ ............... 65 4 6 Results 0% ACM, 0% Manual, 50% Ticket, 50% ETC payment distribution ....... 65 4 7 Results 50% ACM, 50% Manual, 0% Ticket, 0% ETC payment distribution ....... 65 4 8 Results 5% ACM, 85% Manual, 5% Ticket, 5% ETC p ayment distribution ......... 66 4 9 Results 10% ACM, 10% Manual, 0% Ticket, 80% ETC payment distribution ..... 66 4 10 Results 10% ACM, 60% Manual, 10% Ticket, 20% ETC payment distribution ... 66 4 11 Results 15% ACM, 15% Manual, 50% Ticket, 20% ETC payment distribution ... 66 4 12 Results: 20% ACM, 20% Manual, 20% Ticket, 40% ETC payment distribution .. 66 4 13 Results: 20% ACM, 20% Manual, 50% Ticket, 10% ETC payment distribution .. 67 4 14 Verification scenarios for mean service time input ................................ .............. 67 4 15 Results for 4 second service time testing ................................ ........................... 67

PAGE 9

9 4 16 Results for 7 second service time testing ................................ ........................... 67 4 17 Results for 9 second service time testing ................................ ........................... 67 4 18 Results for 13 second service time testing ................................ ......................... 68 4 19 FDOT typical testing ACM and Ticket payment ................................ .................. 68 4 20 FDOT typical testing Manual payment ................................ ................................ 68 4 21 FDOT typical testing ETC payment ................................ ................................ .... 68 4 22 0 second service time sce nario ................................ ................................ .......... 68 4 23 Payment restriction testing ................................ ................................ ................. 69 4 24 Results Trucks restricted to one lane no car restrictions ................................ .... 69 4 25 Results Trucks restricted to two lanes cars restricted to four lanes .................... 69 4 26 Results two vehicle types to two toll booths as signment ................................ .... 69 4 27 Multiple time period verification scenario ................................ ............................ 70 4 28 Results of multiple time period testing ................................ ................................ 70 4 29 Traffic volumes for Beachline West toll plaza ................................ ..................... 70 4 30 Traffic volume for Leesburg toll plaza ................................ ................................ 71 4 31 Standard toll plaza capacities and rates along Florida toll roads (single payment type lane) ................................ ................................ ............................. 71 4 32 ........... 72 4 33 Leesburg 15 minute traffic data ................................ ................................ .......... 72 4 34 Beachline West 15 minute traffic data ................................ ................................ 73 4 35 Five minute interval data for Leesburg Toll Plaza ................................ ............... 73 4 36 Five minute interval data for Beachline West Toll Plaza ................................ ..... 73 4 37 Volume comparison Leesburg Toll Plaza ................................ ........................... 73 4 38 Queuing comparison Leesburg Toll Plaza ................................ .......................... 74 4 39 Volume comparison Beachline West Toll Plaza ................................ ................. 74 4 40 Queuing comparison Beachline West Toll Plaza ................................ ................ 74

PAGE 10

10 A 1 Lane selection example toll lane desirability ................................ ..................... 103 A 2 Binary Code Use for Payment Acceptance ................................ ...................... 103 A 3 Example 1 lane utilization by payment type ................................ ...................... 103 A 4 Example 2 exiting volumes results ................................ ................................ ... 103 A 5 Example 2 average service time by toll booth ................................ .................. 103 A 6 Example 3 toll booth utilization by vehicle type time period 1 ........................... 103 A 7 Example 3 toll booth utilization by vehicle type time period 2 ........................... 103

PAGE 11

11 LIST OF FIGURES Figure page 2 1 Flow chart that demonstrates the process to calculate toll plaza delay using the analytical methodology. ................................ ................................ ................ 32 3 1 Generalized Toll lane selection algorithm ................................ ........................... 44 3 2 New legend depicting vehicle color scheme for toll plaza segments .................. 45 3 3 New vehicle color scheme for toll plaza segments ................................ ............. 45 3 4 New lane markings and signage depicting payment types accepted at each toll booth ................................ ................................ ................................ ............. 46 4 1 Link node diagram of generic toll plaza ................................ .............................. 75 4 2 Six lane generic toll plaza developed for service time verification ...................... 75 4 3 Eight lane generic toll plaza developed for payment distribution verification ...... 75 4 4 Verification testing results for toll booth restrictions ................................ ............ 75 4 5 Aerial view of Leesburg toll plaza ................................ ................................ ....... 76 4 6 Toll booth configuration for Leesburg toll plaza (Courtesy of FDOT) .................. 76 4 7 Aerial view of Beach Line West toll plaza eastbound approach ......................... 77 4 8 Aerial view of Beach Line West toll plaza westbound approach ......................... 77 4 9 Toll booth configuration for Beach Line West toll plaza (Courtesy of FDOT) ..... 78 4 10 Location map of toll plazas for study ................................ ................................ .. 78 4 11 Traffic conditions at Leesburg toll plaz a during study period .............................. 79 4 12 Traffic conditions at Beachline West toll plaza during study period .................... 79 4 13 CORSIM node li nk diagram for Beachline West Toll Plaza ................................ 80 4 14 CORSIM model of the Beachline West Toll Plaza ................................ .............. 80 4 15 CORSIM node link diagram for Leesburg Toll Plaza ................................ .......... 80 4 16 CORSIM network model of the Leesburg Toll Plaza ................................ .......... 80 A 1 Lane change selection exa mple ................................ ................................ ....... 104

PAGE 12

12 A 2 .trf format for record type 82 ................................ ................................ ............. 105 A 3 .trf format for record type 83 ................................ ................................ ............. 105 A 4 .trf format for record type 84 ................................ ................................ ............. 105 A 5 Toll plaza that should utilize a combination of FRESIM and NETSIM links to simulate ORT lanes ................................ ................................ ......................... 106 A 6 Toll plaza that should utilize FRESIM link to simulate ORT lanes note separation between toll plaza and ORT lanes ................................ .................. 107 A 7 ORT lane utilizing NETSIM link (ORT lane is top lane) ................................ .... 107 A 9 Network properties input screen for Example 1 ................................ ................ 108 A 10 Link input screens for Example 1 ................................ ................................ ...... 108 A 11 Node and ink diagram of Example 1 ................................ ................................ 109 A 12 Example 1 approach ................................ ................................ ......................... 109 A 13 Toll plaza input screen coded for Example 1 ................................ .................... 110 A 14 Toll plaza developed in Example 1 ................................ ................................ ... 110 A 15 Toll plaza approach for Example 1 ................................ ................................ ... 110 A 16 Output processor configuration for Example 1 ................................ .................. 11 1 A 17 Aerial of Beachline West Toll Plaza ................................ ................................ .. 111 A 18 Example 2 network split (bottom portion leads to traditional plaza) .................. 111 A 19 Node and link diagram for Example 2 ................................ ............................... 112 A 20 Off ramp inputs for traditional toll plaza Example 2 ................................ .......... 113 A 21 Network properties input for Example 3 ................................ ............................ 113

PAGE 13

13 LIST OF ABBREVIATIONS ACM Automatic Coin Machine API A pplication Programming Interface AVI Automatic Vehicle Identification DVU Driver Vehicl e Units ETC Electronic Toll Collection FDOT Florida Department of Transportation FHWA Federal Highway Administration HCM Highway Capacity Manual ITS Intelligent Transportation Systems LOS Level of Service MOE Measures of Effectiveness NCHRP National Cooper ative Highway Research Program OOCEA Orlando Orange County Expressway Authority ORT Open Road Tolling P3 Public Private Partnership TPSIM Toll Plaza Simulation Model v/c Volume to Capacity Ratio

PAGE 14

14 Abstract of Thesis Presented to the Graduate School of the U niversity of Florida in Partial Fulfillment of the Requi rements for the Degree of Master of Engineering INTE GRATION OF TOLL PLAZA MODELING INTO CORSIM By Brett Allen Fuller M ay 2011 Chair: Scott Washburn Major: Civil Engineering In the U.S. there currently exist s a financial crisis for the funding of necessary roadway maintenance and expansion. I t has thus become necessary to find other means to fund transportation based projects. One such solution is public private partnerships (P3s) i n which a private investor funds a public transportation project and in turn the government entity allows the private investor to collect tolls to recoup their investment As this type of partnership becomes a more popular option it will become necessary t o develop tools necessary to assist engineers in the planning and design of the toll plazas placed along these new roadways. Simulation software is one of these tools. Simulation software such as CORSIM, Aimsun and VISSIM to name a few, are vital tools to the planning process of roadways as these programs allow engineers a means to analyze and visualize their proposed roadway designs under expected traffic conditions This allows engineers an opportunity to develop the appropriate toll network design bef ore construction even begins. This can greatly save federal, state, and local entities millions of dollars in expenses to correct or alter already started/ completed

PAGE 15

15 projects. Unfortunately, few of these simulation programs are capable of proper ly simulatin g traditional toll plazas. CORSIM, one of the most widely utilized simu lation programs in the U S does not currently allow for direct simulation of toll plaza facilities. This project resulted in the implementation of direct toll plaza modeling into CORS IM. This was accomplished through the development of new algorithms and modeling features This document discusses the development, verification, and validation of the new toll plaza features implemented in CORSIM.

PAGE 16

16 CHAPTER 1 INTRODUCTION Background Given the transportation financing challenges faced by government agencies in the U.S toll roads are becoming a more common feature along freeway facilities In Florida there are over 700 miles of toll roads with more under construction and in the planning p rocess These toll roads provide a vital service by connecting portions of the state that may not have be en connected by the Interstate Highway System or the Florida Strategic Intermodal System Examples include connecting Naples to Miami via the Alligator Alley Expressway and Orlando to South Florida via the Florida Turnpike. As the usage of toll roads in America continues to increase, there is a need to better understand the traffic operational characteristics of toll roads as well as how these operations impact the overall operations of the surrounding freeway corridor. The toll plaza segment has the greatest effect on freeway capacity compared to other segment types. This is because if the capacity of the toll plaza is below the capacity of the upstream segment, bottlenecking can occur, which in turn decreases the overall 1 ). Given this issue, it is important to identify bottlenecks as soon as possible, preferably during the design process of the toll road. Be cause of this, it is vital for engineers to be able to analyze toll plazas during the planning process with minimal expenditures. One way to analyze freeways at a low cost is to develop a simulation of the freeway using a traffic simulation program By uti lizing this software engineers are capable of visually observing the network to determine problem areas. In addition to being able to visualize the freeway segments, simulation programs are also capable of

PAGE 17

17 providing large amounts of data useful for analys is. T h ese data can include travel times, speeds, and delay. Problem Statement CORSIM is a well established simulation program in the U.S., is the most commonly used microsimulation program in the U.S., and generally has a good reputation with respect to it s underlying models and algorithms given its long history of development and testing. However, CO R SIM currently does not directly accommodate toll plaza modeling This has been a very common request of CORSIM users over the past few years. While it is poss ible to develop a basic toll plaza by utilizing stop control, these simulations do not take into account the variability of driver behavior toll plaza transactions, etc The creation of accurate simulation tools, such as CORSIM, for toll plazas will allow for more in depth study on the subject. One area of study that the improved CORSIM program would be able to assist in is the development of an analytical method to analyze toll plazas. While methodologies exist to analyze toll plazas in isolation, all but one these methodologies base toll plaza performance on delay. One methodology estimates density for toll plazas, but this methodology was developed prior to the implementation of electronic toll collection lanes. All of the HCM freeway segment analysis me thodologies, as well as the overall facility, base level of service on delay. Thus, existing methodologies for freeway facility analysis and toll plaza analysis use disparate performance measures. Consequently, a methodology does not exist by which the eff ect of toll plaza operations on extended lengths of freeway can be considered

PAGE 18

18 Research Objective s The objective s of this research are to 1) integrate explicit toll plaza modeling into the CORSIM microscopic simulation program and 2) compare plaza simulation capabilities and results with field data. This will provid e a valuable tool for engineers who need to evaluate the operations of existing toll plaza corridors and plan future toll plazas along freeway corridors The task s that were conduc ted to achieve these objectives are as follows : Conducted a literature review on toll plaza design, and analytical and simulation based methodologies developed for toll plazas. Evaluat ed existing toll plaza analysis methodologies to determine usability of methodologies for current research. Identified and recommended necessary revisions for CORSIM to allow for explicit toll plaza simulation. Implemented toll plaza simulation into CORSIM. Performed testing of CORSIM toll plaza modeling and compared to avail able field data. Developed toll plaza simulations to be utilized as examples for future CORSIM versions. Develop user guidelines for utilizing CORSIM to simulate toll plazas. Document Organization C hapter 2 present s the results of a literature review on th e topics of toll plaza analysis, simulation, and design Chapter 3 describe s the implementation of direct toll plaza modeling into CORSIM. This includes discussion on newly developed inputs added models/algorithms and revised models/algorithms needed to i mplement toll plaza modeling. Chapter 4 discusses the testing conducted to determine the validity of the CORSIM toll plaza modeling capabilities. Chapter 5 d iscusses the conclusions and

PAGE 19

19 recommendation s developed from this research. This includes a discussi on on limitation s as well as recommendations for future improvements. Appendix A compiles all necessary information to properly simulate a toll plaza in CORSIM into a user guide Appendix B provides the .trf files for three example problems

PAGE 20

20 CHAPTER 2 LITE RATURE REVIEW Overview This chapter summarizes the previous r esearch conducted on toll plazas. This include s research conducted on the analysis of toll plazas, simulation of toll plazas, and the effect that ETC lanes have on toll plaza operations Analytic al Approach The analysis of toll plazas originates with the research conducted by Woo and Hoel ( 2 ) The ir study resulted in the development of a methodology for analyzing toll plaza capacity and provide d a LOS for toll plazas E qu ations were developed by Woo and Hoel to calculate capacity and density ; E quations 2 1 and 2 2 respectively Equation 2 1 for capacity of entire toll plaza: (2 1 ) where, C = capacity of toll plaza (veh /h) n j = toll booth with collection t ype j c j = capacity of toll booth with c ollection t ype j (veh/h) t 1 j = service time for v ehicle t ype i and t oll c ollection t ype j (s) Equation 2 2 for the density of a toll plaza: (2 2 ) where, K = d ensity of toll plaza ( veh/mi/ln ) Q = flow rate ( a for automobiles t for trucks)

PAGE 21

21 T = average total time to travel through the toll plaza area ( a for automobiles t for t rucks) A = Area of toll plaza segment n 1 = number of arriva l lanes n 2 = number of toll booths n 3 = number of departure lanes L 1 = length of convergence section (ft) L 2 = length of re convergence section (ft) In addition to the developed equations field data (primarily traffic counts, including vehicle type, a nd vehicle time spent in the toll plaza) were then collected at eight toll plazas to test the validity of these equations These data along with regression analysis, were utilized to develop a relationship between the volume to capacity ratio ( v/c ) and de nsity This analysis provided evidence of a distinct relationship between density and v/c. From the regression models and the collected data, LOS thresholds for toll plazas were created based on both density and v/c In addition to establishing LOS thresho ld s for toll plazas Woo and Hoel also establish ed average service time s for cars and trucks; 5.11 s ec to 5.47 s ec and 12.87 s ec to 14.88 s ec. C apacity values were also determined by toll booth type, 600 veh/h for Automatic Coin Machine ( ACM ) booths with a gate, 665 to 745 veh/h ACM booths without a gate, and 650 to 705 veh/h for general cash booths. Table 2 1 presents the LOS findings from the work of Woo and Hoel. NCHRP S ynthesis 240 ( 3 ) contain s average toll lane capacities for a variety of payment methods. These values were obtained from a questionnaire sent out to toll plaza operators and represent

PAGE 22

22 operational capacity values. The results from this questionnaire are found in Table 2 2 T oll plaza capacity is a n important determinant in the toll plaza operations C apacity is a difficult value to obtain bec a u s e a varying ETC penetration can significantly affect the plaza s capacity ( 4 ) In addition, th e posted speed limit through the ETC only lanes also can affect a toll plaza capacity. In the case of Holland East Plaza in Orlando, Florida it was observed that by de creasing the posted speed limit of the ETC lane f r o m 55 m i/ h to 35 m i/ h the processin g rate of ETC vehicles decreased from 32 veh/min to 23 veh / min ( 5 ) This equates to a decrease in capacity of 540 veh/h per ETC lane. In order t o determine the capacity of a toll plaza Zarrillo proposed E quations 2 3 and 2 4 (2 3 ) where, C = toll plaza capacity (veh/h) J = capacity of single service lanes (veh/h) K = capacity of mixed use lanes (veh/h) (2 4 ) where, K = capacity of mixed u se lanes (veh/h ) N = number of lanes of mixed use S i = vehicle processing rate for payment type i (veh/h ) P i = percentage of vehicles utilizing payment method i

PAGE 23

23 The vehicle processing rate S can be found Table 2 3 Utilizing thes e equations and plaza traffic data from the Holland East Plaza in Orlando, Florida and Interchange 11A in Westborough, Massachusetts Zarrillo evaluated the capacities of these toll roads From this research Zarrillo was able to conclude the following: Th e c apacity of a toll plaza is dependen t on the processing time and lane type s of the toll plaza The a vailable capacity of a toll plaza increases as ETC lanes replace cash lanes as long as appropriate levels of ETC usage are observed. Non ETC semi trucks A drawback of using simulation models is that there is a lack of data to compare the simulation outputs to the facility. The solution to this was to develop a methodology that could be used m anually to calculate capacity, queuing patterns, and delay ( 6 ) The primary concern of these calculation s was determining if the upstre am segment capacity was more tha n the toll plaza capacity. If this was the case a bottleneck w ill occur during a n interval of high demand which would caus e an overall decrease in the toll road a queue were to form at the toll plaza. In order to manually calculate toll plaza operations Aycin ( 6 ) proposed E quat ions 2 5, 2 6, 2 7, 2 9, and 2 10 for capacity, plaza queue, and delay for different toll booth payment options : For capacity: (2 5 ) (2 6 )

PAGE 24

24 ( 2 7 ) (2 8 ) where, = capacity of toll booth for payment i (veh/h ) = average ETC vehicle speed (ft/s) = average distanc e headway (ft) = vehicle service time = time for next vehicle in queue to move to booth = transaction time of pair j = probabilities of possible leader follower pairs given %ETC using mixed lane To find the upstream roadway capacity Acyin uses the established equation for a basic freeway segment from the 2000 Highway Capacity Manual ( 1 ) : (2 9 ) where, C road = Capacity of upstream segment (veh/h) v p = 15 min peak passenger car equivalent flow rate (pc/h/ln) N = number of lanes = heavy vehicle factor = driver population factor For queue:

PAGE 25

25 (2 10 ) where, Q i = number vehicles in plaza queue at time i = cumulative vehicle demand ( C plaza C ) at time i (v eh ) F i = flow rate (veh/h ) V section = average section speed ( mi/ h) X = distance betwee n end of queue and automatic traffic recorder (mi) For delay: (2 11 ) where, D = queue delay ( sec ) X j = length of individual queue section for booth j (ft) t = average headway time between completing transactions of successive cars (sec) (X k ) joined = length of joined queue section for vehicle k in queue (ft) S = average distance headway (ft) n = number of queues in the joined area B = number of available boo ths C ertain factors that can affect capacity were assumed Some assumptions includ ing queues of different payment types d i d not affect the arrival time of other vehicles. P erception reaction los t time is accounted for by the separation d istance and accel eration rates. W ith these mentioned assumptions when compared to a simulation model, capacity, queuing, and delay were accurately calculated.

PAGE 26

26 Simulation Approach For toll roads in Florida two computer simulation programs have be en utilized for research, TPSIM and PARAMICS. The research efforts using these programs are described in the following sections. T PSIM TPSIM is a stochastic discrete event microscopic simulation program, written in Visual Basic 6 ( 8 ). T PSIM has been u sed extensively for research conducted o n toll plaza operations in the Orlando Florida area Klodzinski and Al Deek ( 9 ) investigated the various methodologies available for analyzing toll plazas using TPSIM The methodologies invest igated were based on traffic density, v / c and vehicle delay. By doing this the authors hoped to not only establish the best measure of effectiveness ( MOE ) to analyze toll plazas but to also establish proper LOS criteria for the selected methodology. Us ing traffic data obtained from field collection and TPSIM simulations the three methodologies mentioned were evaluated. When evaluating the vehicle density methodology it was determined that LOS based on vehicle density was not appropriate for toll plaza s. This was because different lane transaction types produced varying vehicle densities. In addition, it was noted that ETC lanes can accommodate higher vehicle densities without an increase in plaza delay. The authors assert that t his situation makes usin g vehi cle density to determine LOS not viable because higher densities may no t be an indicator of lower LOS. The evaluation of v / c also proved to be an inaccurate indicator of LOS. A LOS based on v / c makes the assumption that the operating conditions of a roadway

PAGE 27

27 toll plazas, this may not always be the case. T oll plaza s may run close to capacity but operating conditions may be acceptable This is due to the effect of ETC penet ration, which will be discussed later on. D elay proved to accurately represent toll plaza LOS. According to the authors, 8 ) Traffic delay at the plaza takes into account ETC lanes, geometry of the plaza, and upstream and downstream conditions. Using the traffic and simul ation data collected Klodzinski and Al Deek [2002] further determined that cumulative delay better represented the data then average delay. This is becau se of the variation of delay distribution due to the peak hour. With cumulative delay selected by Klodzinski and Al Deek ( 8 ) the next step was to establish the LOS ranges for each LOS, starting with LOS A. Once the maximum allow ed vehicle delay for LOS A was determine d, the rest of the LOS levels were determined by a percent increase method that is provided in the HCM 2000 for signalized intersection delay. Table 2 4 contains the LOS values. PARAMICS Q uadstone P aramics is a comprehensive microsimulation program ( 10 ) Paramics contains an application programming interface (API) that allows users to modify the behavior of the simulation. This allows users to expand the simulation capability of Paramics by creating new algorithms as needed. Nezamuddin and Al Deek ( 11 ) wrote a component to simulate toll plazas that they integrated with Paramics through the API PARAMICS was used to simulate operations for i ndividual toll plazas and for entire networks that include d multiple toll plazas in Florida PARAMICS utilizes what is referred to as driver vehicle units (DVU), which imitate individual driver characteristics

PAGE 28

28 based on input parameters. The PARAMICS toll p laza and toll road co rridor model was developed by Nez amuddin and Al Deek ( 11 ) Traffic data from the Orlando Orange County Expressway Authority ( OOCEA ) toll road corridor and GEH statistic a stati stical value similar to the chi squared test that compares hourly traffic values of a model to the hourly traffic values of field data were utilized in the calibration of the model. To test the validity of the model eight hypothetical scenarios were run using the model. During each sce nario the model acted within expectations. From this work a successful simulation model was created that can proper ly analyze toll road corridors. Effect of ETC Lanes Dedicated ETC lanes are toll lanes where the vehicle typically does not stop to pay its toll but rather continues through the toll plaza at regular or a reduced speed, with the toll transaction being done electronically. Sometimes electronic toll collection is allowed at the cash lanes as well, but in this case the vehicle must stop and wai t for a gate to rise up It is due to the characteristic s of ETC only lanes that make determining LOS for a toll plaza difficult as these lane types create situations where density and v / c may not be clear indicators of poor operational conditions. ( 14 ) Shown in Table 2 5 for similar levels of v / c but considerably different level of ETC vehicle percentages, the level of delay can be considerably different Additional work was co nducted by Zarrillo ( 5 ) to investigate the affect ETC lanes have on capacity of a toll plaza. F rom the study it was determined that ETC The results of the study are shown in Table 2 4 Table 2 5 and Table 2 6 illustrate that ETC vehicle pe netration and ETC efficiency Thus, u nderstanding how ETC lanes effect a toll plaza s capacity is v ital to developing a valid methodology to analyze toll plazas.

PAGE 29

29 While converting manual payment toll booths to ETC only lanes appears to be an obvious solution to increasing toll plaza capacity, it must be remembered that the number of ETC only lanes must be balanced with the percentage of vehicles in the traffic stream that are equipped with electro nic toll collection transponders. S witching manual payment toll booths to ETC only toll booths without adequate ETC penetration will cause a decrease in a plaza overall performance ( 1 2 ) In a ddition a 10% user shift from manual payment to ETC payment, when the manual lanes of the plaza are operating over capacity can decrease the total plaza queuing delay by 50% reduce delay per vehicle by more than 90 seconds, and increase s plaza flow by 20%. T he increase of ETC users also cau se s a decrease in the simulated peak hour delay ( 1 2 ) Summary Considerable research has been conducted on toll plaza operations. From the research discussed in this chapter, analytical methodologies have been developed that are c apable of evaluat ing capacity, queuing, and delay by payment type. A n LOS criterion has been developed based on vehicle delay at the toll plaza. Simulation programs, suc h as TPSIM and PARAMICS have also provided a vital look into how ETC lanes affect the overall function of a toll plaza. Despite this research, however, there are still limitations specifically with regards to integrating toll plaza analysis into freeway facility analysis The mai n limitation is that a relat ionship between vehicle delay and traffic density for toll plazas with ETC only lanes has not been created. Furthermore, the one existing methodology for estimating density at toll plazas (without ETC only lanes) is approximately 20 years old, during which time toll plaza and traffic chara cteristics have possibly changed enough such that this methodology is less

PAGE 30

30 accurate tha n it once was. This has prevented toll plaza methodologies from being incorporated into the HCM freeway facilities analysis methodology. Table 2 1 LOS t hresho lds for t oll p lazas LOS Density v/c A < 12 0.24 B < 20 0.4 C < 30 0.57 D < 42 0.74 E < 67 1 F > 67 --Table 2 2 Typical toll lane capacities by method of collection and vehicle use Types of To ll Payment/Lanes Number of Responses Actual Data Range ( veh/h/ln ) Average Value ( veh/h/ln ) Manual (Attended) Passenger vehicles only 22 240 500 416 Mixed use 24 180 550 360 ACM (Single Coin) Mixed use 2 550 550 ACM (multip le Coins) Mixed use 2 550 550 Ticket Entry Mixed use 4 425 600 506 Ticket Exit Payment Mixed use 2 275 465 370 ETC Express/Lanes 2 1200 1800 1500

PAGE 31

31 Table 2 3 Processing rate at toll faci lities by customer group Customer Group Processing Rates (veh/h/ln) Manual 498 48 ACM 618 30 Trucks 138 78 ETC 15 mi/h 900 120 ETC 35 mi/h 1380 120 ETC 55 mi/h 1920 120 Table 2 4 LOS t able b ased on d el ay Level of Service 85th percentile delay (s/veh) A B > 14 28 C > 28 49 D > 49 77 E > 77 112 F > 112 Table 2 5 Delay and v / c ratio scenarios Volume % of ETC vehicle % of ACM vehicle % of manual vehicle # of ETC lanes # of ACM lanes # of manual lanes v/c ratio Minimum % vehicles that have no delay 5000 0% 20% 80% 0 2 10 1.0 0 % 5000 36% 20% 44% 1 2 6 0.96 36% 5000 72% 10% 18% 2 1 3 0.94 72% 5000 100% 0% 0% 3 0 0 0.93 100% Table 2 6 Capacity e valuation of i nterchange 11 A in Westborough, Massachusetts Stage Entry to Turnpike For entire Plaza (%) Veh/h v/c ratio MSF P E P T N E J K C V Before ETC 0 8.6 0 1440 1131 2571 2220 0.864 1900 After S E = 15 veh/min 5 8 1 1542 492 2034 2200 >1.0 >2200 After S E = 15 veh/min 25 6 1 2088 502 2590 2200 0.849 1870 After S E = 23 veh/min 45 4 1 2820 606 3426 2200 0.642 1410

PAGE 32

32 Figure 2 1 Flow chart that demonstrates the process to calculate toll plaza delay using the analytical methodology. [ F rom Aycin et al 2009. Development of Methodology for Toll Plaza Delay Estimation for Use in Travel Demand Model Postprocessor. In Transportation Research Record (Page 3, Figure 1)]

PAGE 33

33 CHAPTER 3 I MPLEMENTATION OF TOL L PLAZA MODELING IN CORSIM Overview Before impleme nting direct simulation of toll plazas into CORSIM it is important to evaluate the current capabilities of CORSIM 6.2 This chapter will describe the current limitations with modeling toll plazas in CORSIM and then describe the revisions and additions mad e to CORSIM to allow for robust modeling of a variety of toll plaza configurations. CORSIM Limitations CORSIM 6.2 does not currently have the ability to directly model toll plazas However, with the creative use of stop yield, and/or signal control it is possible for CORSIM 6.2 to indirectly model toll plazas. One drawback with this approach is that the stochastic nature of vehicle service times at the toll plaza cannot be taken into account, particularly with respect to how they can vary across different toll lanes with different payment methods Us ing one of the stop control devices results in a constant service time for all vehicles across all lanes, which is not realistic at toll plazas, even if the same payment method was made in each lane. Typical to ll plaza models allow for the input of an average se rvice time along with an upper and lower service time range This allows for the simulation program to vary the service time for each vehicle by rand omly assigning a service time from the input range prov ided by the user and according to the specified distribution (usually a normal or exponential distribution) With the current methods used to model toll plazas in CORSIM, using stop and yield signs as the toll booths, lane selection at the toll booth is d one in a mor e deterministic manner compared to what actually occurs at a toll plaza In CORSIM the

PAGE 34

34 only lane assignment restriction for a toll plaza is to utilize the toll booth that has the shortest queue. With toll plazas, queue length is probably the m ost significant factor, but likely not the only determining factor for why a particular toll booth is selected. Additionally, a driver needs to make sure they select a toll booth that is compatible with their desired form of payment (e.g., exact change). Unfortunately, CORSIM 6.2 currently cannot do this and operates as if all toll booths are able to accommodate all payment methods. A specialized lane selection algorithm is a vital part of a toll plaza simulation as th is algorithm allows for the creation of lane restrictions by vehicle payment type. In the case of toll plazas, this algorithm would prevent a cash vehicle from utilizing an ETC lane or an ACM vehicle from utilizing a cash lane. This toll plaza specific lane selection algorithm adds an additional layer to the simulation that promotes a more accurate representation of the toll plaza Changes to CORSIM The research team worked with the Mc Trans C enter to make the necessary improvements to CORS IM to explicitly model toll plaza operations The main components that were added or revised in CORSIM 6.3 to accomplish the direct toll plaza modeling include: Developing a toll plaza control device Developing a toll plaza lane selection algorithm Adding toll plaza specific input variables Adding p erformance measure outputs for the toll plaza link Toll Plaza Control Device The toll plaza control device was designed to be the heart of the new improvements to accommodate toll plaza simulation. The control d evice contain s all the

PAGE 35

35 necessary inputs needed to properly simulate a toll plaza primarily information concerning the traffic and toll booth characteristics. Toll p laza c haracteristics The toll plaza characteristics include toll booth status, average serv ice time, and pull up distance. The toll booth status information specifies whether the toll booth is open or closed the payment types accepted at each toll booth and the vehicle types allowed to use each toll booth This is accomplished by using two bin ary coding strings which will be discussed in more detail in Appendix A. This method currently a llows each toll booth to accept up to four different payment types. Currently these payment types are named ACM, Manual, Ticket, and ETC. Even though each paym ent type is named after a specific payment, in reality they are interchangeable and can represent any payment type desired In addition to specifying how many of the four types of payments are accepted at each toll booth a mean service time is also requir ed for each payment type. This mean service time is used to place a delay on each vehicle as they stop at the toll booth, simulating the time it takes for a vehicle to pay the toll or obtain a toll ticket This delay is determined by utilizing a random nu mber generated from a negative exponential distribution as specified by the mean service time parameter. This value is also constrained by a minimum service time of one second Typical values for each payment type as determined from toll plaza field data obtained from FDOT, can be seen in Table 3 1 It is important to note two things from these values. It should be noted that the typical service time shown for the TICKET payment type is based on average service time s for vehicles entering a ticket based toll network. A significantly higher service

PAGE 36

36 time, around 15 to 16 seconds, would need to be utilized for the exit toll plaza for a ticket based toll road. T affected by the pull up distance between the vehic le at the toll booth and the first vehicle in queue for that booth. This distance is usually established by the toll authority as a safety measure for toll workers and vehicles interacting with the plaza. This distance varies by toll authority; thus, it wa s included as a user input in CORSIM. A default value of 25 feet is utilized by CORSIM. Traffic c haracteristics To properly simulate a toll plaza information concerning the traffic characteristic s is necessary. There are two traffic characteristic s ne eded to simulate a toll plaza; the percentile distribution of payment types within the traffic flow and the percentage of ETC users that do not utilize ETC only lanes. It should be noted that traffic volume is not a necessary input as a toll plaza segment is a closed traffic segment ; thus, the traffic volume entering the toll plaza segment will be a function of upstream traffic volume inputs. To address the payment distribution issue a n input was added such that the user can specify the percentage of vehicles in the traffic stream for each payment type ( e.g., ETC, change required). Thi s allow s the user to utilize any combin ation of the four available payment types. Currently these four payment types are labeled ACM, ETC, Manual, and Ticket aft er the four most commonly accepted toll payment types in Florida. In addition to the payment distribution information, it is also important to distinguish what percentage of ETC eligible vehicles will use the dedicated ETC lane (in which vehicles do not have to stop) versu s a standard toll booth lane in which ETC and other

PAGE 37

37 payment methods might be accepted (in these lanes vehicles will have to stop and wait for a gate to raise) The modeling of dedicated ETC lanes is discussed in more detail in ccommodating D ed icated ETC L anes I t should be noted that in theory acceleration and deceleration rates should also be considered as inputs as it is possible that drivers use different deceleration and acceleration rates in toll plaza areas than along other roadway fa cilities; however, determining this is outside the scope of this research. Thus, the default acceleration and deceleration values in CORSIM will be utilized. Toll Lane Selection Algorithm To determine toll plaza lane selection in CORSIM previously develo ped toll lane selection algorithms were considered and evaluated One option is a heuristic algorithm similar to the method developed by Al Deek et al. ( 2 ) for the TPSIM toll plaza simulator. This methodology is a two step process The first step occurs in the approach zone of the toll plaza. A s a vehicle enters this zone of the t oll plaza the program scans the toll plaza to identify toll lanes th at match the vehicle s assigned payment type. Based on the identification process toll plaza lanes are designa ted open or closed based on the vehicle s payment type. After identifying the available toll lanes the program then selects a toll lane with the shortest available queue. This becomes the desired toll lane the driver wants to use. Th e second step of this process occurs as the vehicle leaves the approach zone and enters the tra nsition zone The second step recheck s the original lane selection to determine the final lane selection This allows for a more accurate model that takes into account the varying con ditions that occur at a toll plaza as a vehicle approaches the plaza. When looking at this process it would appear that the first step is not necessary. However, it may become impossible for the vehicle to get

PAGE 38

38 to the desired toll lane due to other vehicles in the network. It is also possible that conditions at the originally selected toll lane have changed and now make another toll lane more favorable. Another existing approach to simulating toll plazas was developed for PARAMICS. Developed by Nezamuddin a nd Al Deek ( 11 ) the PARAMICS approach utilizes the existing driver ve hicle units (DVU) and four features already available in PARAMICS to simulate a toll plaza. First to assist with visual identification the vehicle type manager was adjusted to suit the needs for toll plaza simulation Th e vehicle type manager algorithm implements a color coding for vehicles based on their payment type. The vehicle type manager also adds payment type identifiers to each DVU. This allows for the restriction manager, next l ane allocation, and lane choice rule algorithms to properly interact with each DVU. The next feature used is the restriction manager. In this case t he restriction manager dictates which lanes are available for each payment type and prevents vehicles from u tilizing the wrong toll lane based on payment type The next feature adjusted to accommodate toll plaza simulation was the next lane allocation tool. This tool is used to assist with smoother transitions when lanes are added. The tool works by overriding t he default lane mapping used in PARAMICS. This prevents the unrealistic tendency of vehicles not utilizing the newly added lanes. The primary tool used to move the vehicles to the correct toll lanes is the lane choice rule This is done by overriding the d efault lane use rules. In the case of the toll plaza simulation, the lane choice rule assigns vehicles to toll lanes based first on payment type accepted at the booth and then on queue length.

PAGE 39

39 After research ing existing lane selection algorithms a heurist ic algorithm similar to Al Deek et al. ( 2 ) was developed. The modified heuristic algorithm utilizes a two step process to determine the preferred toll lane based on existing conditions. Refer to Figure 3 1 for the developed algori thm for toll lane selection implemented in CORSIM. To implement this toll lane selection algorithm a specific point upstream of the plaza serves as the point at which the toll lane selection algorithm is invoked for each vehicle passing this point This p oint essentially serves as a driver reaction t he reaction point that informs the vehicle that it is approaching a toll plaza. It is also at this point that a payment method is randomly assigned to a vehicle, as a function of the user specified distribution of payment percentiles. CORSIM uses a default value of 1 500 feet but this value can also be user specified The heart of the toll lane selection algorithm is the following equation for calculating the desirability of a given toll lane This equation is a function of relative queue length and the number of lane changes required to reach a given toll lane. The e quation to determine desirability is as follows: (3 1 ) where, = Toll lane desirability of toll lan e j = Difference in queue length between current toll lane and toll lane = Number of l ane changes required for vehicle to reach toll lane j = Lane change sensitivity factor

PAGE 40

40 With regard to the lane change sensitivity factor, this value can rang e from 0 to 3 and provides the user with the ability to adjust the importance of the number of lane changes irability of a given toll lane. The default value is 0.7 based on trial and error experimentation and what seemed reasonable to the research team. See Appendix A for a more in depth discussion on the toll lane selection equation. Additional Improvements to CORSIM In the process of implementing toll plaza simulation into CORSIM previous limitations were observed and corrected. One such limitation ob served deals with the interface node that connects FRESIM links to NETSIM links. Before the recent changes t o CORSIM the interface node was limited to a maximum of five lanes (due to an unintended consequence of the original separate development tracks of FRESIM and NETSIM) The maximum number of lanes for an interface node was changed to nine, now consistent w ith the maximum number of lanes allowed for NETSIM links Accommodating Dedicated ETC Lanes While developing the toll plaza capabilities for CORSIM it was determined that implementing ETC payment into the traditional toll lanes was easily accommodated. The same cannot be said for dedicated ETC lanes. This is mainly due to the speed differential witnessed between dedicated ETC lanes and the traditional toll lane. CORSIM was unable to accommodate multiple desired speeds within the same link. It was then deter mined this that the best way to overcome this obstacle was to simulate dedicated ETC lanes as independent parallel link separate to the toll plaza link. This would allow the ETC link to operate at free flow speed or reduced speeds as necessary. It is impor tant to note that the ability to simulate dedicated ETC lanes wa s not a change

PAGE 41

41 to CORSIM more of a solution to a new problem using existing tools already found in CORSIM. Additional information concerning the simulation of dedicated ETC lanes can be found in Appendix A. Changes Made to TRAFVU In addition to the changes made to CORSIM, changes were also made to the TRAFVU graphic processor. TRAFVU provides users a visual depiction of the CORSIM simulation. The changes made to TRAFVU assist the user in visual ly identifying important features of the toll plaza. This includes vehicle payment assignment and payment type acceptance at each toll booth. T o allow users to visually recognize vehicles by their assigned payment method, a new color schem e was developed i n TRAFVU. To complement the new vehicle color scheme developed for toll plaza segments a toll payment section was added to the TRAFVU legend. Figure 3 2 and Figure 3 3 show the improved legend and vehicl e color scheme for toll plaza segments The other addition to TRAFVU concerns the visualization of the toll plaza. This involves additions to pavement markings and signage. The addition to signage allows for a visual representation of the toll plaza contro l device. The new pavement marking s, which utilize a matching color scheme as used for vehicles, display the various payment types accepted at each toll lane. The pavement markings also denote if the booth is open or closed. Figure 3 4 provides a description of what each pavement marker color represents. Performance Measures The new toll plaza link created in CORSIM will produce outputs that can be utilize d to evaluate the overall operation s and capacity of the toll plaza, as well as the

PAGE 42

42 operations and capacity of individual toll lanes Two new performance measures were developed for toll plaza analysis : TOLLBOOTH and TOLLPAYMENT T he toll plaza link performance measures include delay, speed, density discharge total, service time average and toll booth utilization by payment type. The performance measures are discussed in detail in Appendix A. Implementation of New Record Types in CORSIM To accommodate direct toll plaza simulation in CORSIM new record types were implemented for t he CORSIM program. These new record types contain and organize the necessary input data needed for toll plaza simulation. In depth discussion o f the new record types is contained in Appendix A.

PAGE 43

43 Table 3 1 Typical FDOT service t imes / processing rates of toll payment types Payment Type Mean Service Time (s /veh ) Mean Processing Rate (s /veh ) ACM 2.5 7 .0 Manual 5.5 9 .0 Ticket 2.5 7 .0 ETC 1.0 4.5 Table 3 2 Color coding for toll booth markings C olor Description Yellow Marking ACM Brown Marking Manual Blue Marking Ticket Green Marking ETC White Marking All payment types Three Red Marking s Booth Closed

PAGE 44

44 Figure 3 1 Generalized Toll la ne selection algorithm

PAGE 45

45 Figure 3 2 New legend depicting vehicle color scheme for toll plaza segments Figure 3 3 New vehicle color scheme for toll plaza segments

PAGE 46

46 Figure 3 4 New lane marking s and signage depicting payment types accepted at each toll booth

PAGE 47

47 CHAPTER 4 VERIFICATION AND V ALIDITY TESTING OF C ORSIM SIMULATION Verification of CORSIM Improvements The first step in evaluating the improv ements made to CO RSIM is the verification process. During the verification process the improvements to CORSIM were run through a variety of test scenarios to determine that all improvements are working correctly and produce reasonable results This was accomplished by ind ividually varying the input values of the new variables. All bugs identified during this testing process w ere relayed back to the programmer for correction. For the toll plaza improvements, five CORSIM algorithms were tested to confirm that the inputs fun ctioned correctly. These inputs included: Payment distribution Service time Payment restrictions at toll booth Vehicle type restrictions at toll booth Toll booth status changes during multiple time period simulation General Assumptions for Verification Pr ocess Before starting the verification process it is important to identify variables that can affect the results of the verification process. To ensure that these variables only have minimal effects on the verification process they must have their impact m inimized There are two variables capable of affecting the verification process : toll plaza geometry and the toll lane selection algorithm One hour simulations were used to produce volume outputs instead of flow rates. To ensure that the effects of the t oll plaza geometry and toll lane selection algor ithms were minimal two generic toll plaza s w ere designed for the verification testing. The generic toll plaza s were design ed based off a traditional toll plaza design

PAGE 48

48 without the typical lane additions and d rops seen at traditional plazas T his prevents additional lane changes that are due to lane additions or drops typically seen as vehicles fan out/merge to utilize available lanes. To ensure equal availability of each payment type an eight lane generic tol l plaza was utilized for testing the payment distribution. This was not an issue for testing the service time algorithm; thus, a smaller six lane toll plaza was utilized. In addition to the number of lanes, care was also taken in determining the length of the approach segment. T his was to ensure that the toll lane selection algorithm does not interfere with testing. The warning sign utilized to start the toll lane selection algorithm was place d at 2000 feet B y establish ing the start ing point of the toll l ane selection algorithm far enough upstream th e lane changes due to the toll lane selection algorithm would be at a minimum near the toll booths. This distance was determined based off of measurements of existing toll plazas which typically have an approa ch length of a half mile See Figure 4 1 for the link node design of the plaza and Figure 4 2 and Figure 4 3 for the visual depiction of the six l ane and eight lane generic toll plaza design s Verification of p ayment d istribution To verify that the payment distribution input was working correctly twelve scenarios were run with varying payment distributions. These scenarios cover a wide range of sit uations, from single payment type scenarios to all four payment type s being utilized. This ensures that the payment distribution works for all cases. Using the developed generic toll plaza e run proces sor and the average values of the ten runs were evaluated. The twelve test scenarios developed for this testing are shown in Table 4 1

PAGE 49

49 When conducting the verification of the payment distribution, it became evident that this test ing could be broken up into two distinct tests. The first test was to determine that when the user specified only one payment type, the payment distribution algorithm only assigned vehicles to the defined payment type. The second test was to determine that the payment distribution algorithm properly distributed the user specified payment percentiles for a wide variety of scenarios. For the first portion of testing, four scenarios that utilized 100 percent of a single payment type were tested, with one scena rio for each payment type. To ensure minimal variance in these tests, variables such as service time and traffic volume, were kept uniform throughout the four scenarios. For these scenarios, an entering traffic volume of 2000 veh/h and an average service t ime of 10 seconds/veh were utilized. Each scenario was simulated ten times and results were obtained from the average of these ten runs. The results of this testing are found in Table 4 2 Table 4 3 Table 4 4 and Table 4 5 From this testing, it was determined that the payment type distribution algorithm properly identified that only one payment type was utilized and only assigned vehicles to that payment type. After testing individual payment types, the next step was to confirm that the payment distribution algorithm properly assigned the correct percentiles of multiple payment types to the traffic flow. To accomplish this, eight scenarios utilizing a variety of payment distributions were run. T hese test s could not be performed in exactly the same way as the four scenarios used to test the individual payment types because vehicles left in the toll plaza queue at the end of the simulation would affect the results of these particular tests. Even though diff erent payment percentages were specified for each

PAGE 50

50 payment type if queuing were to exist at the plaza for the entire simulation scenarios could arise where the volumes of each payment type would be greatly different from the expect volumes and percent dist ribution. This is caused by the queuing at the toll plaza not being cleared by the end of the simulation. These vehicles that did not clear the toll plaza would not be counted towards the total volume of vehicles exiting the plaza. Thus, the entering traff ic volumes ha d to be adjusted on a scenario by scenario basis to ensure that no or very minimal queuing existed at the end of each scenario which would ensure that all vehicles that entered the network were accounted for in the final analysis. To obtai n the desired network conditions at the end of each scenario, it was determined that the network entering volume should be adjusted by time period, with each time period having a duration of fifteen minutes. This approach would allow a significant number o f vehicles to enter the network at the beginning of the simulation, and as the simulation progresses decrease the volume of traffic entering the network until the volume was low enough to where the queuing at the plaza was cleared before the end of the sim ulation period Results for these scenarios are shown in Table 4 6 through Table 4 13 From the results of these test scenarios, it was determined that the payment distribution algorithm is working correc tly. Verification of s ervice t ime The verification process of service time inputs follows a similar approach used for the verification of the payment distribution input. For this testing seven scenarios were developed for testing; three scenarios to test the FDOT typical values f or each payment type and four scenarios to test a wide range of user specified inputs. Only three of the four payment types need to be tested as the ACM and Ticket payment type have the

PAGE 51

51 same typical service time. This testing uti lized the six lane generic toll plaza segment For this process a single payment type was utilized across all toll lanes. This approach eliminated the interaction between vehicles with different payment reducing potential variability of each simulation Th e test scenarios developed for testing are shown in Table 4 14. In addition to utilizing only one payment type, care was taken in establishing a volume of vehicles entering the network. Different volumes were utilized for each scenario. The reason for t his was to ensure that the toll plaza was operating under constant queuing conditions This ensures that each toll booth is operating at capacity for the specified service time of that scenario Generally, assuming constant queuing, average service time fo r a toll lane can be calculated using Equation 4 1. (4 1) where, = average service time ( seconds /veh) = Volume of vehicles exiting toll booth i (veh / h) Strictly speaking, however, the t ime calculated in Eq uation 4 1 also includes the time a vehicle spends pulling up from the first position in queue to a position immediately adjacent to the booth. Thus, the time calculated in Eq uation 4 1 will be referred to as the overall processing time and the service time is considered to be just the time a vehicle spends immediately adjacent to the toll booth. The difference between the overall processing time and average service time will be referred to as the pull up time. Pull up time is the time it takes the first vehicle in the queue to pull up to the toll booth. This

PAGE 52

52 usually accounts for three to four seconds of the total processing time Accounting for pull up time is discussed in the following section. Testing to verify service time followed t he original experimental design. As mentioned previously, testing would be conducted on both user specified average service times and default average service times to determine how accurately the outputs correspond to the inputs. The FDOT typical service t imes for the four payments, as well as four scenarios designed to test various levels of average service times, were created. For this testing, each toll booth was analyzed individually; producing six data points averaged over ten runs for each simulation. To ensure that the largest number of vehicles possible would be processed for a given service time, each scenario was set up to operate with constant queuing. This would ensure that the maximum throughput was achieved with the given service time. Testing of the user specified average service time inputs showed good results. For low to medium low service times, 1 to 6 seconds, average service times were found to be typically within one tenth of a second from the desired average service time, with a standard deviation of under 0. 1 seconds Typically, for these lower average service times, the average service times resulting from the simulation tended to be slightly higher than the average. This is a result of a required minimum service time of one second that is imposed on all vehicles entering a toll booth. The one second minimum also produces a larger error for smaller service times. At higher average service times, the observed range of error for the average service times jumped from one tenth of a second t o two tenths of a second for service times ranging from 7 to 10 seconds. Service times over 10 seconds produce averages within three tenths of a second of the

PAGE 53

53 desired average service time. Results for the testing of user specified service times are shown i n Table 4 15 Table 4 16 Table 4 17 and Table 4 18 T esting was also conducted on the FDOT typical service times. Since ACM and Ticket payment types h ave the same average service time, only one simulation was run for the two of them. At this time, it should be noted that an exact processing rate for ETC payment utilizing a standard toll booth has not been determined, so an estimate of 4.5 seconds was ut ilized. This was based on 3.5 seconds observed for pull up time and an additional 1 second needed for the toll arm to rise Results for the testing of the FDOT typical service times are shown in Table 4 19 Table 4 20 and Table 4 21 In addition to the testing previously mentioned testing was also conducted on a 0 scenario typically observed during hurricane evacuations or other high volume situations To test this scenario a simulation was developed utilizing ACM, Manual, and ETC payments types. Each of these payment types average service time were assigned to 0 seconds. Service time and average speed for each toll bo oth was obtained from the CORSIM output processor From this testing it was determined that the evacuation scenario works properly with vehicles traveling through the plaza at or near the free flow speed specified for the toll link Results for this test can be seen in Table 4 22 Development of t oll p laza p ull u p t ime e quation Pull up time typically accounts for three to four seconds of the processing time. This time is vehicle/driver type specific, as it is a function of vehic le acceleration/deceleration rates and driver reaction times. Because pull up time is vehicle/driver specific, an approximation equation was developed so that a general

PAGE 54

54 estimate of pull up time (an average for the given traffic stream) could be obtained an d applied, along with the average service time, to obtain an estimate of the processing rate. To develop this equation, 30 toll plaza scenarios with varying queue setback distances and truck percentages were developed. This testing was similar to the verif ication testing for the single payment type in the fact that each scenario utilized the six lane generic toll plaza and was simulated with constant queuing to insure that maximum throughput for each toll booth. Each scenario was simulated ten times in CORS IM. The CORSIM output processor was utilized to collect the exiting traffic volume and the average service time for each toll booth. These outputs allowed for the calculation of the processing rate and pull up time for each toll booth. Using these collecte d data, a three axis plot was created using truck percentage, queue setback distance, and pull up time. From this plot, it was seen that the relationship between the dependent variable of pull up time and the independent variables of truck percentage and q ueue setback distance was approximately linear. Thus, a linear regression analysis was performed for these three variables, and E quation 4 2 was obtained: (4 2 ) where, Queue S etback D ist = distance between stopped vehicle position im mediately adjacent to toll booth and stopped position of first vehicle in queue (measured from front bumper to front bumper), in feet %Truck s = Percent of heavy vehicles in the traffic stream This equation produces an adjusted R 2 value of 0. 806 The t stat istics showed that the independent variables are significant at the 99% confidence level

PAGE 55

55 Verification of p ayment r estrictions The verification testing of the payment restrictions test s to make sure that each vehicle is only utilizing toll booths that acce pt their assigned payment type This testing was not done by a quant it ative method but instead a visual confirmation approach was utilized This was accomplished by running s imulations and observed using TRAFVU to determine if the restrictions were workin g correctly. To determine this, attention was focused on randomly selected vehicles. These vehicles were observed from the time their payment type was assign ed to when they enter ed the toll booth. At this point careful attention was paid to make sure that the vehicle in question utilized a toll lane that accepted its payment type. This testing showed that the payment restriction capabilities were working correctly. T esting was also conducted to the test the open/closed status of a toll booth. This was to e nsure that vehicles would not utilize closed toll booth s during high volume scenarios. To test this, scenarios were developed with multiple toll booth closures and traffic volumes well over the capacity of the available toll booths. This testing also relie d on a combination of visual confirmation of the results and exiting volume collection from the CORSIM output processor From this testing it was determined that e ven in high demand low capacity scenarios vehicles would not pass through a closed toll boo th. Visualization of this valid ation testing can be found in Figu re 4 4 Numerical results of this testing can be found in Table 4 23 Verification of vehicle type restrictions To veri fy that the vehicle type restriction functioned properly three simulations were developed. These simulations were developed to test two realistic scenarios and one hypothetical scenario. Scenario one restricts all heavy vehicles to the far right toll

PAGE 56

56 boot h; there are no restrictions for car vehicle types. For scenario two all heavy vehicles were restricted to the two far right toll lanes and car vehicle types were restricted to the remaining four toll booths The third scenario is based on a hypothetical scenario that utilizes six vehicle types and assigns vehicle types 1 and 2 to toll booths 1 and 2, vehicle types 3 and 4 to toll booths 3 and 4, and vehicle types 5 and 6 to toll booths 5 and 6. To ensure that adequate volumes for each vehicle type were o bserved the vehicle type percentages were adjusted so that each vehicle type would have the same probability of being assigned to a vehicle entering the network Results for these three scenarios can be found in Table 4 24 Table 4 25 and Table 4 26 From this testing it was determined that the algorithms limiting vehicle types to specific toll booths was working properly. Verification of multiple time period toll boo th changes The verification testing of multiple time period plaza changes tests the new CORSIM features to ensure that the simulation is properly implementing changes to the toll booths during multiple time period simulations. To test this, a single CORSIM simulation was developed. This simulation consisted of four time periods. Each time period utilize d a different number of open toll booths. See Table 4 27 for the plaza configuration for each time period. Results for this simulat ion were averaged over ten runs. Results for this testing can be found in Table 4 28 From this testing it was determined that the toll booth changes implemented during each time period worked properly. Summary Verification testin g was conducted on five essential toll plaza algorithms to ensure they functioned correctly. From this testing it was determined that the payment

PAGE 57

57 distribution algorithm payment restriction algorithms vehicle restriction algorithm, and multiple time perio ds algorithm, operated as expected. The service time algorithm tends to produce average service times that are slight ly higher than desired for smaller service times. This is due to the enforced 1 second minimum service time that shifts the average service time slightly upward. Validation of CORSIM Improvements After the verification process, in which errors were identified and corrected, the performance measure results were further scrutinized for consistency This was accomplished by testing to see if the toll plaza features in CORSIM could replicate field conditions of a real toll plaza. For this effort, data were obtained from the FDOT The data obtained include d the following: Video footage of two toll plazas Daily average traffic volumes Average ETC p enetration Average capacity volumes and processing rates for various payment types These data are found in Table 4 29 Ta ble 4 30 Table 4 31 and Table 4 32 T his information provide d valuable resources to determine default values for a variety of toll plaza input s and expected outputs allowing for CORSIM to be calibrated based on these values. Calibration To confirm the accuracy of the improvements made to CORSIM, it is important to test the validity of the simulation. For this, two toll plazas were selected from the list of toll plazas currently in use in Florida. The two toll plazas were selected to provide calibration for two of the three styles of toll plazas seen in Florida. The two plaza types that were simulated were the traditional toll plaza and the hybrid plaza that combines

PAGE 58

58 open road tolling (ORT) any type of tolling system that does not require a vehicle to come to a com plete stop, with traditional tolling into one plaza. The third toll plaza type open road tolling only plaza was not simulated, as the plaza is simply a basic freeway segment that operates at normal freeway speed s In the case of ORT toll plazas the toll plaza tools developed in CORSIM would not be needed. These two plazas were plazas. The two plazas selected for this testing were the Leesburg Plaza and the Beach Line West t oll plaza. The locations of these toll plazas can be seen in Figure 4 10 Video Data Collection In addition to the basic traffic data, FDOT also was able to provide video footage for the Leesburg Toll Plaza and the Beach Line West Toll Plaza. A total of about 1 hour and 15 minutes of operations at each plaza w as recorded I t was decided to use a 15 minute interval from each video recording for the toll plaza operations validatio n. The 15 minute interval chosen was the one with the heaviest traffic demand However, one 15 minute interval for the Leesburg Toll Plaza was not considered because the number of open booths changed during this interval. Leesburg p laza d ata c ollection The video footage was of the southbound approach of the L eesburg plaza. It was observed that during the selected 15 minute interval the plaza had three manual payment lanes open and one dedicated ETC lane open The dedicated ETC lane has a posted speed limit of 25 mi/h; however, Turnpike personnel indicated tha t many vehicles travel through the plaza in this lane at speeds up to 40 mi/h During the 15 minute interval steady queuing of one to two vehicles was observed with a maximum queue of two to three vehicles at each of the three manual payment lanes. See Figure

PAGE 59

59 4 11 for a screen shot of the traffic conditions at the Leesburg plaza. A fairly steady flow of vehicles entering the ETC only lane was also observed. A summary of the minute by minute traffic counts of the selected 15 minute interval is in Table 4 33 Beach Line West p laza d ata c ollection The video footage was of the westbound approach. It was observed that during the selected 15 minute interval the plaza had three manual payment lanes open and thre e ORT dedicated ETC lanes open. Typically queuing at this toll plaza was nonexistent. However an instance of a t wo vehicle queue was observed at one manual lane. See Figure 4 12 for a screen shot of the traffic conditions at the Beachline West plaza. Concerning the ORT lane congestion was not an issue as vehicles were traveling near or at free flow speed. A summary of the minute by minute traffic counts of the selected 15 minute interval is in Table 4 34 Traditional t oll p laza To simulate the traditional toll plaza, the Leesburg Plaza located along the Florida Turnpike latitude 28.66 deg longitude 81.84 deg was utilized. The sou thbound approach of this plaza is a two lane approach which fan s out to ac commodate seven toll booths These seven toll lanes are comprised of one ETC only lane and six cash /ETC lanes. In the case of this plaza, the ETC only lane is not a full speed lane as seen in the open road tolling plaza. Instead, speed limits are reduced a s the vehicle approaches the plaza until the vehicle reaches the plaza at which point the posted speed limit is 25 mi/h It is also important to note that of the six lanes available for non ETC vehicles; typically only three to four of them are open d urin g normal traffic conditions A fifth toll lane is opened only during higher than normal traffic conditions and t he sixth cash lane is only opened during extreme ly high demand periods such as when toll s are lifted

PAGE 60

60 during emergencies or before or after a ma jor holiday An aerial photograph and c onfiguration for the northbound approach of the plaza are shown in Figure 4 5 and Figure 4 6 respectively Hybrid p laza In the case of the hybrid scenario, the Bea ch Line West toll plaza located along the Beachline Expressway (State Road 528), latitude 28.44 deg longitude 81.38 deg was utilized. The Beach Line West toll plaza contains seven toll lanes for each direction and is broken up into two distinct segments. The f irst segment is the ORT portion of the plaza which has a posted speed limit of 55 m i/ h In this segment there are t hree ETC ORT lanes. The second part of the plaza contains a traditional toll plaza configuration, with four cash toll lanes for users not utilizing the ETC ORT lanes. T he aerial photograph s and configuration of the Beach Line West toll plaza are shown in Figure 4 7 Figure 4 8 and Figure 4 9 respectively Res ults of Validation Testing To confirm the accuracy of the CORSIM improvements video data for the Leesburg and Beach Line West Plaza was analyzed. Using the collected data as inputs an attempt was made to recreate a 15 minute time period observed in the v ideo footage using CORSIM. To produce a more accurate representation of this 15 minute interval three time periods of five minutes each were utilized for each simulation. The summarized 5 minute interval data can be found in Table 4 35 and Table 4 36 These vehicle counts were then converted to hourly rates to be used as inputs. To confirm that the simulation s are accurately portraying the field data, each toll plaza model was simulated twelve times and t he average values obtained from the simulations were compared to the field data.

PAGE 61

61 Network Model Development When developing toll plaza network models in C ORSIM a certain amount of planning needs to be done first This is especially the case when developing network models that contain toll plazas with ETC only lanes. The reason for this is that the presence of ORT lanes requires a split to occur to separate the ETC only lanes from the traditional toll plaza. This is done by utilizing a FRESIM link with an off ramp. Care needs to be taken when determining which portion of the toll plaza, ETC only portion or traditional portion is incorporated into the off ramp. For the Beachline West toll plaza it was decided that the traditional portion of the toll plaza wou ld utilize the off ramp portion of the network model. This was decided based on the geometry of the plaza and regulatory speeds of the ORT lanes To simulate the ORT lanes, the regulatory speed limit was high enough to allow the utilization of FRESIM links for the entire ORT portion. See Figure 4 13 and Fig ure 4 14 for the developed network model of the Beachline West toll plaza In the case of the Leesburg toll plaza it was decided that the ETC only lane of the toll plaza would utilize the off ramp portion of the network model. The reason for this decision was due to the number of manual booth s at this toll plaza In the case of the ETC only lane for this plaza a combination of FRESIM and NETSIM links we re utilized for the network This was due to regulatory speed limit placed on the ETC only lane as it passed through the plaza. The regulatory speed of 25 mi/h cannot be accommodated by FRESIM links. As such, NETSIM links were utilized as the ETC only lane approached the toll plaza. See Figure 4 15 and Figure 4 16 for the developed network model of the Leesburg t oll p laza.

PAGE 62

62 Results With the network models for Leesburg and Beachline West toll plazas created, the y were simulated using the collected field data as inputs. Each toll plaza was simulated twelve times. Utilizing the output processor the following three traffic characteristics were collected: Traffic volume by vehicle type exiting the toll plaza Max imum queue length Average queue length Leesburg t oll p laza r esults The simulation results for the Leesburg toll plaza appear to be very promising. The Leesburg network model was found to be capable of producing passenger vehicle volumes that were within t hree to four vehicles of the five minute volumes collected in the field Simulation results of the truck volume were even more accurate, within one to two vehicles of the five minute volumes collected from the field data Testing for the queuing averages a nd maximum queue length also produced promising re sults. The average queue length s obtained from the video footage were a rough approximation. Even with this being the case, the CORSIM model produce d average queue lengths within the range observed from the video footage. I n addition to the average queue lengths, the maximum queue length observed in CORSIM, which averaged around three to four vehicles, matched up to the observed four vehicle maximum queue from the video footage. Results for this testing can be found in Table 4 37 and Table 4 38 Beachline West t oll p laza r esults The Beachline West toll plaza produced similar results seen in the Leesburg toll plaza Traffic volume did not match up as well as the Leesburg model. Even with this

PAGE 63

63 being the case, the Beachline West simulation was still typically within six vehicles of the five minute volumes obtained from the video footage. Concerning the average queue length and max imum queue length, the results w ere in the expected range. One observation that reinforces the validity of the CORSIM network model created is that the average queue length increase s as the 15 minute interval passes. During the 15 minute interval, the video footage showed a progressive increase in the traffic volumes on the roadway. This increase in traffic resulted in a slight increase to the average queuing observed. Results for this testing can be found in Table 4 39 and Table 4 40

PAGE 64

64 Table 4 1 Verification scenarios for payment distribution input Scenario ACM Manual Ticket ETC 1 100 % 0 % 0 % 0 % 2 0 % 100 % 0 % 0 % 3 0 % 0 % 100 % 0 % 4 0 % 0 % 0 % 100 % 5 0 % 0 % 50 % 50 % 6 50 % 50 % 0 % 0 % 7 10 % 10 % 0 % 80 % 8 15 % 15 % 50 % 20 % 9 20 % 20 % 20 % 40 % 10 10 % 60 % 10 % 20 % 11 20 % 20 % 50 % 10 % 12 5 % 85 % 5 % 5 % Table 4 2 Results 100% ACM payment ACM Manual Ticket ETC Total Volume (Vehicles) 1940.8 0 0 0 1940.8 Percent Distribu tion 100.00% 0.00% 0.00% 0.00% 100.00% Expected Distribution 100.00% 0.00% 0.00% 0.00% 100.00% Absolute Difference 0.00% 0.00% 0.00% 0.00% Percent Difference 0.00% 0.00% 0.00% 0.00%

PAGE 65

65 Table 4 3 Results 100% Manua l payment ACM Manual Ticket ETC Total Volume (Vehicles) 0 1940.8 0 0 1940.8 Percent Distribution 0.00% 100.00% 0.00% 0.00% 100.00% Expected Distribution 0.00% 100.00% 0.00% 0.00% 100.00% Absolute Difference 0.00% 0.00% 0.00% 0.00% Per cent Difference 0.00% 0.00% 0.00% 0.00% Table 4 4 Results 100% Ticket payment ACM Manual Ticket ETC Total Volume (Vehicles) 0 0 1991.4 0 1991.4 Percent Distribution 0.00% 0.00% 100.00% 0.00% 100.00% Expected Distribution 0.00% 0.00% 100.00% 0.00% 100.00% Absolute Difference 0.00% 0.00% 0.00% 0.00% Percent Difference 0.00% 0.00% 0.00% 0.00% Table 4 5 Results 100% ETC payment ACM Manual Ticket ETC Total Volume (Vehicles) 0 0 0 1940.8 1940.8 Percent Distribution 0.00% 0.00% 0.00% 100.00% 100.00% Expected Distribution 0.00% 0.00% 0.00% 100.00% 100.00% Absolute Difference 0.00% 0.00% 0.00% 0.00% Percent Difference 0.00% 0.00% 0.00% 0.00% Table 4 6 Results 0% ACM, 0% Manual, 50% Ticket, 50% ETC payment distribution ACM Manual Ticket ETC Total Volume (Vehicles) 0 0 542.3 559.6 1101.9 Percent Distribution 0.00% 0.00% 49.21% 50.79% 100.00% Expected Distribut ion 0.00% 0.00% 50.00% 50.00% 100.00% Absolute Difference 0.00% 0.00% 0.79% 0.79% Percent Difference 0.00% 0.00% 1.58% 1.56% Table 4 7 Results 50% ACM, 50% Manual, 0% Ticket, 0% ETC payment distribution ACM M anual Ticket ETC Total Volume (veh) 542.3 559.6 0 0 1101.9 Percent Distribution 49.21% 50.79% 0.00% 0.00% 100.00% Expected Distribution 50.00% 50.00% 0.00% 0.00% 100.00% Absolute Difference 0.79% 0.79% 0.00% 0.00% Percent Difference 1.58% 1.56% 0.00% 0.00%

PAGE 66

66 Table 4 8 Results 5% ACM, 85% Manual, 5% Ticket, 5% ETC payment distribution ACM Manual Ticket ETC Total Volume (veh) 45.8 737.4 40.5 43.2 866.9 Percent Distribution 5.28% 85.06% 4.67% 4.98% 100.00% Expected Distribution 5.00% 85.00% 5.00% 5.00% 100.00% Absolute Difference 0.28% 0.06% 0.33% 0.02% Percent Difference 5.51% 0.07% 6.79% 0.34% Table 4 9 Results 10% ACM, 10% Manual, 0% Ticket, 80% ETC p ayment distribution ACM Manual Ticket ETC Total Volume (veh) 97.8 94.6 0 773.2 965.6 Percent Distribution 10.13% 9.80% 0.00% 80.07% 100.00% Expected Distribution 10.00% 10.00% 0.00% 80.00% 100.00% Absolute Difference 0.13% 0.20% 0.00% 0.0 7% Percent Difference 1.28% 2.05% 0.00% 0.09% Table 4 10 Results 10% ACM, 60% Manual, 10% Ticket, 20% ETC payment distribution ACM Manual Ticket ETC Total Volume (veh) 97.7 589.4 95.8 188.7 971.6 Percent Distribution 10.06% 60.66% 9.86% 19.42% 100.00% Expected Distribution 10.00% 60.00% 10.00% 20.00% 100.00% Absolute Difference 0.06% 0.66% 0.14% 0.58% Percent Difference 0.55% 1.10% 1.41% 2.93% Table 4 11 Result s 15% ACM, 15% Manual, 50% Ticket, 20% ETC payment distribution ACM Manual Ticket ETC Total Volume (veh) 143 143 491.2 188.6 965.8 Percent Distribution 14.81% 14.81% 50.86% 19.53% 100.00% Expected Distribution 15.00% 15.00% 50.00% 20.00% 100 .00% Absolute Difference 0.19% 0.19% 0.86% 0.47% Percent Difference 1.30% 1.30% 1.70% 2.39% Table 4 12 Results: 20% ACM, 20% Manual, 20% Ticket, 40% ETC payment distribution ACM Manual Ticket ETC Total Vol ume (veh) 193.8 184.6 192.1 389.1 959.6 Percent Distribution 20.20% 19.24% 20.02% 40.55% 100.00% Expected Distribution 20.00% 20.00% 20.00% 40.00% 100.00% Absolute Difference 0.20% 0.76% 0.02% 0.55% Percent Difference 0.97% 3.89% 0.09% 1.36%

PAGE 67

67 Table 4 13 Results: 20% ACM, 20% Manual, 50% Ticket, 10% ETC payment distribution ACM Manual Ticket ETC Total Volume (veh) 193.7 185.7 484.3 94.4 958.1 Percent Distribution 20.22% 19.38% 50.55% 9.85% 100.00% Expected Distribution 20.00% 20.00% 50.00% 10.00% 100.00% Absolute Difference 0.22% 0.62% 0.55% 0.15% Percent Difference 1.08% 3.14% 1.09% 1.48% Table 4 14 Verification scenarios for mean service time input Pa yment Type Mean Service Time ACM FDOT Typical 2.5 sec Manual FDOT Typical 5.5 sec Ticket FDOT Typical 2.5 sec ETC FDOT Typical 1 sec ACM 4 sec ACM 7 sec ACM 9 sec ACM 13 sec Table 4 15 R es ults for 4 second service time testing Lane 1 Lane 2 Lane 3 Lane 4 Lane 5 Lane 6 Expected Service Time 4 4 4 4 4 4 CORSIM Service Time 4.1203 4.1185 4.0719 4.1476 4.1495 4.144 Difference (seconds) 0.12 0.119 0.072 0.148 0.15 0.144 Percent Diffe rence 2.96% 2.92% 1.78% 3.62% 3.67% 3.54% Table 4 16 R esults for 7 second service time testing Lane 1 Lane 2 Lane 3 Lane 4 Lane 5 Lane 6 Expected Service Time 7 7 7 7 7 7 CORSIM Service Time 7.1403 7.2994 6.9962 7.0208 7. 0065 7.1711 Difference (seconds) 0.14 0.299 0.0038 0.021 0.007 0.171 Percent Difference 1.98% 4.19% 0.05% 0.30% 0.09% 2.42% Table 4 17 R esults for 9 second service time testing Lane 1 Lane 2 Lane 3 Lane 4 Lane 5 Lane 6 Expected Service Time 9 9 9 9 9 9 CORSIM Service Time 9.1043 9.1868 9.3161 9.2429 8.8427 8.8973 Difference (seconds) 0.104 0.187 0.316 0.243 0.1573 0.1027 Percent Difference 1.15% 2.05% 3.45% 2.66% 1.76% 1.15%

PAGE 68

68 Table 4 18 R esults for 13 second service time testing Lane 1 Lane 2 Lane 3 Lane 4 Lane 5 Lane 6 Expected Service Time 13 13 13 13 13 13 CORSIM Service Time 13.077 13.177 12.918 12.889 13.427 12.686 Difference (seconds) 0.077 0.177 0.0822 0.1111 0.427 0 .3143 Percent Difference 0.59% 1.36% 0.63% 0.86% 3.23% 2.45% Table 4 19 FDOT typical testing ACM and Ticket payment Lane 1 Lane 2 Lane 3 Lane 4 Lane 5 Lane 6 Volume 609.1 607.2 611.4 610.5 609.4 608.4 Expected Processing Rate 9 9 9 9 9 9 CORSIM Processing Rate 5.9104 5.9289 5.8881 5.8968 5.9074 5.9172 Expected Service Time 3.0896 3.0711 3.1119 3.1032 3.0926 3.0828 CORSIM Service Time 2.2253 2.2468 2.2002 2.2148 2.2147 2.2384 Table 4 20 FD OT typical testing Manual payment Lane 1 Lane 2 Lane 3 Lane 4 Lane 5 Lane 6 Volume 403.4 397.3 404.4 404.3 400.8 406 Expected Processing Rate 9 9 9 9 9 9 CORSIM Processing Rate 8.9241 9.0612 8.9021 8.9043 8.982 8.867 Expected Service Time 5.3 5.3 5.3 5.3 5.3 5.3 CORSIM Service Time 5.4037 5.5261 5.3869 5.3748 5.4526 5.3157 Table 4 21 FDOT typical testing ETC payment Lane 1 Lane 2 Lane 3 Lane 4 Lane 5 Lane 6 Volume 690.6 688.4 693.4 690.8 688.2 691.7 Expected Process ing Rate 4.5 4.5 4.5 4.5 4.5 4.5 CORSIM Processing Rate 5.2129 5.2295 5.1918 5.2113 5.231 5.2046 Expected Service Time 1 1 1 1 1 1 CORSIM Service Time 1.3693 1.39 1.3571 1.3759 1.3841 1.3629 Table 4 22 0 second service tim e scenario Toll Booth 1 2 3 4 5 6 Average Service Time 0.0 0.0 0.0 0.0 0.0 0.0 Average Speed 42.4 42.5 42.7 42.5 42.4 41.9

PAGE 69

69 Table 4 23 Payment restriction testing Lane 1 Lane 2 Lane 3 Lane 4 Lane 5 Lane 6 Sta tus Closed Open* Open* Open* Closed Closed Expected Volume 0 277 277 277 0 0 CORSIM Volume 0 278 277.1 275.6 0 0 Assuming 13 second processing rate Table 4 24 Results Trucks restricted to one lane no car restricti ons Vehicle type 1 2* 5 6* 7* 8* Booth 1 259.7 22.0 88.5 27.6 17.3 6.0 Booth 2 291.2 0.0 103.1 0.0 0.0 0.0 Booth 3 292.2 0.0 92.3 0.0 0.0 0.0 Booth 4 280.1 0.0 96.7 0.0 0.0 0.0 Booth 5 299.0 0.0 94.0 0.0 0.0 0.0 Booth 6 320.1 0.0 109.0 0 .0 0.0 0.0 Denotes heavy vehicle vehicle types Table 4 25 Results Trucks restricted to two lanes cars restricted to four lanes Vehicle type 1 2* 5 6* 7* 8* Booth 1 0.0 98.8 0.0 112.0 72.1 24.8 Booth 2 0.0 92 .9 0.0 103.7 69.2 29.5 Booth 3 320.9 0.0 113.8 0.0 0.0 0.0 Booth 4 326.2 0.0 111.0 0.0 0.0 0.0 Booth 5 333.6 0.0 109.7 0.0 0.0 0.0 Booth 6 357.1 0.0 117.9 0.0 0.0 0.0 Denotes heavy vehicle vehicle types Table 4 26 Results two vehicle type s to two toll booths assignment Vehicle type 1 a 2 a 5 b 6 b 7 c 8 c Booth 1 287.0 112.6 0.0 0.0 0.0 0.0 Booth 2 253.1 107.2 0.0 0.0 0.0 0.0 Booth 3 0.0 0.0 271.7 114.9 0.0 0.0 Booth 4 0.0 0.0 272.7 114.1 0.0 0.0 Boot h 5 0.0 0.0 0.0 0.0 112.9 118.5 Booth 6 0.0 0.0 0.0 0.0 105.8 108.3 a Denotes vehicle types restricted to Booths 1 & 2 b Denotes vehicle types restricted to Booths 3 & 4 c Denotes vehicle types restricted to Booths 5 & 6

PAGE 70

70 Table 4 27 Multiple time period verification scenario Toll Booth 1 2 3 4 5 6 7 8 Time Period 1 Open Open Open Open Open Open Open Open 2 Open Open Open Open Open Open Closed Closed 3 Closed Open Open Open Open Open Open Open 4 Open Open Closed Closed Open Open Open Open Table 4 28 Results of multiple time period testing Toll Booth Volumes (vph) 1 2 3 4 5 6 7 8 Time Period 1 25.1 22.8 29.3 46.5 75.1 94.4 100.1 104.3 2 52.2 51.3 74.4 92.9 110 118.2 0* 0* 3 0* 6.1 19.1 50.1 88.5 1 11.6 1 14 4 111.7 4 51.3 54.4 0* 0* 45.1 87.8 123.1 139.6 Denotes that toll booth was closed during time period Table 4 29 Traffic volumes for Beachline West t oll plaza Manned Booths Open Road ETC Cash SunPass Cash* SunPass Weekend PM Average 8,845 62 920 11,221 Total 70,757 494 7,363 89,771 AM Average 4,495 30 502 6,814 Total 35,962 239 4,016 54,516 Weekday PM Average 4,426 30 914 12,246 Total 101,790 699 21,017 281,653 AM Average 7,970 53 581 10,757 Total 183,321 1,208 13,370 247,414 Entire Weekend Average 13,340 92 1,422 18,036 Total 106,719 733 11,379 144,287 Entire Weekday Average 12,396 83 1,495 23,003 Total 285,11 1 1,907 34,387 529,067 All Days Average 12,640 85 1,476 21,721 Total 391,830 2,640 45,766 673,354 These vehicles are toll violators

PAGE 71

71 Ta ble 4 30 Traffic volume for Leesburg toll plaza Manned Booths Dedicated ETC Cash SunPass Cash* SunPass Weekend PM Average 2,905 50 136 2,842 Total 66,823 1,160 3,117 65,361 AM Average 5,114 151 191 4,538 Total 117,632 3,474 4,397 104,373 Weekday PM Average 8,827 71 237 5,707 Total 70,619 565 1,897 45,659 AM Average 3,954 34 117 2,368 Total 31,633 273 938 18,945 Entire Weekend Average 8,020 201 327 7,380 Total 184,455 4,634 7,514 169,734 Entire Weekday Average 12,782 105 354 8,076 Total 102,252 838 2,835 64,604 All Days Average 9,249 177 334 7,559 Total 28 6,707 5,472 10,349 234,338 These vehicles are toll violators Table 4 31 Standard t oll p laza c apacities and r ates a long Florida t oll r oads ( s ingle p ayment t ype l ane) Lane Type Capacity (vph) Rate veh/s High Speed SunPass only 2100 1.71 D edicated SunPass (M ainline) 1700 2.12 D edicated SunPass (Ramps) 1300 2.77 A utomatic coin 500 7.2 M anual/automatic 400 9 M anual booth 400 9 M anual ticket entry 500 7.2 M anual ticket exit 180 20

PAGE 72

72 Table 4 32 Table 4 33 Leesburg 15 minute traffic data Total Volume/Car Volume/Truck Volume ETC Lane Manual 1 Manual 2 Manual 3 46:00 47:00 14/14/0 1/1/0 3/3/0 8/8/0 47:00 48:00 16/14/2 5/5/0 0/0/0 3/2/1 48:00 49:00 22/22/0 6/6/0 7/7/0 1/1/0 49:00 50:00 17/17/0 6/6/0 2/2/0 7/7/0 50:00 51:00 13/13/0 7/7/0 2/1/1 1/1/0 51:00 52:00 11/9/2 4/4/0 3/3/0 5/4/1 52:00 53:00 10/9/1 5/5/0 1/1/0 1/1/0 53:00 54:00 16/12/4 6/6/0 5/5/0 6/6/0 54: 00 55:00 21/21/0 2/2/0 3/3/0 3/3/0 55:00 56:00 13/12/1 3/3/0 6/6/0 4/1/3 56:00 57:00 12/11/1 6/6/0 3/3/0 1/0/1 57:00 58:00 7/7/0 5/5/0 4/4/0 3/2/1 58:00 59:00 20/20/0 6/6/0 4/4/0 4/4/0 59:00 1:00:00 17/16/1 7/7/0 3/3/0 5/4/1 1:00:00 1:01:00 16/ 16/0 5/5/0 5/5/0 2/2/0 Total Volume 225/213/12 51/51/0 51/50/1 54/46/8 System Type Assumed SunPass Rate Capacity ( v eh/ h ) Northern Coin Cash/ETC 64% 718 South Ticket (MP 88 142) ME/ETC 74% 918 MX/ETC 74% 621 North Ticket (MP 142 236) ME/ETC 59% 785 MX/ETC 59% 478 Southern Coin Cash/ETC 70% 776 BeachLine West Cash/ETC 60% 684 Sawgrass Cash/ETC 79% 883 Seminole Cash/ETC 75% 832 Veterans Cash/ETC 68% 756 Southern Connector Cash/ETC 65% 727 Polk Pkwy Cash/ETC 55% 64 6 Suncoast Pkwy Cash/ETC 67% 746

PAGE 73

73 Table 4 34 Beachline West 15 minute traffic data Total Volume/Car Volume/Truck Volume ETC Lane Manual 1 Manual 2 Manual 3 01:00 02:00 37/33/ 4 4/4/0 5/5/0 6/6/0 02:00 03:00 27/26/1 4/4/0 1/1/0 2/2/0 03:00 04:00 32/31/1 2/2/0 4/4/0 2/2/0 04:00 05:00 27/27/0 2/2/0 0/0/0 1/1/0 05:00 06:00 45/40/5 2/2/0 3/3/0 3/3/0 06:00 07:00 42/41/1 2/2/0 3/3/0 5/5/0 07:00 08:00 38/37/1 5/5/0 3/3/0 4/ 4/0 08:00 09:00 39/38/1 4/4/0 2/2/0 3/3/0 09:00 10:00 26/24/2 3/3/0 5/5/0 2/2/0 10:00 11:00 39/33/3 4/4/0 3/3/0 3/3/0 11:00 12:00 45/42/3 4/4/0 3/3/0 2/2/0 12:00 13:00 46/41/5 5/5/0 5/5/0 3/2/1 13:00 14:00 62/61/1 4/4/0 5/5/0 4/4/0 14:00 15:0 0 38/38/0 4/3/1 5/5/0 6/6/0 15:00 16:00 31/30/1 3/3/0 5/5/0 3/2/1 Total Volume 574/545/29 52/51/1 52/52/0 49/47/2 Table 4 35 Five minute interval data for Leesburg Toll Plaza Entry Volume ETC Only Volume Toll Plaza Vo lume Total Car Truck Total Car Truck Total Car Truck Interval 1 141 137 4 82 80 2 59 57 2 Interval 2 128 116 12 71 63 8 57 53 4 Interval 3 135 130 5 72 70 2 63 60 3 Table 4 36 Five minute interval data for Be achline West Toll Plaza Entry Volume ETC Only Volume Toll Plaza Volume Total Car Truck Total Car Truck Total Car Truck Interval 1 209 198 11 168 157 11 41 41 0 Interval 2 235 224 11 184 173 11 51 51 0 Interval 3 283 270 13 222 212 10 61 58 3 Table 4 37 Volume comparison Leesburg Toll Plaza Toll Plaza Volumes ORT Volumes Total Cars Trucks Total Cars Trucks Interval 1 Field Data 59 .0 57 .0 2 .0 82 .0 80 .0 2 .0 CORSIM Results 57.1 55.1 2 .0 81.7 79 .6 2.1 Interval 2 Field Data 57 .0 53 .0 4 .0 71 .0 63 .0 8 .0 CORSIM Results 59. 7 55. 6 4. 1 73.4 66.3 7. 1 Interval 3 Field Data 63 .0 60 .0 3 .0 72 .0 70 .0 2 .0 CORSIM Results 63 .0 60.3 2. 8 70. 3 67.6 2. 7

PAGE 74

74 Table 4 38 Queuing com parison Leesburg Toll Plaza Interval 1 Interval 2 Interval 3 Expected Queue Booth 1 0. 44 0. 46 0.7 8 1 2 Booth 2 0.82 0.82 1.22 1 2 Booth 3 1. 22 1.16 1.63 1 2 Avg Max Queue 3. 25 3. 17 4.08 3 4 Table 4 39 Volu me comparison Beachline West Toll Plaza ORT Volumes Toll Plaza Volumes Total Cars Trucks Total Cars Trucks Interval 1 Field Data 168.0 157.0 11.0 41.0 41.0 0.0 CORSIM Results 167.3 157.4 9.9 39.8 39.8 0.0 Interval 2 Field Data 184.0 173. 0 11.0 51.0 51.0 0.0 CORSIM Results 176.7 166.1 10.6 52.9 52.9 0.0 Interval 3 Field Data 222.0 212.0 10.0 61.0 58.0 3.0 CORSIM Results 210.8 201.4 9.4 62.0 59.1 2.9 Table 4 40 Queuing comparison Beachline West Toll Plaza Interval 1 Interval 2 Interval 3 Expected Queue Booth 1 0.34 0. 51 0. 78 1 Booth 2 0. 71 0.91 1. 25 1 Booth 3 1. 02 1. 13 1. 48 1 Avg Max Queue 3. 00 3. 16 3.6 7 2 3

PAGE 75

75 Figure 4 1 Link n ode diagram of gene ric toll plaza Figure 4 2 Six lane generic toll plaza developed for service time verification Figure 4 3 Eight lane generic toll plaza developed for payment distribution verification Figu re 4 4 Verification testing results for toll booth restrictions

PAGE 76

76 Figure 4 5 Aerial view of Leesburg toll plaza Figure 4 6 Toll booth configuration for Leesburg toll plaza (Courtesy of FDOT)

PAGE 77

77 Figure 4 7 Aerial view of Beach Line West toll plaza eastbound approach Figure 4 8 Aerial view of Beach Line West toll plaza westbound approach

PAGE 78

78 Figure 4 9 Toll booth configuration for Beach Line West toll plaza (Courtesy of FDOT) Figure 4 10 Location map of toll plazas for study

PAGE 79

79 Figure 4 11 Traffic conditions at Lee sburg toll plaza during study period Figure 4 12 Traffic conditions at Beachline West toll plaza during study period

PAGE 80

80 Figure 4 13 CORSIM n ode l ink d iagram for Beachline West Toll Plaza Fig ure 4 14 CORSIM model of the Beachline West Toll Plaza Figure 4 15 CORSIM n ode l ink d iagram for Leesburg Toll Plaza Figure 4 16 CORSIM network model of the Lees burg Toll Plaza

PAGE 81

81 CHAPTER 5 SUMMARY AND RECOMENDATIONS Summary The results of this study produced the integration of toll plaza modeling into CORSIM. To accomplish this, new algorithms were developed for CORSIM. These new algorithms and their required inpu ts were then verified for accuracy and constancy during the verification testing. During this testing, various experiments were developed to test each algorithm and input individually. Once it was determined that the toll plaza features were working correc chosen to be simulated by CORSIM as a means to validate the simulation tool. Traffic data and video footage for these two toll plazas were obtained from FDOT. This information was input into th e developed CORSIM network models for the two toll plazas to see if CORSIM would produce similar outputs. From this testing, it was determined that CORSIM could accurately model real life traffic conditions at toll plazas. This was determined by comparing the outputs produced by CORISM to various traffic data collected at the toll plazas. From this, it was determined that the two CORSIM toll plaza models and real toll plazas had very similar volume and queuing characteristics To assist users in simulating toll plazas, research was also conducted on establishing reasonable default values for various toll plaza inputs for CORSIM. These default values give users fairly accurate inputs without the need for expensive traffic studies and data collection. This res earch led to the creation of default service times for four payment types commonly found in Florida, as well as default values for queue setback distance and lane change sensitivity.

PAGE 82

82 This research also led to the development of an equation to estimate pull up time. Pull up time is the time it takes a vehicle in the first queue position at a toll booth to accelerate, decelerate, and stop immediately adjacent to the toll booth. This pull up time equation allows users to estimate an average service time input for CORSIM for any payment type based to obtain the desired processing rate. Recommendations During the process of completing this research some additional improvements for toll plaza modeling in CORSIM were thought of but were outside of the scope of th is project It is recommended that further research be conducted on the following items. User Specified Acceleration and Deceleration Rates for Toll Plaza Links As mentioned previously, it is believed that vehicles approaching and departing a toll plaza us e higher acceleration/deceleration rates than typically observed at other control devices (e.g., signalized intersections) While CORSIM allows a user to modify the acceleration/deceleration rates for an entire network, it does not allow these rates to be varied at a link level. The higher acceleration and deceleration rates would possibly lead to more accurate values of control delay. Integration of ORT Lanes into Toll Plaza Link One current inconvenience that would be nice to address is having to code ETC only lanes separate from the toll plaza link Currently the toll plaza link cannot handle an ETC only lane built into the toll plaza link. Instead a separate link, parallel to the toll plaza link, is used to simulate ETC only lanes. This is because ETC o nly lanes are not stop controlled and operate at either the free flow speed of the freeway or at a reduced speed, usually 25 mph to 35 mph as specified by regulatory signs To accomplish this i t

PAGE 83

83 will be necessary to make two improvements within the CORSIM framework to allow ETC only lanes to be integrated into the toll plaza link First, changes will need to be made to the toll plaza stop control device that will allow the user to individually specify which lanes to apply the toll plaza stop control device. It is possible to bypass this issue b y assigning a service time of 0 seconds for one payment type This would allow the selected payment type to bypass stopping at the toll booth. However, by utilizing this method the user is unable to adjust the speed of the ETC only lanes This prevents this method from being used for ORT lanes. To fully integrate ORT/ETC only lanes i t would be necessary to improve NETSIM links to allow for multiple free flow speed s along a single link. Currently, CORSIM only allows a us er to specify one free flow speed for each link. By making this change it would allow a user to specify the thru speed for the ORT lane and the approach speed for the traditional toll lanes. As nice as this improvement would be, it is not always desira ble to incorporate the ORT lanes into the toll plaza. This is due to the fact that many of the newly developed toll plazas have a distinct separation between the toll plaza and the ORT lanes. However, for cases where there is no physical separation between the ORT lanes and the toll plaza integrating the ORT lanes into the toll plaza link w ould likely increase the accuracy of the simulation Logit Model for Toll Lane Selection In the future one possible improvement that could be made to the developed CORSIM model would be to implement a multinomial logit model to determine toll plaza lane selection Logit models are well suited to the modeling of unordered discrete choices. The basis of the Logit model, the utility equation, would likely be a function of

PAGE 84

84 vari and a given toll plaza lane, queue length at toll plaza lane, and number of trucks in queue. From the developed utility equation utility values would be calculated for each t oll lane. Based on the calculated utility values the probability of selecting each toll lane would be calculated. The probability values would be compared to uniformly generate d random numbers to determine the lane selection However, any improvement in t he accuracy of toll lane selection due to a Logit model must be weighed against increases in computation time due to more mathematical calculations.

PAGE 85

85 APPENDIX A CORSIM USER GUIDE FOR TOLL PLAZA MODELING Overview This appendix serves as a guide for CORSIM users to learn how to properly code a toll plaza section into CORSIM 6.3 This guide includes detailed discussion on the necessary input values, description of the new record types and fields, allowable ranges and default values and the proper formatting of the .trf code. The end of this guide will include a step by step walkthrough of coding a toll plaza into CORSIM 6.3. Toll Plaza Data Discussion Before getting into the discussion on each toll plaza record type and w h ere each item of input data is enter ed into CORSIM it is important to understand the necessary data needed to properly simulate any given toll plaza. This information can be broken up into two categories; essential toll plaza data and secondary toll plaza data. Essential Toll Plaza Data Es sential toll plaza data is data that is absolutely necessary to adequately simulate a toll plaza in CORSIM Not inputting this information into CORSIM will cause fatal errors when a simulation of a network containing toll plazas is attempted This informat ion includes traffic and toll plaza characteristics. When attempting to simulate a toll plaza there is one primary traffic characteristic needed by CORSIM : the percentile distribution of each payment type within the traffic stream. This information is ne cessary for CORSIM to simulate a toll plaza because CORSIM utilizes these percentile inputs to properly distribute all the available payment types to the vehicles entering the toll plaza segment. In addition to the basic percentile distribution, additional information concerning the ETC payment type may be needed.

PAGE 86

86 This is only necessary i f ETC only lanes are available at the toll plaza. When ETC only lanes are available, a percentile distribution is needed of ETC users utilizing the ETC only lane (s) and ETC users utilizing the traditional toll lanes. The reason for this will be discussed in more detail in section In addition to the traffic characteristics just discussed, there is an essential datum needed concerning the toll plaza characteristics This datum concerns the payment types accepted at each toll booth. Currently there exist a wide variety of payment configurations utilized at toll plazas such as ETC only, mixed use, ETC and ACM to name a few. In addition to this, a sing le toll plaza can utilize a different payment combination for each of its toll booths. To accommodate this wide variety of toll plaza configurations it was determined that the user would have to specify the payment types accepted at each toll booth. To en sure that all applicable payment types are accepted at the plaza a fatal error will occur if a payment type specified by the payment distribution input is not accepted at the toll plaza. Secondary Toll Plaza Data Secondary toll plaza data is additional in formation concerning the toll plaza that is not absolutely necessary to simulate a toll plaza. This informati on adds additional data that will improve the accuracy of the simulation ; however default values for the se inputs are already specified in CORSIM. Failure to input this data will not result in a fatal error. There are currently four toll plaza inputs that fall into this category of secondary data; inputs include queue setback distance, payment average service time, reaction point where the toll lane selection algorithm takes effect and vehicle sensitivity to lane changes for toll booth selection.

PAGE 87

87 Queue setback distance Toll plazas typically do not allow vehicles to queue bumper to bumper directly behind the vehicle at the toll booth. Instead, a sign is usually used to inform the first vehicle in the queue where they are required to stop. This setback distance is utilized to provide additional safety to the toll booth workers. To accommodate this issue, a queue setba ck distance input was incorporated into CORSIM. This value provides the user with the ability to define what the required pull up distance is in feet, and is a factor in the pull time time discussed in the next section. The default value for this input is 25 feet with an input range of 0 99 feet Average s ervice t ime Ideally, for modeling existing toll plazas, average service times should be measured in the field However when this is not possible or a future toll plaza is being simulated, typical service times for four payment types commonly found Florida were identified See for the service times for each payment type These service time s were obtained from average processing rates for four payment type s obtained from FDOT. Th e FDOT information provides b asic service times for four payment types utilized on toll roads state wide. based on the average service time for vehicles entering a ticket toll system ; the service time for an exit toll bo oth is much higher, around twenty seconds instead of seven seconds. It is important to note that there is a distinct difference between service time and processing rate. The processing rate of a toll booth or payment type is the combination of the pull up time and the service time. If only the processing rate was obtained, use the following equation to estimate what portion of the processing rate can be attributed to the pull up time:

PAGE 88

88 ( A 1 ) By knowing the proces sing rate and estimating the pull up time the service time can be determined. Reaction point for toll plaza w arning s ign To ensure that vehicles have adequate distance to get to their desired toll booth a user specified reaction point distance input was created for toll plazas T his reaction point can be loosely translate d into real world t erms as the first road sign informing drivers that they are approaching a toll plaza. This sign would also contain information directing what payment type is accepted at each toll booth. It is after vehicles pass this reaction point that they are randomly assigned a payment type based on the payment distribution input previously mentioned. It is at this point that vehicles start to identify which toll booth is preferred type, queue length, and number of required lane changes) In the case of the user not specifying an input for the reaction point, the reaction point distance is established by either a default dis tance of fifteen hundred feet or if the link containing the toll plaza is directly connected to an inter face node the inter face node would serve as the reaction point. Lane change s ensitivity to toll lane selection When the toll lane selection process is being applied to a vehicle, the toll lane selection algorithm utilizes an equation that evaluates each toll lane relative to the toll lane a vehicle is currently in. This equation utilizes relative queue length required number of lane changes, and a sensi tivity factor. The sensitivity factor is a variable that affects to save one queue space The input range for this value is 0 to 3 with 0 meaning a vehicle is very willing to make a lane

PAGE 89

89 change and 3 less likely to make a lane change If no value is input then a default sensitivity of 0.7 is utilized by CORSIM. The equation used to assist with toll lane selection is as follows: (A 1 ) where, = Toll lane desirabilit y of toll lane j and adjacent toll lane = Number of lane changes required for vehicle to reach toll lane j = Lane change sensitivity factor (default value = 0.7) To better understand how the toll lane desirability equation is used, a hypothetical toll plaza scenario was developed. See Figure A 1 for the visual representation of the toll plaza. For this configuration, the subject vehicle would first identify that toll booth 5 is closed and remove it from consideration. Next, each toll lane is evaluated, relative to the the left most toll lane. If that toll lane accepts the 1 is applied. For example, for lane 1 in Figure A 1 the subject vehicle approaches in lane 3, so the difference in queue is 2 vehicles and th e number of lane changes to move to that lane would be 2. Thus, the TLD value is calculated as follows, (A 2 )

PAGE 90

90 Note that if the current lane the vehicle is in has a queue length less than or equal to the queue length of any other toll lane, the vehicle will c ontinue in that lane. The results from applying Eq. 3 1 to the other lanes are shown in Table A 1 Based on these re sults, the subject vehicle would choose toll booth 1 as its desired toll booth. Output Processor For toll plaza simulation two new MOE categorie s were developed to collect data concerning the toll plaza portion of the network. In the output processor window these including average service time, exit volumes, density, average speed, and average delay per vehicle. It should be noted that the service time output produces an output of an av erage service time for each toll lane. This means that the service time output will be based on the weighted average of the service times of the payment types assigned to that toll booth. the traffic volumes exiting each toll booth by each payment type. This means that if a user wishes to gather information concerning the traffic volumes for each payment type at each toll booth this MOE would be utilized. Record Type Discussion To fully u nderstand how the toll plaza modeling functions it is necessary to describe in detail the record types pertaining to toll plaza simulation. For toll plaza simulation three record types are utilized by CORSIM to specify the necessary input data It should be noted that each of these record types can be modified in different time periods.

PAGE 91

91 Record Type 82 Record T ype 82 contains information concerning the mean service times for all four payment types a nd the location upstream of the toll plaza where drivers r eact to a toll warning sign T o properly input the mean service time for each toll payment type it is important to remember that service time is input as tenths of a second T his means that a desired service time of 7 seconds would be repres ented by 70 in the .trf format. Concerning the toll warning sign input, this value is specified in feet in the .trf format. Formatting for Record Type 82 can be found in Figure A 2 The input range for each service time is 0 9999 tenths of a second. Record Type 83 Record T ype 83 contains information pertaining to the status of the toll booth. This information includes payment types accepted at each toll booth, vehicle types allowed to utilize each toll booth, queue setback distance at the toll booth, and the lane changing sensitivity factor. It was determined that the best way to implement payment acceptance and toll booth status, open or closed, for a toll booth into CORSIM was to combine both values into one input. This was done b y utilizing a four digit binary code to tell CORSIM what payment type is accepted at each toll booth. In this binary format type is accepted at the boot h. Each toll booth has its own binary code allowing the user being accepted at a toll booth, that is, 0 for all payment types, the toll booth in question is consider ed to be closed and no vehicles will utilize it. See Table A 1 for payment location within the binary code.

PAGE 92

92 A binary coding configuration was also utilized for the vehicle restriction input. For this input a sixteen digit binary code is utilized to represent th e sixteen vehicle types available in CORSIM. For this coding a 0 represents that the vehicle type can utilize the toll booth and a 1 means the vehicle type cannot use the toll booth. Refer to the CORSIM user manual for a detailed description of each vehic le type. Record Type 83 also contains the input information for the queue setback distance and the lane changing sensitivity factor. The units for queue setback distance are feet. Th e value for queue setback distance can range from 0 to 99 feet The lane c hanging sensitivity factor corresponds to the willingness of a driver to make a lane change to save time in the queue. T his value is input in tenths of a second and ranges 0 to 30 (i.e., 0 to 3 seconds) Formatting and input locations for Record Type 83 ca n be found in Fi gure A 3 Record Type 84 Record Type 84 contains the payment distribution information for the four payment types. The payment distribution for each payment type is represent ed by a whole number from 0 to 100. A fat al error is produced from this record type if the sum of the various payment distributions does not add up to 100. Formatting for Record Type 84 can be found in Figure A 4 Simulating ORT Lanes Simulating ORT lanes creates an inte resting challenge when trying to model a toll plaza. The main issue with ORT lanes is that vehicles do not have to reduce their speed to travel through the plaza This creates a dilemma for one reason. First, a single CORSIM link cannot currently accommoda te different speeds for each lane

PAGE 93

93 To resolve these issues it was determined that currently the best solution to accommodate ORT lanes was to create ORT lanes on a link parallel to the toll plaza. By know ing the overall ETC penetration and percentage of ETC vehicles that utilize mix ed used payment lanes at a toll plaza a diagonal turning movement can be coded into CORSIM To ensure that ETC vehicles assigned to the ORT lane s utilize the proper lane record type 81 is utilized. Record type 81 is utilized to specify in percent how cooperative the subject vehicle is to allowing a vehicle making lane changes. By inputting a high cooperation value vehicles are more likely to allow other vehicles to make lane changes into the ORT/ETC only lanes. To simulate ORT and ETC only lanes both NETSIM and FRESIM links can be used Typically a FRESIM link is desired as it can handle diagonal lane changes much better than NETSIM links ; however this should not be the deciding factor in using FRESIM over NETSIM links. To de termine which type of CORSIM link to utilize the speed and type of the ORT lanes should be looked at A FRESIM link should be utilized for the following scenarios; when no deceleration is required to go thru the ORT lane s the ORT lane s are integrated int o the mainline freeway and operate at the same regulation speed as the freeway containing the toll plaza, or there is a distinct physical separation between the ORT /ETC only lanes and the toll plaza. NETSIM links on the other hand should be utilized when t he speed thru the ORT is not the speed of the freeway or there is no separation between the ORT lanes and the toll plaza. See Figure A 5 and Figure A 6 for depiction on when to use FRESIM or NETSIM links to simulate ORT lanes. See Figure A 7 and Figure A 8 for depiction of networks utilizing ORT lanes.

PAGE 94

94 Example Problems This section provides t hree examples on how to code toll plazas into CORSIM 6.3 These examples include a basic complex and multi time period toll plaza models. Since there is no plan to incorporate the toll plaza inputs into TRAFED, graphical user input concerning toll plaza inputs are provided by TSIS Next the newest version of CORSIM t hat integrates TRAFED and TRAVU into one program A ll other visual inputs are provided by TRAFED of CORSIM 6.3 At the end of this section the .trf formatted simulations are provided for the three examples Example 1 This example is based on a traditional toll plaza without ORT lanes. The inputs are as followed: Simulation length of 15 minutes Traffic volume of 20 00 vehicles per hour Assume there are no heavy vehicles Two lane approach and departure Approach length of 1500 feet Departure length of 1500 fee t Four lane toll plaza Payment types accepted at the plaza are ETC and Manual Toll booth 1 accepts ETC Toll booth 2 and 3 accepts ETC and Manual Toll booth 4 accepts Manual Payment distribution is 70% ETC 30% Manual Manual payment type service time is 5.5 seconds/vehicle ETC payment type service time is 1.5 seconds/vehicle Queuing offset of 5 feet Lan e change sensitivity factor of 0 7 Simulation and n etwork s etup Similar to setting up a normal CORSIM simulation the first s tep is setting up the network prop erties inputs and network inputs. The network properties screen is the first input screen seen when opening a new TSIS Next model This includes the simulation

PAGE 95

95 length number of time periods, and simulation start time. For this example the only input that needs to be adjusted is the simulation length, which is input as 900 seconds. See Figure A 9 for screen shot of network properties input screen. With the network properties input the next step is to build the network For this exa mple only NETSIM nodes and links are needed. For this network e ach node is spaced 500 feet apart and connected by a link. Using a multiple link approach for a toll plaza allows the user to incrementally increase the number of lanes on each link until the n umber of lane of the link matches the number of toll lanes of the plaza. When increasing the number of lanes make sure that the lane alignment matches the desired direction of lane fanning out. Figure A 10 Figure A 11 and Figure A 12 provide node and link configuration for Example 1. After building the network the entry traffic volume is entered into the entry node. Toll p laza s etup Now that the simulation and network have been setup the next step is to setup the toll plaza inputs. window For this example link [3,4] contains window open bring up the toll plaza tab, within this tab contains all the inputs needed to code the toll plaza. These plaza exists Once the icon is selected the toll plaza inputs can be changed. First to bit of information to be added to this section is payment typ es accepted at each toll booth. Each box correlates to a toll booth and payment type. The numbering for toll booths starts from right to left, this means that the far left lane is toll booth 1. In the .trf format coding of the toll booths is right to left. After configuring the toll booths the next step is to input the service times and payment distribution values. At this point, if there were desired processing rates for

PAGE 96

96 each payment type the pull up equation would be utilized to calculate the actual serv ice for each payment type. For this example a service time was provided so this step is skipped and service times and payment distribution values are input. Finally, the last inputs entered into this window are the setback distance and lane change sensitiv ity values. See Figure A 13 for a screen shot of the completely input toll plaza tab for this example. With this information input the model is built and ready to be run. Figure A 14 and Figure A 15 provide examples of the toll plaza simulation based on the inputs provided. Output p rocessor With the toll plaza model created data can now be collected from the simulation using the output processor. For this example the output proces sor is going to be used to determine lane utilization by payment type for the entire fifteen minute simulation. To do and under the object section select all objects under the important that the CVS file format is selected as this is the only file type available that outputs toll plaza information. See Figure A 16 for a visual of the output processor configuration. With the output processor configured, the multiple run tool is utilized to collect the desired information. Table A 3 h as the results of this testing. The for matting for Example 1 can be found in Appendix B This concludes Example 1. Example 2 E xample 2 utilizes a real life toll plaza For this example the Beachline W est toll plaza along the Beachline Expressway wa s utilized. This is a much more complex

PAGE 97

97 network that requires the implementation of ORT lanes. For this example service time and exiting volumes will be collected. Inputs used for this simulation are below: Simulation length of 15 minutes Traffic volume of 3 000 vehicles per hour Assume there are no hea vy vehicles Four lane approach Three lane departure Approach length of 1500 feet Departure length of 1500 feet Four lane toll plaza Three lane ORT segment Payment types accepted at the plaza are ETC ACM, and Manual payment types Toll booth 1 2,3, and 4 a ccepts ETC ACM, and Manual payment types Payment distribution is 80% ORT ETC users and 20% traditional toll plaza users with 6 0% ETC, 30 % Manual and 10% ACM Manual payment type processing rate is 10 seconds/vehicle ETC payment type processing rate is 5 s econds/vehicle ACM payment type processing rate is 7 seconds/vehicle Queuing offset of 5 feet Lane change sensitivity factor of 0.7 Simulation and n etwork s etup As the basics of developing a network for toll plaza have already been discussed in detail thi s section will look more at implementation of ORT lanes into a toll plaza simulation. When coding toll plazas with ORT lanes the user must first determine which part of the toll plaza will be the mainline portion. This is typically determined by either

PAGE 98

98 the number of ORT lanes or the location of the ORT lanes. In the case of this scenario the ORT lanes are the mainline. As it can be observed in Figure A 17 the aerial provided demonstrates the reason that the ORT lanes were chosen f or the mainline portion In this case the reason was because of location When compared to the traditional toll plaza location it appears that the lanes to the traditional plaza appear to be an off ramp If this was the Leesburg toll plaza the t raditional portion of the plaza would be the mainline. Figure A 18 depicts the network split and Figure A 19 provides the completed node and link diagram for this network. Note that in the node and link d iagram the toll plaza node, node 7, matches up with a node along the ORT section, node 3. This network design can assist the user in collecting data for the toll plaza as both nodes would be located in the same spatial position allowing for accurate collec tion of volumes during multiple time periods Toll p laza s etup Implementing a toll plaza into this network follows the same steps described in Example 1. The only difference being that the service time for each payment type needs to be determined based on the desired processing rate provided This is done by u tilizing the pull up equation From this equation a pull up time of 3 .5 seconds was calculated for this plaza Subtracting this value from the des ired processing rate produces approximate service time s for each payment type. In addition to determining the service times for each payment, the volume split needs to be determined. This split determines the vehicle utilization of the two different parts of the toll plaza. As mentioned in the input data 80%, 2400 vph, of the vehicles utilize the ORT lanes and 20%, 600 vph, utilize the traditional toll plaza. This information

PAGE 99

99 is input at the node where separation between the traditional toll plaza and the ORT lanes occurs. Figure A 20 shows the inputs for the network split. Output p rocessor With the toll plaza model created data can now be collected from the simulation using the output processor. For this example the output processor is going to be used to determine the average service rate for each lane and exiting volume of each lane during the fifteen minute simulation To do this open up the output processor and under the BOOTH object s BOOTH category. In addition to the MOEs for the toll plaza, MOEs also need to be selected for the ORT segment. Like the other toll plaza MOE used in Example one go to mat output option a s a CVS file. Results of the output processor can be found in Table A 4 and Table A 5 The .trf format for Example 2 can be found in Appendix B This concludes Example 2. Example 3 This example is based on a traditional toll plaza without ORT lanes to demonstrate This example is based on the same network used for Example 1. The inputs are as followed: S imulation uses two 10 minutes time periods Traffic volume of 20 00 vph during first 10 minute period 15 00 vph during second 10 minute period Assume there are 5% heavy vehicles for both time periods Heavy vehicles restricted to toll booth 4 Two lane approac h and departure Approach length of 1500 feet Departure length of 1500 feet Four lane toll plaza Payment types accepted at the plaza are ETC and Manual

PAGE 100

100 Toll booth 1 accepts ETC Toll booth 2 accepts Manual Toll booth 3 and 4 accepts ETC and Manual Toll booth 3 closes during second time period Payment distribution is 70% ETC 30% Manual Manual payment type service time is 5.5 seconds/vehicle ETC payment type service time is 1.5 seconds/vehicle Queuing offset of 5 feet Lane change sensitivity factor of 0.7 Simu lation and network setup As mentioned previously, Example 3 utilizes the same network configuration and simulation setup as Example 1. As such the setup of this simulation will not be discussed. Please refer to Example 1 for a detailed description on how t o create this network. Toll plaza setup The setup of the toll plaza for this example follows the same approach as Example 1 with the addition of the heavy vehicle input and the second time period The heavy vehicle input is found in the entry node. Adding the additional time period ca n be done one of two ways. One way is for the user to specify that there are two time periods when first creating the simulation file. The other way is by going into the network properties and adding the second time period. See Figure A 21 for the network properties input screen. With the network fully set up the next step is to incorporate the toll plaza information into the .trf file. For a simulation that uses multiple time periods the toll plaza rec ord types need to be included in each time period only when information concerning the toll plaza changes. In the case of this example, the toll plaza record types do need to be included as a toll booth is closed during the second time period.

PAGE 101

101 The final s tep is to implement the vehicle restrictions. For this simulation only the far right toll lane can accommodate heavy vehicles. To input this into CORSIM the binary coding for vehicle restrictions in RT 83 needs to restrict vehicle types that are classified as trucks. In NETSIM, vehicle types 2, 6, 7, and 8 are classified as truck class vehicles. Changing the 0 to 1 for these four vehicle types in the binary code for vehicle types ensures heavy vehicles do not utilize toll booths 2, 3, and 4. The finalized trf file for Example 3 can be found in Appendix B Output processor For this example outputs will be obtained to determine toll booth utilization by vehicle type. To accomplish this the VEHICLETYPE_LANE MOE will be utilized. The objects selected are all t he vehicle types for the four lane on link [3,4]. Similar to the toll processor can be found in Table A 6 and Table A 7 Additional Application of CORSIM Improvements The new toll plaza capability greatly increases the ability of CORSIM to simulate a wide variety of roadway networks. The new toll plaza capability also allows CORSIM to simulate a variety of other applica tions that are similar to a toll plaza. One such application that can be found for these improvements is border crossings. Like a toll plaza, border crossings utilize a multi booth system to facilitate the flow of traffic through the border crossing and in to the country. When looking at the basic characteristics of a border cros sing, the only significant difference between the two are the service times. In the case of a toll plaza, services times tend to be in the magnitude of seconds, whereas border crossi ng service times tend to be in the minutes. The difference in magnitudes for service times produces a large capacity difference between toll plaza booths and

PAGE 102

102 border crossing booths. To remedy this issue, border crossings usually provide a larger number of open booths for users. Each CORSIM toll plaza link can accommodate up to a nine lane

PAGE 103

103 Table A 1 Lane selection example toll lane desirability Booth 1 Booth 2 Booth 3 Booth 4 Booth 5 TLD 1.2 3 1.0 0 1. 0 0 1. 0 0 Closed Table A 2 Binary Code Use for Payment Acceptance Numerical Location Payment Type 1XXX ACM X1XX Manual XX1X Ticket XXX1 ETC Table A 3 Example 1 lane utilization by payment type Lane 1 Lane 2 Lane 3 Lane 4 Manual 89.8 39.2 20.5 0 ETC 0 95 95.8 158.3 Table A 4 Example 2 exiting volumes results ORT Lanes Toll P laza Expected Volume 600 150 CORSIM Volume 593.2 155.2 Table A 5 Example 2 average service time by toll booth Booth 1 Booth 2 Booth 3 Booth 4 Expected Service Time 3.4 3.4 3.4 3.4 Actual Service Time 4.1 823 3.3836 3.7677 3.5695 Table A 6 Example 3 toll booth utilization by vehicle type time period 1 1 2 5 6 7 8 Booth 1 48.4 4.8 16.5 7.3 4.1 1.3 Booth 2 65.1 0.0 24.6 0.0 0.0 0.0 Booth 3 40.4 0.0 15.0 0.0 0.0 0.0 B ooth 4 79.8 0.0 24.2 0.0 0.0 0.0 Table A 7 Example 3 toll booth utilization by vehicle type time period 2 1 2 5 6 7 8 Booth 1 45.5 4.2 14.8 5.7 2.8 1.2 Booth 2 58.9 0.0 19.2 0.0 0.0 0.0 Booth 3* 0.0 0.0 0.0 0.0 0.0 0 .0 Booth 4 76.7 0.0 24.8 0.0 0.0 0.0 Closed during time period 2

PAGE 104

104 Figure A 1 Lane change selection example

PAGE 105

105 Figure A 2 .trf format for r ecord t ype 82 Fi gure A 3 .trf format for r ecord t ype 83 Figure A 4 .trf format for r ecord t ype 84

PAGE 106

106 Figure A 5 Toll plaza that should utilize a combination of FRESIM and NETSIM l ink s to simulate ORT lanes note that there is no separation between the toll plaza and the ORT lane

PAGE 107

107 Figure A 6 Toll plaza that should utilize FRESIM link to simulate ORT lanes note separation between toll plaza and ORT lan es Figure A 7 ORT lane utilizing NETSIM link (ORT lane is top lane) Figure A 8 ORT lane utilizing FRESIM link (ORT lane is top lane)

PAGE 108

108 Figure A 9 Network p rope rties input screen for E xample 1 Figure A 10 Link input screens for Example 1

PAGE 109

109 Figure A 11 Node and ink diagram of Example 1 Figure A 12 E xample 1 approac h

PAGE 110

110 Figure A 13 Toll plaza input screen coded for E xample 1 Figure A 14 Toll plaza developed in Example 1 Figure A 15 Toll plaza approach for Example 1

PAGE 111

111 Figure A 16 Output processor configuration for Example 1 Figure A 17 Aerial of Beachline West Toll Plaza Figure A 18 Example 2 network split (bottom portion le ads to traditional plaza)

PAGE 112

112 Figure A 19 Node and l ink diagram for Example 2

PAGE 113

113 Figure A 20 Off ramp inputs for traditional toll plaza Example 2 Figure A 21 Netw ork properties input for Example 3

PAGE 114

114 APPENDIX B EXAMPLE PROBLEMS FILE FORMATS Example 1 Created by TSIS Wed Mar 09 17:41:30 2011 from TNO Version 65 12345678 1 2345678 2 2345678 3 2345678 4 2345678 5 2345678 6 2345678 7 234567 3 92011 0 1 1 0 0 10 97165909 0000 0 31600 6799963041456717 2 900 3 1 60 4 0 0 0 0 0 0 0 0 0 0 0 0 5 1 2 500 2 01 3 20 18 30 012 11 2 3 500 3 01 4 20 18 65 012 11 3 4 500 4 01 5 20 18 65 0 11 4 5 500 4 01 6 20 18 65 043 11 5 6 500 3 01 7 20 18 30 032 11 6 7 500 2 01 8002 20 18 30 0 11 8001 1 2 01 2 20 18 0 11 1 2 100 21 2 3 100 21 3 4 100 21 4 5 100 21 5 6 100 21 6 7 100 21 8001 1 100 21 1 8001 35 2 1 35 3 2 35 4 3 35 5 4 35 6 5 35 7 6 35 1 1 36 2 1 36 3 1 36 4 1 36 5 1 36 6 1 36 7 1 36 8001 12000 0 0 100 50 3 4 90 55 60 151200 5 7 82 3 4 1 0100 0000000000000000 83 3 4 2 0101 0000000000000000 83 3 4 3 0101 0000000000000000 83 3 4 4 0001 0000000000000000 83 3 4 0 30 0 70 84 0 170 8001 0 0 195 8002 3480 0 195 1 300 0 195 2 800 0 195 3 1294 0 195 4 1800 0 195 5 2300 0 195 6 2800 0 195 7 3290 0 195 1 0 0 210

PAGE 115

115 Example 2 Created by TSIS Thu Mar 10 00:52:34 2011 from TNO Version 65 12345678 1 2345678 2 2345678 3 2345678 4 2345678 5 2345678 6 2345678 7 234567 3 12011 0 1 1 0 0 120 97165909 0000 0 32100 6799963041456717 2 900 3 1 60 4 0 0 0 0 0 0 0 0 0 0 0 0 5 11 13 398 2 01 7002 20 18 65 0 11 12 11 400 3 01 13 20 18 65 0 11 7 12 400 4 01 11 20 18 65 021 11 8 7 400 4 01 12 20 18 65 0 11 4 8 404 3 01 7 20 18 65 0 11 10 4 496 2 01 8 20 18 65 012 11 7001 10 400 2 01 4 20 18 65 0 11 137002 202 1 01 20 18 65 11 4 8 8 7 1 1 14 4 8 8 7 2 1 14 4 8 8 7 3 1 14 10 4 4 8 1 1 14 10 4 4 8 2 1 14 11 13 100 21 12 11 100 21 7 12 100 21 8 7 100 21 4 8 100 21 10 4 100 21 7001 10 100 21 137002 100 21 4 10 35 7 8 35 8 4 35 10 70 01 35 11 12 35 12 7 35 13 11 35 4 1 36 7 1 36 8 1 36 10 1 36 11 1 36 12 1 36 13 1 36 8 7 40 60 60 201200 5 7 82 8 7 1 1101 0000000000000000 83 8 7 2 1101 0000000000000000 83 8 7 3 1101 0000000000000000 83 8 7 4 1101 0000000000000000 83 8 7 10 30 0 60 84 8 170 5 2 17 11000 3 93 1100 1 9 19 16 3 6 10060 3 1 19 1 5 2 13990 4 9 19 3 6 9 9980 3 1 19 6 9 15 8040 3 1 19 14 9 15 2561 1 9 19 9 158003 4940 3 91 200 1 19 27001 2091 2 1 19 7002 14 9 1501 1 1 19 8001 1 5 0 4 1 19 17 16 3 4320 3 1 19 2 17 16 4620 3 1 19

PAGE 116

116 5 2 0 0 0 11065 2500 2500 100 20 16 3 0 0 0 11065 100 20 1 5 0 0 0 11065 100 20 3 6 0 0 0 11065 100 20 6 9 0 0 0 11065 100 20 14 9 0 0 0 11065 100 20 9 15 0 0 0 11065 431500 100 20 27001 0 0 0 11065 100 20 7002 14 0 0 0 11065 100 20 8001 1 0 0 0 11065 20 17 16 0 0 0 11065 100 20 2 17 0 0 0 11065 100 20 5 2 3 0 24 5 2 4 0 24 5 2 5 0 24 5 2 6 0 24 5 2 7 0 24 5 2 8 0 24 5 2 9 0 24 5 2 1724007001 600 25 16 3 6 100 25 1 5 2 100 25 3 6 9 100 25 6 9 15 100 25 14 9 15 100 25 9 158003 100 25 7002 14 9 100 25 8 001 1 5 100 25 17 16 3 100 25 2 17 16 100 25 8001 13000 0 0 100 25 25 25 25 50 0 170 8003 7608 50 195 8001 0 50 195 4 3896 0 195 7 4700 0 195 8 4300 0 195 10 3400 0 195 11 5500 0 195 12 5100 0 195 13 5898 0 195 1 299 51 195 2 2798 54 195 3 4698 54 195 5 1698 52 195 6 5696 54 19 5 9 6500 56 195 14 6250 0 195 15 6994 54 195 7001 300 0 0 195 7002 6100 0 195 16 3692 44 195 17 3260 50 195 1 0 0 210 Example 3 Created by TSIS Sat Apr 09 22:32:55 2011 from TNO Version 65 12345678 1 2345678 2 23456 78 3 2345678 4 2345678 5 2345678 6 2345678 7 234567 3 92011 0 1 1 0 0 10 97165909 0000 0 31600 6799963041456717 2

PAGE 117

117 600 600 3 1 60 4 0 0 0 0 0 0 0 0 0 0 0 0 5 1 2 500 2 01 3 20 18 30 012 11 2 3 500 3 01 4 20 18 65 012 11 3 4 500 4 01 5 20 18 65 0 11 4 5 500 4 01 6 20 18 65 043 11 5 6 500 3 01 7 20 18 30 032 11 6 7 500 2 01 8002 20 18 30 0 11 8001 1 2 01 2 20 18 0 11 1 2 100 21 2 3 100 21 3 4 100 21 4 5 100 21 5 6 100 21 6 7 100 21 8001 1 100 21 1 8001 35 2 1 35 3 2 35 4 3 35 5 4 35 6 5 35 7 6 35 1 1 36 2 1 36 3 1 36 4 1 36 5 1 36 6 1 36 7 1 36 8001 12000 5 0 100 50 5 1 4 100 25 0 0 0 130 58 1 16 100 75 0 0 0 130 58 2 35 120 0 31 0 0 120 58 6 53 120 0 36 0 0 120 58 7 53 120 0 24 0 0 120 58 8 64 120 0 9 0 0 120 58 3 4 90 55 60 151200 5 7 82 3 4 1 0101 0000000000000000 83 3 4 2 0101 0100011100000000 83 3 4 3 0100 0100011100000000 83 3 4 4 0001 0100011100000000 83 3 4 0 30 0 70 84 0 170 8001 0 0 195 8002 3480 0 195 1 300 0 195 2 800 0 195 3 1294 0 195 4 1800 0 195 5 2300 0 195 6 2800 0 195 7 3290 0 195 0 3 210 8001 11500 5 0 100 50 3 4 90 55 60 151200 5 7 82 3 4 1 0101 0 000000000000000 83 3 4 2 0101 0100011100000000 83 3 4 3 0000 0100011100000000 83 3 4 4 0001 01000111000000 00 83 3 4 0 30 0 70 84 0 170

PAGE 118

118 1 0 0 210

PAGE 119

119 LIST OF REFERENCES 1 Highway Capacity Manual TRB, National Research Council, Washinton, D.C., 2000. Print. 2 Woo, T, and Lester Hoel. "Toll Plaza Capacity and Level of Service." T ransportation Research Record 1320. (1991): 119 127. Print. 3 Schaufler, Alberte. NCHRP Synthesis 240 Toll Plaza Design Transportation Research Board, 1996. Print. 4 Zarrillo, Marguerite, A Radwan, and Jo seph Dowd. "Toll Network Capacity Calculator." Transportation Research Record 1781. (2002): 49 55. Print. 5 Zarrillo, Marguerite. "Capacity Calculation for Two Toll Facilities: Two Experiences in ETC Implementation." 79th Transport ation Research Board Annual Meeting (2000): 1 11. Print. 6 Aycin, Murat. "Simple Methodology for Evaluating Toll Plaza Operation." Transportation Research Record 1988. (2006): 92 101. Print. 7 Al Deek, Hai tham, Ayman Mohamed, and Essam Radwan. "New Model for Evaluation of Traffic Operations at Electronic Toll Collection Plazas." Transportation Research Record 1710. (2000): 1 10. Print. 8 Klodzinski, Jack, and Haitham Al Deek. "New M ethodology for Evaluating a Toll Plaza's Level of Sevice." ITE Journal 27.2 (2002): 34 43. Print. 9 Klodzinski, Jack, and Haitham Al Deek. "New Methodology for Defining Level of Service at Toll Plaza." Journal of Transportation Eng ineering 128.2 (2002): 173 181. Print. 10 "Freeways and Highways". Quadstone Paramics Ltd. 7/8/2010 http://www.paramics online.com/freeways and highways.php 11 Nezamuddin, N, and Haitham Al Deek. "Developing Microscopic Toll Plaza and Toll Road Corridor Model with PARAMICS." Transportation Research Record 2047. (2008): 100 110. Print. 12 Al Deek, Haitham. "Analyzing Performance of ETC Plazas Using New Computer Software." Journal of Com puting in Civil Engineering 15.4 (2001): 309 319. Print. 13 Aycin, Murat, Keith Kiskel, Vassilis Papayannoulis, and Gary Davies. "Development of Methodology for Toll Plaza Delay Estimation for Use in Travel Demand Model Postproces sor." Transportation Research Record 2133. (2009): 1 10. Print.

PAGE 120

120 14 Klodzinski, Jack, and Haitham Al Deek. "Transferability of a Stochastic Toll Plaza Computer Model." Transportation Research Record 1811. (2002): 40 49. Print. 15 Klodzinski, Jack, and Haitham Al Deek. "Evaluation of Toll Plaza Performance After Addition of Express Toll Lanes at Mainline Toll Plaza." Transportation Research Record 1867. (2004): 107 115. Print.

PAGE 121

121 BIOGRAPHICAL SKETCH Brett Al l en Fuller, t he only ch ild of Chris and Cliff Fuller, grew up in Okeechobee, Florida graduating from Okeechobee High School in 2005. He began his post secondary education at the University of Miami (Florida) in the fall of 2005 graduating in the spring of 2009 with a B achelor of Science in Civil Engineering He is a lice nsed Engineering Intern in the S tate of Florida. In August 2009, he began work on his civil engineering at the University of Florida and graduated in May 20 11