Jun 6, 2016 - like to thank the NCST and CEC for their support of university-based research ..... sensors measure vehicl
Traffic Flow Models and Impact of Combined Lane Change and Speed Limit Control on Environment in Case of High Truck Traffic Volumes
June 2016
A Research Report from the National Center for Sustainable Transportation Petros Ioannou, University of Southern California Yihang Zhang, University of Southern California Yanbo Zhao, University of Southern California
About the National Center for Sustainable Transportation The National Center for Sustainable Transportation is a consortium of leading universities committed to advancing an environmentally sustainable transportation system through cuttingedge research, direct policy engagement, and education of our future leaders. Consortium members include: University of California, Davis; University of California, Riverside; University of Southern California; California State University, Long Beach; Georgia Institute of Technology; and University of Vermont. More information can be found at: ncst.ucdavis.edu.
Disclaimer
This report was prepared as the result of work sponsored by the California Energy Commission. It does not necessarily represent the views of the Energy Commission, its employees or the State of California. The Energy Commission, the State of California, its employees, contractors and subcontractors make no warrant, express or implied, and assume no legal liability for the information in this report; nor does any party represent that the uses of this information will not infringe upon privately owned rights. This report has not been approved or disapproved by the California Energy Commission nor has the California Energy Commission passed upon the accuracy or adequacy of the information in this report. The contents of this report reflect the views of the authors, who are responsible for the facts and the accuracy of the information presented herein. This document is disseminated under the sponsorship of the United States Department of Transportation’s University Transportation Centers program, in the interest of information exchange. The U.S. Government assumes no liability for the contents or use thereof.
Acknowledgments This study was funded by a grant from the California Energy Commission. The authors would like to thank the NCST and CEC for their support of university-based research in transportation, and especially for the funding provided in support of this project. The authors would like to acknowledge interactions with the research group of Professor Matthew Barth of University of California, Riverside on traffic flow modeling and environmental models.
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Traffic Flow Models and Impact of Combined Lane Change and Speed Limit Control on Environment in Case of High Truck Traffic Volumes
A National Center for Sustainable Transportation Research Report June 2016
Petros Ioannou, University of Southern California Yihang Zhang, University of Southern California Yanbo Zhao, University of Southern California
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TABLE OF CONTENTS LIST OF FIGURES ............................................................................................................................. v LIST OF TABLES .............................................................................................................................. vi ABSTRACT ....................................................................................................................................... 1 CHAPTER 1: Microscopic Traffic Network Model ........................................................................... 2 CHAPTER 2: Impact of Combined Lane Change Speed Limit Control on Environment in Case of High Truck Traffic Volumes ............................................................................................................. 5 Introduction ................................................................................................................................ 5 Combined LC & VSL Controller ................................................................................................... 7 Description of LC System and VSL System .............................................................................. 7 Design of LC Control Strategy ................................................................................................. 9 Design of VSL Control Law .................................................................................................... 10 Combination of VSL Control and LC Control ......................................................................... 11 Evaluation ................................................................................................................................. 12 Simulation Network .............................................................................................................. 12 Traffic Demand and Composition ......................................................................................... 13 Monte Carlo Simulation and Setup of Incident Scenarios .................................................... 14 Performance Measurements ................................................................................................ 15 Controller Parameters .......................................................................................................... 16 Simulation Results ................................................................................................................ 16 Conclusion ................................................................................................................................ 20 GLOSSARY ..................................................................................................................................... 22 REFERENCES ................................................................................................................................. 23 NOMENCLATURE .......................................................................................................................... 25 APPENDIX A: Definitions ............................................................................................................... 26 iv
LIST OF FIGURES Figure 1: Selected Freeway Network Area ..................................................................................... 2 Figure 2: Traffic Simulator of Selected Freeway Network .............................................................. 3 Figure 3: Selected Arterial Road Network ...................................................................................... 4 Figure 4: Traffic Simulator of Selected Arterial Road Network ...................................................... 4 Figure 5: Highway Bottleneck ......................................................................................................... 8 Figure 6: Configuration of LC & VSL Controller ............................................................................... 8 Figure 7: 𝝃 under Different Traffic Conditions .............................................................................. 10 Figure 8: System Block Diagram ................................................................................................... 12 Figure 9: Simulation Network ....................................................................................................... 13 Figure 10: Flow Rate in Discharching Section ............................................................................... 17 Figure 11: Density in Discharging Section ..................................................................................... 17
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LIST OF TABLES Table 1: Vehicle Types .................................................................................................................. 14 Table 2: Simulation Scenarios ....................................................................................................... 15 Table 3: Performance of Cars in Scenario 1 .................................................................................. 18 Table 4: Performance of Trucks in Scenario 1 .............................................................................. 18 Table 5: Performance of Cars in Scenario 2 .................................................................................. 18 Table 6: Performance of Trucks in Scenario 2 .............................................................................. 19 Table 7: Performance of Cars in Scenario 3 .................................................................................. 19 Table 8: Performance of Trucks in Scenario 3 .............................................................................. 19
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Traffic Flow Models and Impact of Combined Lane Change and Speed Limit Control on Environment in Case of High Truck Traffic Volumes ABSTRACT This report presents the work performed in collaboration with University of California, Riverside (UCR) as part of a project to University of California, Davis funded by the California Energy Commission (CEC). The aim of the project is to research intelligent traffic control strategies, which will have positive impact on the environment by reducing fuel consumption and pollution levels in areas where the truck volume is relatively high, using as an example for demonstration a network adjacent to the twin ports of Los Angeles and Long Beach. The work is divided into two parts. The first part involves the development of a microscopic traffic simulation network in a selected area around the Ports of Long Beach/Los Angeles in collaboration with UCR to be used for simulation studies of different Intelligent Transportation Technologies for traffic flow control. The second part deals with the evaluation of the impact of combined variable speed limit (VSL) and lane change control on the environment during highway incidents where the volume of trucks is relatively high. We use the simulation model developed in the first part to carry out microscopic Monte-Carlo traffic flow simulations of traffic in order to evaluate the benefits of combined VSL and lane change control during incidents on I-710 that involve closure of lanes and capacity drops. We demonstrated that this combined control strategy is able to generate consistent improvements with respect to travel time, safety, and environmental impact under different traffic conditions and incident scenarios.
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CHAPTER 1: Microscopic Traffic Network Model Under this effort we, developed a microscopic traffic simulation model using VISSIM software to be used for evaluation of different Intelligent Transportation System (ITS) technologies and traffic flow control techniques at the University of Southern California (USC) and University of California, Riverside (UCR). The simulation model involves a traffic network that includes highways and arterial streets adjacent to the Port of Long Beach/Los Angeles. An arterial street is a high-capacity urban road that delivers traffic from smaller roads to freeways. In order to improve the speed of computations, the simulation model allows the user to split it into parts. For example, for highway traffic flow control the simulator models the highway traffic that interacts with some of the main arterial streets which feed into the respective highway, without exercising the full network. For traffic flow control strategies for arterial streets, the simulator focuses on traffic on arterial streets and treats the highway traffic as a source and sink of traffic interacting with the arterial network. The overall simulation model covers I-110, I-710, and SR-47 freeways, and arterial streets near the port as shown in Figure 1. The simulation model allows the implementation of traffic flow control algorithms in MATLAB/C++ software integrated with the simulation environment via a Component Object Model (COM) interface. The corresponding VISSIM diagram of the simulation model that focuses on highway traffic flow is shown in Figure 2. Figure 1: Selected Freeway Network Area
* When the source of a figure, table, or photo is not otherwise credited, it is the work of the authors of the report.
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Figure 2: Traffic Simulator of Selected Freeway Network
The arterial road network adjacent to the Port of Long Beach is circled by Pacific Coast Highway, North Wilmington Blvd., West Anaheim St., and North Avalon Blvd., and consists of more than 100 intersections in total—15 of which have traffic signals as shown in Figure 3. The 15 intersections are controlled by 15 signal controllers, which can be designed using different approaches. The corresponding microscopic simulator of the selected road network in VISSIM is shown in Figure 4. The designed microscopic traffic simulation network model is used to evaluate a combined variable speed limit and lane change control strategy under USC’s part of the project. UCR considered the simulation model for traffic light control evaluations.
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speed limits, are deployed at the beginning of Section 1 through Section N-M. It is assumed that sensors measure vehicle density at sections 1 to N and send the information to the VSL controller. The central processing unit receives the density signal in real-time and computes the desired VSL control command of each section for display.
Design of LC Control Strategy In this study, the design of the LC controller includes decisions on the pattern of LC recommendations and the length of LC controlled segments according to bottleneck formation. Lane Change Recommendation Patterns Assignment of proper lane change recommendation type 𝑅! in lane i should help upstream vehicles to leave the closed lane and evenly distribute traffic flow to open lanes. Therefore, the LC control pattern is a function of bottleneck formation. Suppose a general highway segment has m lanes, with Lane 1 (Lane m) being the right (or left) most lane. We select the LC recommendation type for each lane using the following rules: 1. For i = 1, 2, …, m, if Lane i is open, 𝑅! ="Straight Ahead". 2. For i = 1 (i = m), if Lane i is closed, 𝑅! ="Change to Left (Right)". 3. For 1
