Integrated Optimization of Vehicle Speed Control and Traffic Signal Timing: System Development and Testing

The research develops an integrated optimal control system to improve the transportation system efficiency and fuel economy on arterial roads by simultaneously optimizing vehicle speeds and traffic signal timings. The proposed approach entails designing two integrated control systems for connected automated vehicles (CAVs) and connected vehicles (CVs), which will be tested in a microscopic traffic simulation software and a driving simulator, respectively. Given that the existing methods are generally complicated, involving high computational cost, the team will start by developing a simple dual-optimization approach and use heuristic algorithms to locate an approximate optimum solution ensuring expedited computations. Meanwhile, the proposed approach will be developed to ensure it can be easily extended from internal combustion vehicles (ICEVs) to other vehicle types such as hybrid electric vehicles (HEVs) or battery electric vehicles (BEVs). Thereafter, the CAV and traffic signal control system will be implemented in a microscopic traffic simulation software so that the system is evaluated in mixed traffic (CAVs and non-CAVs). A simulated traffic network composed of multiple signalized intersections will be used to quantify the system-wide impacts of the proposed CAV/traffic signal control system on traffic mobility, energy consumption and emission levels for various traffic demand and market penetration levels. Lastly, the team will consider the impacts of human errors and perception reaction times (PRTs) when implementing the CV control system in a driving simulator at MSU. The simulator test will be conducted by participants to compare the proposed dual-optimization CV control system with two other scenarios -- adaptive traffic signal control and an eco-driving system previously developed to optimize vehicle trajectories. It is anticipated that the proposed systems will improve the mobility of arterial traffic by reducing delays, energy consumption and vehicle emissions, which are typically higher in low income areas.

• Record URL:
  https://www.morgan.edu/school_of_engineering/research_centers/urban_mobility_and_equity_center/research/new_research/traffic_signal_timing.html

Language

• English

Project

• Status: Completed
• Funding: $180385
• Contract Numbers:

  69A43551747123

• Sponsor Organizations:

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Managing Organizations:

  Urban Mobility & Equity Center

  Morgan State University
  Baltimore, MD  United States  21251
• Performing Organizations:

  Virginia Polytechnic Institute and State University, Blacksburg

  Virginia Tech Transportation Institute
  3500 Transportation Research Plaza
  Blacksburg, VA  United States  24061

  Morgan State University

  1700 E. Coldspring Lane
  Baltimore, Maryland  United States  21251
• Principal Investigators:

  Chen, Hao

  Rakha, Hesham

  Jeihani, Mansoureh

• Start Date: 20210101
• Expected Completion Date: 20220630
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers Program

Subject/Index Terms

• TRT Terms: Algorithms; Autonomous vehicles; Connected vehicles; Driving simulators; Energy consumption; Optimization; Pollutants; Reaction time; Speed control; Traffic delays; Traffic signal timing; Traffic simulation; Vehicle mix
• Subject Areas: Highways; Operations and Traffic Management; Vehicles and Equipment;

Filing Info

• Accession Number: 01744596
• Record Type: Research project
• Source Agency: Urban Mobility & Equity Center
• Contract Numbers: 69A43551747123
• Files: UTC, RIP
• Created Date: Jul 1 2020 9:30AM