Traffic Flow Models Based on Queuing Theory for Analysis and Performance Evaluation

Queueing models provide a compelling framework to evaluate performance of traffic systems at macroscopic scale, e.g., in terms of flow, density, and travel times. However, the service paradigms typically used in existing frameworks do not have sufficient resolution to model and differentiate between emerging automation technologies at the microscopic scale. Such inadequacies can translate into erroneous performance estimates at the macro scale. On the other hand, there have been sustained and even renewed efforts on modeling vehicle level dynamics under (automated) car-following and lane-changing protocols, and their impact on traffic flow. The analytical studies along these lines, e.g., platooning and string stability, are typically restricted to closed systems, i.e., with a fixed number of vehicles, and primarily in spatially unbounded settings. While such setups are a good starting point, realistically one needs to account for externalities, in the form of arrival and departures and spatial constraints, attributed to the rest of the traffic system. In this project, we propose to develop novel spatial queues for traffic systems, whose service paradigm is modeled explicitly on the basis of microscopic inter-vehicle interactions (car-following and lane-changing) including communication/reaction delay. The setup will be flexible to include heterogeneity in inter-vehicle interactions, e.g., mixed-autonomy, and to include varying levels of connectivity. Rigorous queueing-theoretic analysis for identifying the region of stability and waiting time will be performed, to provide a characterization of capacity and average travel times, respectively, in terms of physical dimensions of the traffic infrastructure, spatio-temporal travel demand profile, and automation and control technologies. Case studies using standard datasets, such as PEMS and NGSIM, as well as using microscopic simulators such as PTV VISSIM, will be used to demonstrate the theoretical results.

Language

• English

Project

• Status: Active
• Funding: $99,998.00
• Sponsor Organizations:

  Department of Transportation

  1200 New Jersey Avenue, SE
  Washington, DC  United States  20590
• Managing Organizations:

  METRANS Transportation Center

  University of Southern California
  Los Angeles, CA  United States  90089-0626
• Project Managers:

  Brinkerhoff, Cort

• Performing Organizations:

  University of Southern California, Los Angeles

  University Park Campus
  Los Angeles, CA  United States  90089
• Principal Investigators:

  Savla, Ketan

• Start Date: 20200516
• Expected Completion Date: 20210515
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers

Subject/Index Terms

• TRT Terms: Autonomous vehicle guidance; Autonomous vehicles; Traffic signal control systems
• Subject Areas: Data and Information Technology; Passenger Transportation; Research;

Filing Info

• Accession Number: 01741800
• Record Type: Research project
• Source Agency: METRANS Transportation Center
• Files: RiP
• Created Date: Jun 2 2020 2:31PM