A Markov Model for Headway/Spacing Distribution of Road Traffic

In this paper, we link two research directions of road traffic-the mesoscopic headway distribution model and the microscopic vehicle interaction model-together to account for the empirical headway/spacing distributions. A unified car-following model is proposed to simulate different driving scenarios, including traffic on highways and at intersections. Unlike our previous approaches, the parameters of this model are directly estimated from the Next Generation Simulation (NGSIM) Trajectory Data. In this model, empirical headway/spacing distributions are viewed as the outcomes of stochastic car-following behaviors and the reflections of the unconscious and inaccurate perceptions of space and/or time intervals that people may have. This explanation can be viewed as a natural extension of the well-known psychological car-following model (the action point model). Furthermore, the fast simulation speed of this model will benefit transportation planning and surrogate testing of traffic signals.

• Record URL:
  https://doi.org/10.1109/TITS.2010.2050141
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/41297384
• Supplemental Notes:
  • Abstract reprinted with permission of IEEE.
• Authors:
  • Chen, Xiqun (Michael)
  • Li, Li
  • 0000-0002-7580-3559
  • Zhang, Yi
• Publication Date: 2010

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: pp 773-785
• Serial:
  • IEEE Transactions on Intelligent Transportation Systems
  • Volume: 11
  • Issue Number: 4
  • Publisher: Institute of Electrical and Electronics Engineers (IEEE)
  • ISSN: 1524-9050
  • Serial URL: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6979

Subject/Index Terms

• TRT Terms: Headways; Markov processes; Mesoscopic traffic flow; Traffic models; Traffic simulation; Transportation planning
• Subject Areas: Data and Information Technology; Highways; I70: Traffic and Transport;

Filing Info

• Accession Number: 01333646
• Record Type: Publication
• Source Agency: UC Berkeley Transportation Library
• Files: TLIB
• Created Date: Mar 21 2011 2:15PM