Enhancing and Calibrating Rakha-Pasumarthy-Adjerid Car-Following Model Using Naturalistic Driving Data

The research presented in this paper analyzes the simplified behavioral vehicle longitudinal motion model, currently implemented in the INTEGRATION software, known as the Rakha-Pasumarthy-Adjerid (RPA) model. The model utilizes a steady-state formulation along with two constraints, namely: acceleration and collision avoidance. An analysis of the model using the naturalistic driving data identified a deficiency in the model formulation, in that it predicts more conservative driving behavior compared to naturalistic driving. Much of the error in simulated car-following behavior occurs when a car-following event is initiated at a spacing that is often much shorter than is desired. The observed behavior is that, rather than the following vehicle decelerating aggressively, the following vehicle coasts until the desired headway/spacing is achieved. Consequently, the model is enhanced to reflect this empirically observed behavior. Finally, a quantitative and qualitative evaluation of the original and proposed model formulations demonstrates that the proposed modification significantly decreases the modeling error and produces car-following behavior that is consistent with empirically observed driver behavior.

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• Supplemental Notes:
  • This paper was sponsored by TRB committee AHB45 Traffic Flow Theory and Characteristics.
• Corporate Authors:

  Transportation Research Board

  500 Fifth Street, NW
  Washington, DC  United States  20001
• Authors:
  • Sangster, John
  • Rakha, Hesham
• Conference:
  • Transportation Research Board 92nd Annual Meeting
  • Location: Washington DC, United States
  • Date: 2013-1-13 to 2013-1-17
• Date: 2013

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References; Tables;
• Pagination: 20p
• Monograph Title: TRB 92nd Annual Meeting Compendium of Papers

Subject/Index Terms

• TRT Terms: Automatic data collection systems; Car following; Deceleration; Empirical methods; Errors; Microsimulation
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; I70: Traffic and Transport;

Filing Info

• Accession Number: 01476620
• Record Type: Publication
• Report/Paper Numbers: 13-1518
• Files: PRP, TRIS, TRB, ATRI
• Created Date: Mar 22 2013 2:55PM