An Enhanced Rakha-Pasumarthy-Adjerid Car-Following Model Accounting for Driver Behavior

The biggest challenge facing traffic engineering researchers is how to account for human behavior, a non-physical parameter, in transportation modeling. In fact, a major drawback of existing car-following models is that the human-in-the-loop is not modeled explicitly. This is specifically important since the output from car-following models directly impacts several other factors and measures of effectiveness (MOE), such as vehicle emissions and fuel consumption levels. This paper describes a research effort that attempts to improve an existing car-following model by explicitly considering the characteristics of the vehicle as well as human driving behavior in its mathematical expression. The proposed model is an extension to the Rakha-Pasumarthy-Adjerid (RPA) car-following model, which uses a steady-state formulation along with acceleration and collision avoidance constraints to model the longitudinal motion of vehicles. The dataset used to calibrate and validate the model is extracted from the naturalistic data of the 100-Car study that was gathered by researchers at the Virginia Tech Transportation Institute. An analysis of the proposed modified variant using the aforementioned naturalistic driving data found that the modified formulation successfully integrated the human behavior component in the RPA model and that the new formulation slightly decreases the modeling error.

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

  Transportation Research Board

  500 Fifth Street, NW
  Washington, DC  United States  20001
• Authors:
  • Fadhloun, Karim
  • Rakha, Hesham
  • Abdelkefi, Abdessattar
  • Loulizi, Amara
• Conference:
  • Transportation Research Board 96th Annual Meeting
  • Location: Washington DC, United States
  • Date: 2017-1-8 to 2017-1-12
• Date: 2017

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References; Tables;
• Pagination: 18p
• Monograph Title: TRB 96th Annual Meeting Compendium of Papers

Subject/Index Terms

• TRT Terms: Automatic data collection systems; Behavior; Car following; Driver performance; Longitudinal control; Mathematical models
• Subject Areas: Highways; Operations and Traffic Management; Safety and Human Factors;

Filing Info

• Accession Number: 01622733
• Record Type: Publication
• Report/Paper Numbers: 17-00440
• Files: TRIS, TRB, ATRI
• Created Date: Jan 19 2017 9:12AM