Naturalistic Longitudinal and Lateral Risk-Taking Driving Behavior Modeling during Safety-Critical Events

Driving behavior in traffic has been modeled quite successfully in simulation software using predefined car-following model rules. However, most car-following models are not capable of representing naturalistic driving behavior during safety-critical events, since they were designed to adhere to safe driving conditions. Also, detailed lateral maneuvering has not been simulated in most simulation software. The proposed methodology in this paper focuses on establishing a traffic state-action mapping rule to simulate real driver actions including risky behavior that a driver would take during safety critical events instead of the predefined actions given by car following models. Traffic states are defined by the variables that are influential to driver action such as relative distance, speed or the acceleration of leading vehicle with the purpose of finding the most critical causalities of the events. State-action mapping rules are calibrated and validated using artificial neural networks.

• Record URL:
  • http://onlinepubs.trb.org/onlinepubs/conferences/2011/RSS/2/Chong,Li.pdf
• 
• Supplemental Notes:
  • Distribution, posting, or copying of this PDF is strictly prohibited without written permission of the Transportation Research Board of the National Academy of Sciences. Unless otherwise indicated, all materials in this PDF are copyrighted by the National Academy of Sciences. Copyright © National Academy of Sciences. All rights reserved
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  Transportation Research Board

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• Authors:
  • Chong, Linsen
  • Abbas, Montasir M
  • Higgs, Bryan
  • Medina, Alejandra
• Conference:
  • 3rd International Conference on Road Safety and Simulation
  • Location: Indianapolis Indiana, United States
  • Date: 2011-9-14 to 2011-9-16
• Publication Date: 2011

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References;
• Pagination: 16p
• Monograph Title: 3rd International Conference on Road Safety and Simulation

Subject/Index Terms

• TRT Terms: Behavior; Car following; Driver performance; Neural networks; Risk assessment; Traffic crashes; Traffic safety; Traffic simulation
• Uncontrolled Terms: Naturalistic studies
• Subject Areas: Highways; Safety and Human Factors; I83: Accidents and the Human Factor;

Filing Info

• Accession Number: 01504272
• Record Type: Publication
• Files: TRIS, TRB, ATRI
• Created Date: Jan 24 2014 2:29PM