Modeling the Dynamics of Driver's Dilemma Zone Perception Using Machine Learning Methods for Safer Intersection Control

The "dilemma zone" (DZ) is defined as the area where drivers approaching a signalized intersection must decide to either proceed or stop at the onset of the yellow indication. Drivers that might perceive themselves to be too close to an intersection for a safe stop, and too far to proceed without violating traffic regulations, are said to be caught in DZ. Despite the vast body of related literature, there is a critical gap in research related to the "dynamic nature of drivers' decision" in dilemma zones. In order to identify and capture all significant factors beyond existing research, a driver survey was administered in the three states of Virginia, Pennsylvania, and Maryland. State-of-the-art techniques in human psychology, experimental design, and statistical analysis were used to design the survey and interpret the results. A driving simulator study was conducted to investigate the dynamic nature of driver perception of the dilemma zone and to assess significant factors affecting a driver's decision at the onset of yellow. In addition, the use of machine learning methods to capture the effect of a driver's learning/dynamic perception of DZ was investigated. Findings from this research suggest that drivers do learn from their experience and also that agent-based models can be used for modeling driver behavior in the dilemma zone more accurately than models that currently exist in the literature. The research team therefore recommends that agent-based modeling and simulation techniques should be used for assessing the impacts of dilemma zone mitigation strategies.

• Record URL:
  http://www.mautc.psu.edu/docs/MAUTC-2012-04.pdf
• 
• Record URL:
  https://rosap.ntl.bts.gov/view/dot/27315
• Supplemental Notes:
  • This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program.
• Corporate Authors:

  Virginia Polytechnic Institute and State University, Blacksburg

  Blacksburg, VA  United States  24061

  Pennsylvania State University, University Park

  University Park, PA  United States  16802-4710

  Morgan State University

  Baltimore, MD  United States  21251

  Mid-Atlantic Universities Transportation Center

  Pennsylvania State University
  201 Transportation Research Building
  University Park, PA  United States  16802-4710

  Research and Innovative Technology Administration

  1200 New Jersey Avenue, SE
  Washington, DC  United States  20590
• Authors:
  • Abbas, Montasir
  • Machiani, Sahar Ghanipoor
  • 0000-0002-7314-2689
  • Garvey, Philip
  • Farkas, Andrew
  • Lord-Attivor, Rene
• Publication Date: 2014-4-1

Language

• English

Media Info

• Media Type: Digital/other
• Edition: Final Report
• Features: Appendices; Figures; Photos; References; Tables;
• Pagination: 89p

Subject/Index Terms

• TRT Terms: Decision making; Dilemma zone; Drivers; Driving simulators; Learning; Perception; Surveys
• Geographic Terms: Maryland; Pennsylvania; Virginia
• Subject Areas: Highways; Safety and Human Factors; I83: Accidents and the Human Factor;

Filing Info

• Accession Number: 01526445
• Record Type: Publication
• Report/Paper Numbers: MAUTC-2012-04, LTI 2014-12
• Contract Numbers: DTRT12-G-UTC03
• Files: UTC, NTL, TRIS, RITA, ATRI, USDOT
• Created Date: May 28 2014 3:26PM