HUMAN PERFORMANCE MODELS AND REAR-END COLLISION AVOIDANCE ALGORITHMS

In this paper, a simple deterministic model of driver performance was used to examine kinematics- and perceptual-based rear-end collision avoidance algorithms over a range of collision situations, algorithm parameters, and assumptions regarding driver performance. Results show that the assumptions concerning driver reaction times have important consequences for algorithm performance, with underestimates dramatically undermining the safety benefit of the warning. Further, when drivers sometimes rely on the warning algorithms, larger headways can result in more severe collisions. This reflects the nonlinear interaction among the collision situation, the algorithm, and driver response that should not be attributed to the complexities of driver behavior but to the kinematics of the situation. Comparisons made with experimental data show that a simple human performance model can capture important elements of system performance and complement expensive human-in-the-loop experiments.

• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/1329271
• Corporate Authors:

  Human Factors and Ergonomics Society

  P.O. Box 1369
  Santa Monica, CA  United States  90406-1369
• Authors:
  • Brown, T L
  • Lee, J D
  • MCGEHEE, D V
• Publication Date: 2001

Language

• English

Media Info

• Features: Figures; References; Tables;
• Pagination: p. 462-482
• Serial:
  • Human Factors
  • Volume: 43
  • Issue Number: 3
  • Publisher: Sage Publications, Incorporated
  • ISSN: 0018-7208
  • EISSN: 1547-8181
  • Serial URL: http://hfs.sagepub.com/

Subject/Index Terms

• TRT Terms: Algorithms; Automobile driving; Crash avoidance systems; Highway safety; Highway transportation; Human factors; Human factors in crashes; Perception; Rear end crashes
• Uncontrolled Terms: Performance models
• Subject Areas: Highways; Safety and Human Factors; I83: Accidents and the Human Factor;

Filing Info

• Accession Number: 00921033
• Record Type: Publication
• Files: TRIS, ATRI
• Created Date: Mar 18 2002 12:00AM