The effects of lead time of verbal collision warning messages on driving performance

Jingyan Wan, Changxu Wu, Yiqi Zhang

Research output: Contribution to conferencePaperpeer-review

Abstract

The lead time of warning messages from a collision warning systems (CWSs) is a crucial factor in determining system effectiveness in the prevention of traffic accidents. Accordingly, it is necessary to understand the effects of lead time on driving behaviors and explore the optimal lead time in various collision scenarios. The current driving simulator experiment examined the effects of controlled lead time at 16 levels (predetermined time headway from the subject vehicle to the collision location when the warning message broadcasted to a driver) and lead vehicle conditions (without vs. with lead vehicle) on driving performance in various collision scenarios. The results indicated that the controlled lead time, lead vehicle conditions, lifetime driving experience, and driving speed (instantaneous velocity when the warning message broadcasted) significantly affected driver performance. The results indicated greater effectiveness of warning messages was achieved with the controlled lead time ranging from 4s to 10s. Furthermore a trapezoidal distribution of warning effectiveness was found by the building of the statistic model using curve estimation considering lead time, lead vehicle condition, lifetime driving experience, and driving speed. Potential applications of the results in designing of collision warning systems are further discussed.

Original languageEnglish (US)
StatePublished - Jan 1 2014
Event21st World Congress on Intelligent Transport Systems: Reinventing Transportation in Our Connected World, ITSWC 2014 - Detroit, United States
Duration: Sep 7 2014Sep 11 2014

Other

Other21st World Congress on Intelligent Transport Systems: Reinventing Transportation in Our Connected World, ITSWC 2014
CountryUnited States
CityDetroit
Period9/7/149/11/14

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Mechanical Engineering
  • Automotive Engineering
  • Transportation
  • Electrical and Electronic Engineering

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