The effectiveness of auditory forward collision warning alerts

Xingwei Wu, Linda Ng Boyle, Dawn Marshall, West O'Brien

Research output: Contribution to journalArticlepeer-review

Abstract

The objective of this study is to evaluate the effects of auditory warning characteristics from a forward collision alert system on drivers’ avoidance behavior. A driving simulator study was designed and conducted with a pre-collision scenario that included a lead vehicle decelerating. This scenario is used to examine whether any casual relationship exists between the auditory alert characteristics and collision avoidance. The study included 192 participants across the U.S. The auditory characteristics, including fundamental frequency and duty cycle, were examined at three urgency levels. The data from the study was analyzed using Partial Least Squares (PLS) path modeling. The collision avoidance behavior was measured using two reaction times (throttle release, brake) and three response intensities (maximum brake pedal force, maximum lane deviation and response type). All tested warning alerts resulted in reduced collision rates, shorter reaction times, larger maximum brake pedal force, and larger maximum lane deviation when compared to the baseline condition without a warning. Participants were also more likely to simultaneously brake and steer when given an alert. The models illustrate that the auditory warning information has both a direct and indirect effect on occurrence of collisions, with the indirect effect playing a more important role on collision avoidance than the direct effect. The findings also showed that the low urgency level of duty cycle and high urgency level of fundamental frequency are not recommended for collision warning alerts.

Original languageEnglish (US)
Pages (from-to)164-178
Number of pages15
JournalTransportation Research Part F: Traffic Psychology and Behaviour
Volume59
DOIs
StatePublished - Nov 2018

Keywords

  • Auditory characteristics
  • Causal relationship
  • Collision avoidance behavior
  • Forward collision warning
  • Partial least squares path modeling

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Automotive Engineering
  • Transportation
  • Applied Psychology

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