Arrival-time judgments on multiple-lane streets: The failure to ignore irrelevant traffic

Accid Anal Prev. 2014 Apr:65:72-84. doi: 10.1016/j.aap.2013.12.013. Epub 2014 Jan 4.

Abstract

How do road users decide whether or not they have enough time to cross a multiple-lane street with multiple approaching vehicles? Temporal judgments have been investigated for single cars approaching an intersection; however, close to nothing is known about how street crossing decisions are being made when several vehicles are simultaneously approaching in two adjacent lanes. This task is relatively common in urban environments. We report two simulator experiments in which drivers had to judge whether it would be safe to initiate street crossing in such cases. Matching traffic gaps (i.e., the temporal separation between two consecutive vehicles) were presented either with cars approaching on a single lane or with cars approaching on two adjacent lanes, either from the same side (Experiment 1) or from the opposite sides (Experiment 2). The stimuli were designed such that only the shortest gap was decision-relevant. The results showed that when the two gaps were in sight simultaneously (Experiment 1), street-crossing decisions were also influenced by the decision-irrelevant longer gap. Observers were more willing to cross the street when they had access to information about the irrelevant gap. However, when the two gaps could not be seen simultaneously but only sequentially (Experiment 2), only the shorter and relevant gap influenced the street-crossing decisions. The results are discussed within the framework of perceptual averaging processes, and practical implications for road safety are presented.

Keywords: Intersection-crossing; Multiple gaps; Perceptual averaging; Time-to-arrival.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Attention*
  • Automobile Driving / psychology*
  • Automobile Driving / statistics & numerical data*
  • Computer Simulation
  • Decision Making*
  • Environment Design*
  • Female
  • Humans
  • Judgment*
  • Male
  • Orientation
  • Probability Learning
  • Risk-Taking
  • Safety / statistics & numerical data
  • Time Perception*