Mechanisms underlying cognitive conspicuity in the detection of cyclists by car drivers

Accid Anal Prev. 2017 Jul:104:88-95. doi: 10.1016/j.aap.2017.04.006. Epub 2017 May 7.

Abstract

Objective: The aim of this study was to evaluate the visibility of cyclists for motorists in a simulated car driving task.

Background: In several cases involving collisions between cars and cyclists, car drivers failed to detect the latter in time to avoid collision because of their low conspicuity.

Method: 2 groups of motorists (29.2 years old), including 12 cyclist-motorists and 13 non-cyclist-motorists, performed a vulnerable road user detection task in a car-driving simulator. They had to detect cyclists and pedestrians in an urban setting and evaluate the realism of the cyclists, the traffic, the city, the infrastructure, the car driven and the situations. Cyclists appeared in critical situations derived from previous accounts given by injured cyclists and from cyclists' observations in real-life situations. Cyclist's levels of visibility for car drivers were either high or low in these situations according to the cyclists.

Results: Realism scores were similar and high in both groups. Cyclist-motorists had fewer collisions with cyclists and detected cyclists at a greater distance in all situations, irrespective of cyclist visibility. Several mechanisms underlying the cognitive conspicuity of cyclists for car drivers were considered.

Conclusion: The attentional selection of a cyclist in the road environment during car driving depends on top-down processing.

Application: We consider the practical implications of these results for the safety of vulnerable road users and future directions of research.

Keywords: Attention; Car driving simulator; Conspicuity; Cyclist; Pedestrian; Visibility distance.

MeSH terms

  • Accidents, Traffic / prevention & control
  • Accidents, Traffic / statistics & numerical data*
  • Adult
  • Attention*
  • Automobile Driving / psychology*
  • Automobile Driving / statistics & numerical data
  • Awareness*
  • Bicycling / injuries
  • Bicycling / statistics & numerical data*
  • Computer Simulation
  • Environment Design
  • Female
  • Humans
  • Male
  • Motorcycles / statistics & numerical data*
  • Safety
  • Visual Acuity