Format

Send to

Choose Destination
See comment in PubMed Commons below
Accid Anal Prev. 1998 Sep;30(5):657-66.

Attention and expectation problems in bicycle-car collisions: an in-depth study.

Author information

1
Department of Psychology, University of Helsinki, Finland. mikko.rasanen@helsinki.fi

Abstract

One hundred and eighty-eight bicycle-car accidents in four cities were studied by multidisciplinary in-depth analysis. The sample was representative of the national accident statistics. All the accidents were analyzed in detail to reconstruct the actual movements of those involved and to assess detection of the other party. In 37% of collisions, neither driver nor cyclist realized the danger or had time to yield. In the remaining collisions, the driver (27%), the cyclist (24%) or both (12%) did something to avert the accident. Two common mechanisms underlying the accidents were identified. First, allocation of attention such that others were not detected, and second, unjustified expectations about the behavior of others. These mechanisms were found to be closely related to the system of two-way cycle tracks and to the fact that the general priority rule is applied to the crossings of a cycle track and a roadway. The most frequent accident type among collisions between cyclists and cars at bicycle crossings was a driver turning right and a bicycle coming from the driver's right along a cycle track. The result confirmed an earlier finding (Accident Analysis and Prevention 28, 147-153, 1996) that drivers turning right hit cyclists because they looked left for cars during the critical phase. Only 11% of drivers noticed the cyclist before impact. Cyclists' behavior was in marked contrast to that of drivers. In these cases, 68% of cyclists noticed the driver before the accident, and 92% of those who noticed believed the driver would give way as required by law. Cyclists with a driving license and those who cycled daily through the accident site were involved in different accident types to other cyclists.

PMID:
9678219
[Indexed for MEDLINE]
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for Elsevier Science
    Loading ...
    Support Center