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Applying an extended theory of planned behavior to predicting violations at automated railroad crossings.

Authors :
Palat, Blazej
Paran, Françoise
Delhomme, Patricia
Source :
Accident Analysis & Prevention. Jan2017, Vol. 98, p174-184. 11p.
Publication Year :
2017

Abstract

Based on an extended Theory of Planned Behavior (TPB, Ajzen, 1985, 1991 ), we conducted surveys in order to explain and predict violations at a railroad crossing, among pedestrians ( n = 153) and car drivers ( n = 151). Measures were made with respect to three chronologically related railroad crossing situations that varied in risk level. The situations were described in scenarios and depicted on photographs. The participants were recruited in the suburbs of Paris, at two automated railroad crossings with four half-barriers. We found that the pedestrians had stronger crossing intentions than did car drivers, especially at the more congested crossing of the two under study. For both categories of road users, intentions and the amount of intention variance explained by the extended TPB factors decreased significantly with risk level. In the most dangerous situations, risk-taking was the most unlikely and the least predictable Self-reported past frequency of crossing against safety warning devices was the main predictor of the intention to commit this violation again, especially among males, followed by the attitude and the injunctive norm in favor the violation. Moreover, car drivers were influenced in their crossing intentions by the descriptive norm. The presence of another vehicle on the tracks when the safety warning devices were activated was perceived not as facilitating, but as an additional risk factor. The discussion addresses the importance of taking into account these determinants of violations in conceiving countermeasures. Our findings could be especially useful for conceiving risk-communication campaigns. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00014575
Volume :
98
Database :
Academic Search Index
Journal :
Accident Analysis & Prevention
Publication Type :
Academic Journal
Accession number :
120276884
Full Text :
https://doi.org/10.1016/j.aap.2016.10.005