Sangam: A Confluence of Knowledge Streams

Behavioural culpability for traffic accidents

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dc.creator Dorn, Lisa
dc.creator af Wåhlberg, Anders E.
dc.date 2018-12-05T11:32:14Z
dc.date 2018-12-05T11:32:14Z
dc.date 2018-12-03
dc.date.accessioned 2022-05-25T16:40:21Z
dc.date.available 2022-05-25T16:40:21Z
dc.identifier Dorn L, af Wåhlberg AE. Behavioural culpability for traffic accidents. Transportation Research Part F: Traffic Psychology and Behaviour, Volume 60, January 2019, pp. 505-514
dc.identifier 1369-8478
dc.identifier https://doi.org/10.1016/j.trf.2018.11.004
dc.identifier http://dspace.lib.cranfield.ac.uk/handle/1826/13695
dc.identifier 22187650
dc.identifier.uri http://localhost:8080/xmlui/handle/CUHPOERS/182547
dc.description This study presents a description of the concept of behavioural culpability, a step-by-step manual for using it, and an empirical test of a suspected mis-classification of culpability. Behavioural culpability is defined as whether the driver’s actions contributed to a crash and that non-culpable crashes are not caused by any specific behaviour and can only be predicted from exposure. Drivers with non-culpable crashes are therefore a random sample of the population. However, if the criteria for culpability and/or the individual judgements are not reflective of the principle of behavioural culpability, no fault drivers will not be a random sample of the driving population. To test the predictions from the definition of randomness in a sample assumed to have sub-optimal coding, the categorization of crash involvement undertaken by a British bus company was tested for associations between at fault and no fault crashes, age and experience. As predicted from the low percentage of at fault accidents in the sample, correlations between the variables indicated that a fair percentage of at fault crashes had been coded as no fault of the bus driver, suggesting a too lenient criterion. These results show that within fleet-based companies, culpability for a crash is probably allocated for legal reasons, which means that the predictability of accident involvement taking into account individual differences is not fully utilized. The aim of behavioural culpability coding is to increase effect sizes in individual differences in safety research and to improve our capability of predicting accident involvement.
dc.language en
dc.publisher Elsevier
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Bus driver
dc.subject Accident
dc.subject Crash
dc.subject Culpability
dc.subject Fault
dc.title Behavioural culpability for traffic accidents
dc.type Article


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