A novel driving assessment combining hazard perception, hazard prediction and theory questions

Crundall, D. ORCID: 0000-0002-6030-3631, Van Loon, E. ORCID: 0000-0002-6986-2923, Baguley, T. ORCID: 0000-0002-0477-2492 and Kroll, V. ORCID: 0000-0002-1249-9991, 2021. A novel driving assessment combining hazard perception, hazard prediction and theory questions. Accident Analysis and Prevention, 149: 105847. ISSN 0001-4575

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Abstract

A new hazard test was created using high-fidelity computer animation containing ten hazards. Sixty learner drivers and sixty experienced drivers sat either a hazard-perception version of this test (requiring timed responses to materialized hazards) or a hazard-prediction variant of the test (where the screen is occluded as the hazard begins to appear and drivers are asked ‘What happens next?’). Recent studies have demonstrated that the prediction test format outperforms the hazard perception format using naturalistic video, but there has not yet been a study replicating this effect with computer-animated materials similar to the quality of those used in the official UK hazard perception test. The new test also included eleven theory questions designed to probe drivers’ knowledge of the rules of the road. The results demonstrated that both test variants differentiated between driver groups with considerable effect sizes. Theory-question scores were comparable across learner and experienced driver groups, reflecting learners’ preparation for the test and possible issues with memory decay and overwriting in the experienced group. As an interesting aside, driving-related video game play negatively correlated with hazard perception performance, but not with hazard prediction scores. Some individual hazards better suited the prediction or perception test format, raising the possibility of a future hybrid test that combines the two approaches.

Item Type: Journal article
Publication Title: Accident Analysis and Prevention
Creators: Crundall, D., Van Loon, E., Baguley, T. and Kroll, V.
Publisher: Elsevier
Date: January 2021
Volume: 149
ISSN: 0001-4575
Identifiers:
NumberType
10.1016/j.aap.2020.105847DOI
1377203Other
Divisions: Schools > School of Social Sciences
Record created by: Linda Sullivan
Date Added: 14 Oct 2020 15:27
Last Modified: 23 Nov 2020 15:16
URI: http://irep.ntu.ac.uk/id/eprint/41316

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