Journal article
Evaluating the effects of automated monitoring on driver non-compliance at active railway level crossings
Accident Analysis & Prevention, Vol.163, pp.1-11
2021
PMID: 34710780
Abstract
Collisions between road users and trains at urban railway level crossings persist, despite active protection. The number of railway level crossings in most settings render their removal unfeasible. To effectively reduce or manage risk, alternative treatments are required. Increases in road and rail traffic invariably result in congestion issues at urban railway level crossings, which influences non-compliances by road users. Automated enforcement is one form of treatment that is being considered to reduce such non-compliances. This study conceptualised and adopted a before—after design to evaluate the effect of a conspicuous monitoring system on non-compliances by vehicular road users at an active level crossing. Baseline measurements of vehicle movements and level crossing status were recorded for two months. Conspicuous cameras and radar were subsequently installed, and a further month of data was recorded. Non-compliances with flashing lights were extracted and arranged into “must stop” and “should stop if safe to do so” categories, aligning with road rules at traffic lights. Non-compliances frequently occurred (N = 1,086) with most (94%) of the latter category and ascribed to a lack of an advanced warning before crossing closure. Analysis with Generalised Linear Models revealed that non-compliances where drivers must stop reduced by 36% (from 13.4% to 8.6%) following the introduction of a conspicuous automated monitoring system, even though no actual enforcement was performed. This study suggests that non-compliances at railway level crossings have the potential to be reduced through the introduction of automated enforcement similar to the one used at traffic lights.
Details
- Title
- Evaluating the effects of automated monitoring on driver non-compliance at active railway level crossings
- Authors
- Grégoire S. Larue (Corresponding Author) - Queensland University of TechnologyAnjum Naweed (Author) - Central Queensland University
- Publication details
- Accident Analysis & Prevention, Vol.163, pp.1-11
- Publisher
- Elsevier Ltd
- DOI
- 10.1016/j.aap.2021.106432
- ISSN
- 1879-2057
- PMID
- 34710780
- Organisation Unit
- University of the Sunshine Coast, Queensland; School of Law and Society; Road Safety Research Collaboration
- Language
- English
- Record Identifier
- 99679186402621
- Output Type
- Journal article
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- Collaboration types
- Domestic collaboration
- Web Of Science research areas
- Ergonomics
- Public, Environmental & Occupational Health
- Social Sciences, Interdisciplinary
- Transportation
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Source: InCites