Type de document

Études primaires

Année de publication

2026

Langue

Anglais

Titre de la revue

Safety Science

Résumé

Context

Mobile equipment (ME), such as loader, that runs over pedestrian workers (PWs) is still a major cause of fatal work accidents. Proximity detection devices (PDDs) are an avenue to mitigate these risks, yet there is a lack of comprehensive studies to inform their practical implementation. Aim. The aim is to provide a structured analysis of the factors contributing to ME-PW collisions and to evaluate the potential impact of integrating PDDs into the causality chain of these accidents.

Methodology

An exhaustive database was created through analysis of investigation reports on fatal ME-PW collisions in Quebec, Canada, from 2013 to 2023 (n = 34). Contributing factors were structured using fault tree analysis (FTA).

Results

ME-PW collisions account for 8 % of all available fatal accident reports. Two accident types stand out: dump trucks backing up to deliver earthwork (8/34) and hydraulic shovels used in earthwork operations (8/34). Reversing collisions were the most frequent (21/34), as were accidents occurring during the starting phase of the ME (21/34).

Discussion

In 88 % of cases, the operator was unaware of the PW’s presence just before the accident. This finding confirms the strong potential of PDD as an additional layer of risk reduction. The FTA provides a novel perspective on the potential benefits of PDDs, while also highlighting the challenges of their effective integration into real-world operations. For instance, (1) ensuring coverage of the actual danger zone according to the movement, (2) providing highly targeted warnings, and (3) accounting for subcontracting and environmental conditions that may affect PDD performance. (©Elsevier)

Mots-clés

Accident de transport, Transportation accident, Véhicule en mouvement, Vehicle in motion, Collision, Analyse des causes d'accident, Analysis of accident causes, Piéton, Pedestrian, Détecteur de proximité, Proximity detector guard

Numéro de projet IRSST

2023-0008

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