Abstract

In addition to regulatory obligations (e.g., traffic management plan, flagger), the risk of collision between a mobile machine and a pedestrian worker can be reduced by adding a proximity sensor. There have been many technological advances and products (e.g., camera with artificial intelligence–based image processing). However, feedback from workers is rare, particularly on construction sites. Moreover, implementing such a solution calls for expertise in areas such as machine safety (e.g., operation of mobile machinery, risk analysis, reliability of safety-related control systems, design, alert management, etc.); work activity analysis (e.g., work context and organization, risk situation determinants, decision-making, resistance to change, etc.); or detection and instrumentation methods (e.g., operating limits, detection zone, etc.).

Thus, this project aims to determine the issues and avenues for action related to the implementation and use of emerging proximity sensors to manage the risk of collision between mobile machinery and pedestrian workers in the construction industry. It attempts to fill the knowledge gap concerning the adoption criteria and effectiveness of such devices in real-world conditions on construction sites. Based on accident analysis and preliminary observations, the top-priority machines are front-end loaders, hydraulic shovels, reach trucks with retractable masts, and dump trucks.

The results will help prevention workers in the construction industry with their initiatives to improve worker safety on jobsites. In concrete terms, the results will cover problems such as choosing technology, deciding on the detection zone, alert methods following detection, and acceptability factors. The results could be useful in other industries or in regulatory deliberations concerning the use of such devices.