Pedestrian detection with camera-monitor systems on mobile machinery under divided attention: A dynamic multitask approach
Shuaixin Qi, Peter Nickel, Marino Menozzi, Carlo Menon · Results in Engineering · 2026
Collisions between mobile machines and pedestrian workers remain a safety concern despite the widespread use of camera-monitor systems (CMS) as standard mitigation measures. Prior research has evaluated CMS in single-task settings, revealing shortcomings in existing design requirements. However, this limits generalizability to field realities, where operators divide attention across multiple information sources. This work addresses the gap between current CMS design requirements and the multitask, high-workload conditions typical of mobile-machine use. This paper presents a simulator study in which participants reversed a mobile excavator while detecting pedestrians emerging in a rear-view CMS feed. Two factors were manipulated: the presence of a concurrent task, designed to reflect operationally plausible attentional demands, and on-screen target size, a design proxy aligned with current CMS standards. Hazard detection performance was the primary outcome and was complemented by perceived workload, eye-movement measures, and pupillometry. Results confirmed that the multitask paradigm increased workload and reduced hazard detection performance, while increasing displayed target size alone was insufficient to fully compensate for these deficits. These findings indicate that CMS design requirements derived from low workload or single-task conditions may not be adequate for actual mobile-machine operation. The study provides evidence-based implications for evaluating and refining CMS display requirements for mobile machinery under realistic multitask operating conditions.