ABSTRACT Unmanned aerial vehicles (UAVs) are becoming increasingly prevalent in transportation infrastructure projects due to their operational versatility and ability to minimise traffic disruptions. Consequently, federal and state agencies have shown a marked increase in interest in replacing or augmenting traditional bridge inspection methods with safer and more cost‐effective approaches, such as UAV deployment. However, the potential distraction effect of UAV operations on the travelling public, particularly compared with established methods such as under‐bridge inspection trucks (UBITs), has not yet been thoroughly studied. This study investigates and compares driver distraction caused by roadside bridge inspection operations using UAVs and UBITs. Through a series of controlled driving simulator experiments, driver distraction is quantified by the data collected from synchronised eye‐tracking and electroencephalography sensors worn by experiment participants. The results reveal distinct distraction profiles for the two bridge inspection methods. UBIT operations consistently induced greater visual and cognitive distraction across traffic conditions, with drivers directing frequent, prolonged glances toward the prominent equipment. In contrast, UAV‐related distraction was context‐dependent and primarily manifested as increased visual demand in congested, low‐speed traffic. Compared with baseline methods such as eye‐tracking alone and other mainstream distraction assessment techniques, the proposed multimodal framework provides greater sensitivity by detecting subtle cognitive effects alongside observable visual behaviour. These findings demonstrate that UAVs generally impose lower and more situational distractions than traditional UBITs and provide evidence‐based support for transportation agencies seeking to prioritise UAV deployment for routine roadway inspections while maintaining roadway safety.
Kusha et al. (Thu,) studied this question.
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