Situation-Aware Risk Assessment for Intersection Driving for Heavy Vehicles

Abstract

Navigating unregulated intersections with a heavy vehicle is a challenging task harboring significant risks for the vehicle itself and other traffic participants. In this study we introduce a dynamic, evidence-based risk assessment algorithm predicting increased general risk at upcoming intersections based on environmental cues. We qualitatively evaluated two HMI configurations—a standard dashboard versus an adaptive Head-Up Display (HUD)—with professional drivers in a driving simulator. Drivers perceived the predictive risk indicator as highly useful, preferring the HUD layout. Despite physical simulator constraints, the results strongly support the utility of predictive general risk assessment. Future work will integrate real-time driver monitoring of eyes-off-road (EOR) metrics to dynamically adjust risk indicators based on driver attentiveness.