Consequence-Aware Takeovers: Enhancing Safety in Autonomous Driving Transitions

Awareness of behavioral consequences significantly influences focus, priorities, and emotions. This study investigates the impact of informing drivers about potential takeover consequences on human-machine collaboration in conditional autonomous driving. We recruited 32 licensed drivers and randomly assigned them to groups with and without informed consequences. Each group completed 8 distinct takeover tasks, each with varying consequences of not taking over. We assessed takeover performance, subjective evaluations (situational awareness, workload), and physiological stress responses (electrocardiogram, electromyogram) to provide a comprehensive evaluation of takeover safety. Our findings indicate that drivers informed of the consequences demonstrated superior takeover performance, evidenced by increased time-to-collision, reduced maximum lateral acceleration, and decreased trajectory deviation. Additionally, disclosing consequences increased drivers' perceived attentional demands, elevating workload while maintaining stable stress levels during takeover. Future research should explore how to balance workload with driving performance when informing drivers of the consequences of not taking over.