How can drivers be nudged to avoid distracted driving? The effects of nudging risk type and density through a serial mediation of arousal level and perceived risk

The high frequency of traffic accidents underscores the crucial importance of warning drivers against distracted driving, particularly during the autonomous driving process. Although extant studies on distraction mitigation have delved into distraction sources and distraction detection, they have mostly neglected the effectiveness of nudging content and density, as well as the underlying mechanisms that influence driver responses. Grounded in Nudge Theory and Situated Action Theory, this study investigates how the nudging risk type and density impact driver responses to distraction prompts through a serial mediation of arousal level and perceived risk. It also examines the moderating effects of road weather conditions. Through three experiments, this study demonstrated that immediate risk exerts a stronger influence than potential risk in shaping drivers’ responses. Additionally, higher nudging density, which reflects both greater stimulus intensity and a shorter inter-stimulus interval, is associated with more favorable driver responses. Nudging risk type influences driver responses only through a sequential mediation pathway involving arousal level and perceived risk, while nudging density has both direct and indirect effects via the same mediating mechanism. Under rainy conditions, the effect of nudging risk type on arousal level is attenuated, and the effect of nudging density on driver response is likewise diminished. This study makes a theoretical contribution to the literature on information nudges in driving scenarios.