Multimodal Analysis of Hazard Perception Learning in Novice Drivers with Autism Using a Simulation-Based Training Environment

Simulation-based driver training has shown promise for improving hazard perception in novice drivers; however, how learners with autism adapt behaviorally, visually, and physiologically during such training remains poorly understood. This study examined the effects of a game-based, hazard-focused driving simulation on hazard detection accuracy, gaze behavior, and heart rate in novice drivers with autism using a single-case, multi-phase design. Five participants completed repeated trials across baseline, treatment, and withdrawal phases while behavioral performance, eye movements, and physiological response were recorded. Across outcome domains, participants demonstrated highly individualized learning trajectories with substantial variability in both the direction and magnitude of change. Improvements in hazard detection accuracy were not consistently accompanied by changes in gaze organization or physiological response. While one participant exhibited a canonical pattern of coordinated improvement across behavioral, visual, and physiological measures, others showed dissociation between modalities, including reduced physiological arousal without performance gains or modest accuracy improvements despite sustained physiological engagement. Exploratory peri-hazard analyses further revealed participant-specific heart rate responses aligned to hazard detection, with no uniform temporal signature associated with learning. These findings suggest that hazard perception learning in drivers with autism does not follow a single pathway and cannot be inferred from any single performance or physiological metric. Instead, multimodal, within-participant analysis is critical for capturing meaningful individual adaptation during simulation-based training. The results have implications for the design and evaluation of driver training systems, supporting flexible, learner-specific assessment frameworks and adaptive approaches that accommodate diverse patterns of engagement and learning.