When Emotions Take the Wheel: Sequence Effects on Driving Behaviour, and Implications for Adaptive Design and Intelligent Systems

Driving is a complex task that demands cognitive and emotional resources, with emotions frequently influencing performance and safety outcomes. While extensive research has examined how discrete emotional states affect driving performance, the sequential effects of emotional progression have remained largely unexplored despite their prevalence in real-world driving contexts. Through a mixed-factorial experimental design using a driving simulator, the study compared two emotional progression groups that transition from happy to angry and angry to happy across three levels of driving scenario complexity. The findings revealed that the order of emotional experiences significantly influenced driving behaviour, with the Angry-to-Happy group exhibiting higher speeds during positive emotional states compared to the Happy-to-Angry group (F(1, 31) = 7.16, p = 0.012, partial η² = 0.19). These effects varied with scenario complexity, being most pronounced in simpler driving environments and diminishing in complex scenarios where cognitive demands dominated performance outcomes. Complex scenarios required significantly more effort than Simple and Intermediate scenarios (F(2, 20) = 5.01, p = 0.02, partial η² = 0.33), and induced higher frustration (F(2, 20) = 8.36, p = 0.002) as evidenced by cognitive workload measures. Building on these empirical findings, the thesis explores practical applications for automotive HMI design, proposing a nudge-based framework to guide the development of adaptive human-machine interfaces that can respond to drivers' dynamic emotional states. Additionally, it investigates the potential of quantum computing algorithms to enhance driver monitoring systems through more efficient processing of behavioural data, demonstrating that quantum processing was significantly faster than classical methods for analysing driving behaviour patterns. The research also investigates the possible contributions and challenges to acceptance and trust of drivers on possible quantum systems. This thesis contributes to both theoretical understanding of emotional dynamics in driving and practical innovations in HMI design. By demonstrating that emotional transitions and not just discrete emotional states significantly impact driving performance, it establishes a foundation for more sophisticated emotion- and driving-behaviour-aware vehicle technologies that could enhance road safety by addressing the complex interplay between emotions, driving tasks, and driving behaviour.