Road rage is increasingly becoming a serious problem on Malaysian roads, with the Malaysian Institute of Road Safety Research reporting that about 18% of registered drivers experience road rage. This issue is impaired by the daily pressures of heavy traffic, where prolonged exposure leads to elevated stress and frustration. These conditions can trigger emotional responses such as anger, aggression, and anxiety, which impair drivers' judgment and increase the likelihood of risky driving behaviors and accidents. The objective of this study is to provide a review of the current psychological and physiological mechanisms underlying driver anger, while mapping existing AI technologies designed to detect and mitigate these emotional responses. The review aims to identify challenges and gaps in current systems, as well as highlight future opportunities for improving road safety through anger detection. The literature was gathered from a comprehensive analysis of existing AI-based driver monitoring systems, focusing on physiological signals. Key findings suggest that AI systems can predict and manage driver anger effectively, offering a proactive approach to improving driver behavior and overall road safety.


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    Titel :

    Driver Anger Expression Detection: A Review


    Beteiligte:


    Erscheinungsdatum :

    17.12.2024


    Format / Umfang :

    407884 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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    Ambak Kamarudin / Shamsudini Shuhada / David Daniel Basil et al. | DOAJ | 2017

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    Sullman, Mark J.M. | Online Contents | 2013