Social acceptance is a major hurdle for autonomous vehicle technology, central to which is ensuring both passengers and nearby pedestrians feel safe. This idea of ‘feeling safe’ and perceived safety is highly subjective and rooted in human intuition. As such, traditional analytical approaches to autonomous navigation often fail to cater for the social expectations of individuals. Therefore, this paper proposes an approach to capture the complexity of social expectations and integrate this complexity into a 3-layered Contextual Speed Controller. The layers are; the legal road speed limit, the socially acceptable speed given the number of nearby pedestrians, and the socially acceptable speed based on proximity to nearby pedestrians. An implementation of this layered approach was tested in areas of both low and high density of vehicle-pedestrian interactions. As social acceptability is a subjective measure, the system is assessed through comparative metrics against a human driver operating within a similar urban context. From the experiments conducted, the lower two layers were seen working in tandem to modulate the vehicle speed to appropriate levels that mimicked conservative human driver behaviour. In this paper, the need for different driving schemes to navigate different road environments was identified, building the foundation for future human user studies to validate this approach for perceivably safe autonomous driving.


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    Titel :

    The Design of a Pedestrian Aware Contextual Speed Controller for Autonomous Driving


    Beteiligte:
    Jiang, Daniel (Autor:in) / Worrall, Stewart (Autor:in) / Shan, Mao (Autor:in)


    Erscheinungsdatum :

    08.10.2022


    Format / Umfang :

    2775208 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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