Social scenarios and a social impact assessment methodology for autonomous vehicles
Researchers from Ghent University designed social scenarios and a social impact assessment (SIA) methodology for autonomous vehicles (AVs) in order to help local and transport authorities with the development and implementation of pilots with AVs. This will contribute to more inclusive transport and spatial planning.
Four conceptual social scenarios were designed based on the social key factors ‘complexity’ (space, time, and autonomous vehicles) and ‘social acceptance’: ‘Showcase Visitor’, ‘Curious Tripper’, ‘Easy Rider’, and ‘Sustainable PT Commuter’. These scenarios approach respectively the pilots in Almere (the Netherlands), Varberg (Sweden), Inverness (Scotland), and Hanover (Germany). The scenarios can be the start of discussions with different stakeholders. The ideal outcomes for the authorities are to choose the most suitable AV pilot for the local social groups (with attention for vulnerable groups) and if necessary take strategic actions.
The social impact assessment (SIA) methodology consists of several processes to foster knowledge and develop strategies. The designed methodology distinguishes the transport measure and social scenarios. This is followed by an identification phase in which the social groups, social Key Performance Indicators (KPIs), and social effects are being identified. If the social effects are significant, they will be perceived as social impacts and can be reviewed for each social group. From here onwards, the social impact assessment starts complemented by an analysis of the distribution of the impacts. In the end, it is important to provide feedback for the authorities and summarize the lessons learned and possible best practices. Some of the most important social impacts can be analysed within this methodology: accessibility, environment and health, safety, liveability, and employment. The SIA is a useful tool before, during, and after the implementation phase. The authorities have the power to anticipate and monitor the social impacts by mitigating the negative social impacts and maximising the positive social impacts in their decision-making process.
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