Synthetic Participatory Planning of Shard Automated Electric Mobility Systems
–arXiv.org Artificial Intelligence
Mobility systems worldwide confront escalating challenges--aging infrastructure, increasing environmental impacts from transportation emissions, and widening service provision gaps that exacerbate social inequalities. Addressing these challenges demands smart and adaptive planning strategies to effectively leverage both mature and emerging technologies--including autonomous driving, vehicle electrification, low-latency communication, and Mobility-as-a-Service (MaaS) platforms. Shared Automated Electric Mobility Systems (SAEMS), exemplified by demand-responsive autonomous transit and passenger car services, autonomous electric micro-mobility systems, and unmanned aerial vehicle (UAV) delivery services, present a conceptual framework for integrating and leveraging these existing and promising technologies and addressing the escalating challenges. However, the full advantages and potential side effects of SAEMS often remain uncertain due to environmental, technological, and socioeconomic factors. This ambiguity underscores the importance of integrating a broad spectrum of domain knowledge and perspectives--ranging from land use zoning to charging infrastructure engineering, and from local business operations to residents' daily experiences-- into coherent planning processes.
arXiv.org Artificial Intelligence
Jul-7-2024
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