| Title | Autonomous Shuttle-as-a-Service (ASaaS): Challenges, Opportunities, and Social Implications |
|---|---|
| ID_Doc | 68027 |
| Authors | Bucchiarone, A; Battisti, S; Marconi, A; Maldacea, R; Ponce, DC |
| Title | Autonomous Shuttle-as-a-Service (ASaaS): Challenges, Opportunities, and Social Implications |
| Year | 2021 |
| Published | Ieee Transactions On Intelligent Transportation Systems, 22, 6 |
| Abstract | Providing mobility services effectively to residents and visitors is a complex socio-technical system task to city public managers. Smart mobility systems aim to support the efficient exploitation of city transport facilities and sustainable mobility within the urban environment. People need to travel quickly and conveniently between locations at different scales, ranging from a few blocks within a city to a journey across cities. At the same time, goods need to be timely delivered, considering both the users and the businesses' needs. Several cities indicated an interest in using Autonomous Vehicles (AV) for the "last-mile" mobility services in the last few years. With them, it seems to be easier to get people and goods around using fewer vehicles. In this context, Autonomous Shuttles (AS) are beginning to be thought of as a new mobility/delivery service into the city center where narrow streets are not easily served by traditional buses. They allow them to perform critical areas with minimal new infrastructure and reduce noise and pollution. The article analyses the state-of-art on autonomous shuttles by proposing four application scenarios targeting the last-mile delivery of goods, the tourist experiences, and the shared and integrated mobility. Furthermore, we contribute with the proposition of the Autonomous Shuttles-as-a service (ASaaS) concept as the key pillar for the realization of innovative and sustainable proximity mobility. Our research proposed new research challenges for ASaaS, and we discuss social implications and governance challenges that consider user engagement and sustainability. It also recommended extending new research to focus on simulation and machine learning techniques for last-mile mobility planning and explore the journeys tracking certification via artificial intelligence and blockchain-based techniques. |
| https://doi.org/10.1109/tits.2020.3025670 |
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