Graph-Based Routing Algorithm for Request Response and Charging of Shared Autonomous Electric Vehicles

In the era of autonomous electric vehicles (AEVs), the emergence of Shared AEVs presents a unique set of challenges and opportunities. This paper introduces a new graph-based routing algorithm aimed at optimizing the allocation of AEVs and recharging them. The algorithm takes into account multiple factors, including energy requirements, charging infrastructure availability, time constraints, and trip distances, to efficiently respond to passenger requests. In addition, when AEVs face energy constraints, proposed algorithm selects the most cost-effective charging point to minimize charging costs, considering factors like electricity prices. By bridging the transportation network and the power grid, this algorithm can also address more complex constraints like weather situations, road conditions, and battery degradation. Our case studies demonstrate the algorithm's effectiveness in finding optimal routes and managing low state of charge situations. This research opens the door to further exploration in complex urban environments, dynamic request prioritization, and user involvement, offering a promising future for AEV routing and optimization.