Roadside Unit Assisted Optimised Trajectory and Charging Planning for Electric Vehicles: Deventer City Case Study

Due to environmental and climate change concerns, electric vehicles (EVs) are becoming the predominant form of public transportation for achieving Net-Zero ambition set by governments across the globe. Among different challenges associated with EVs integration into the smart grid, the trajectory planning and charging scheduling of EVs are the main focus of research and practical deployments. This paper investigates the localisation of EVs trajectory planning to the optimal charging point and their charging scheduling considering real-world data taken from Deventer city in the Netherlands. It utilises mobile edge servers as roadside units (RSUs) to facilitate the localisation of EVs communication and their charging service. More specifically, this research consists of three phases: In the first phase, we investigate the optimal locations for edge servers deployment followed by optimal trajectory planning to the best charging point considering real-world constraints in the second phase. In the last phase, the optimal charging scheduling at the target charging point is investigated. Considering real-world data for the above-mentioned case study, we design optimisation model and heuristic algorithm for each phase and finally evaluate their performance by comparing them against few counterpart solutions.