Dataset of electric autonomous dial-a-ride instances with local energy communities and electricity tariffs

Abstract

Shared autonomous electric vehicle (AEV) fleets offer significant potential for decarbonizing urban mobility, but their efficient operation requires jointly optimizing passenger routing and battery charging under real-world energy pricing constraints. The electric autonomous dial-a-ride problem (e-ADARP) formalizes this challenge, and its integration with local energy communities (LECs) introduces further complexity by coupling fleet scheduling decisions with time-varying community energy dynamics. This article presents a dataset of 20 benchmark instances for the e-ADARP integrated with LECs. The instances are derived from real-world taxi trip data from the city of Porto, Portugal, and incorporate energy data from two clustered LECs, each consisting of 10 prosumers with photovoltaic generation and individual load profiles. Each LEC is associated with a charging station located at the geographic centroid of its prosumers. The dataset comprises instances across 10 size configurations, ranging from 2 AEVs and 20 requests to 20 AEVs and 200 transportation requests, with two electricity tariff scenarios per configuration: a time-of-use tariff and a flat tariff, both incorporating mid-market rate pricing during periods of LEC overproduction. Each instance file encodes geographic coordinates of all nodes, time windows for pickups and dropoffs, vehicle parameters (battery capacity, energy consumption, minimum final state of charge), charging station characteristics, travel time matrices computed via OpenStreetMap shortest paths, and time-discretized energy profiles including community overproduction and electricity tariffs at 15-minute resolution over a 24-hour scheduling horizon. The dataset also includes the full LEC energy data workbook with individual prosumer load profiles, photovoltaic generation profiles, battery storage parameters, and electricity tariffs for both LECs, as well as the instance generation scripts, enabling researchers to develop alternative energy scenarios or modify community configurations. All files are publicly available in Zenodo.