EVRoute: An Open-Source Intelligent Routing and Decision-Support Platform for Electric Vehicles

Electric vehicle (EV) adoption has increased the demand for intelligent trip-planning solutions capable of addressing charging infrastructure limitations and reducing range anxiety, a socio-technical barrier that disproportionately affects regions with developing charging networks. This paper presents EVRoute, an open-source intelligent routing and decision-support platform for electric vehicles. The proposed system integrates real charging-station data from Open Charge Map, road-network information from Valhalla, and GPS services provided by Traccar. Its routing engine employs an A*-based state-space search that jointly considers driving and charging times while enforcing battery state-of-charge (SoC) constraints to automatically determine feasible charging stops. The platform was designed based on an exploratory user study that identified charging-station availability and range anxiety as the primary concerns of EV drivers. Experimental evaluation using real charging infrastructure and road-network data from Northeastern Brazil demonstrates that EVRoute successfully converts trips that would otherwise be infeasible into feasible routes through automatic charging-stop planning. In the longest evaluated scenario (685 km), the platform automatically selected three charging stations while maintaining the predefined battery reserve. The results demonstrate that EVRoute bridges the gap between electric vehicle routing research and practical trip-planning tools by combining open-source implementation, real-world data integration, and intelligent route planning, supporting more equitable access to electric mobility in emerging markets.