INTERCITY-EVOPT: Driving the Green Transition: AI Framework for EV Corridor Charging

Objetivo

This project addresses a critical barrier to the wider adoption of electric vehicles (EVs): the availability and reliability of charging infrastructure along intercity corridors. Portugal, a frontrunner in Southern Europe, has achieved rapid growth in EV sales and charging facilities, yet long-distance travel still suffers from uneven station distribution, technical failures, waiting times, and range anxiety. These gaps are also present across Europe, showing the need for strategic, data-driven and policy-aligned solutions.

The project will develop an integrated framework that combines Geographic Information Systems (GIS), Multi-Criteria Decision-Making (MCDM), and Artificial Intelligence (AI), including Machine Learning and Deep Reinforcement Learning (DRL). The approach will (i) collect and harmonise traffic, socio-economic, grid, and charging data; (ii) forecast charging demand using advanced statistical and AI models; (iii) integrate forecasts and spatial analyses into a DRL-based optimisation model that considers grid capacity, accessibility, and compliance with the EU Alternative Fuels Infrastructure Regulation (AFIR); and (iv) validate the framework in Portugal with academic and industry partners.

Expected results include suitability maps, optimisation prototypes, and a roadmap with policy recommendations. Scientifically, the project will advance the state of the art by linking GIS, MCDM and AI in one decision-support system. At the same time, it will provide practical tools for operators and policymakers to optimise investments, reduce costs, and support the European Green Deal. At the societal level, the project will improve accessibility, reduce range anxiety, and accelerate the transition to sustainable mobility in Europe.