Fiorentino, Salvatore (University of Calabria), Dodaro, Carmine (University of Calabria), Maratea, Marco (University of Calabria), Vallati, Mauro (University of Huddersfield)

AI-Enabled Connected Autonomous Vehicles Sustainable Routing in Urban Areas

Scheduled for presentation during the Invited Session "S24b-Traffic Control and Connected Autonomous Vehicles: benefits for efficiency, safety and beyond" (TH-EA-T24), Thursday, November 20, 2025, 14:50−15:30, Coolangata 3

2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC), November 18-21, 2025, Gold Coast, Australia

This information is tentative and subject to change. Compiled on October 18, 2025

Abstract

Rapid urbanisation exacerbates traffic congestion, posing significant challenges to economic productivity, environmental quality, and quality of life. Connected and Autonomous Vehicles (CAVs) can support traffic authorities in addressing congestion issues by directly affecting traffic movements by communicating paths and routes to vehicles navigating the controlled region. While AI-enabled CAV routing has demonstrated potential in reducing congestion, the sustainability aspects of these strategies are usually overlooked, and require dedicated approaches.

This paper extends a state-of-the-art AI-enabled routing framework to explicitly incorporate sustainability aspects, under the form of explicit emissions reduction. We evaluate the extended framework on real-world historical data for two urban networks, one in the UK and one in Italy. The results confirm the ability of the designed optimisation approaches in reducing emissions.