AI-Enabled Connected Autonomous Vehicles Sustainable Routing in Urban Areas

Rapid urbanisation exacerbates traffic congestion,posing significant challenges to economic productivity, environmental quality, and quality of life. Connected and AutonomousVehicles (CAVs) can support traffic authorities in addressingcongestion issues by directly affecting traffic movements bycommunicating paths and routes to vehicles navigating the controlled region. While AI-enabled CAV routing has demonstratedpotential in reducing congestion, the sustainability aspects ofthese strategies are usually overlooked, and require dedicatedapproaches. This paper extends a state-of-the-art AI-enabled routingframework to explicitly incorporate sustainability aspects, under the form of explicit emissions reduction. We evaluate theextended framework on real-world historical data for two urbannetworks, one in the UK and one in Italy. The results confirmthe ability of the designed optimisation approaches in reducing emissions.