3 papers
cs.LG2025
URB -- Urban Routing Benchmark for RL-equipped Connected Autonomous Vehicles
Ahmet Onur Akman, Anastasia Psarou, MichaÅ Hoffmann +5
Connected Autonomous Vehicles (CAVs) promise to reduce congestion in future urban networks, potentially by optimizing their routing decisions. Unlike for human drivers, these decis…
eess.SY2025
Wardropian Cycles make traffic assignment both optimal and fair by eliminating price-of-anarchy with Cyclical User Equilibrium for compliant connected autonomous vehicles
MichaŠHoffmann, MichaŠBujak, Grzegorz Jamróz +1
Connected and Autonomous Vehicles (CAVs) open the possibility for centralised routing with full compliance, making System Optimal traffic assignment attainable. However, as System…
cs.MA2025
Collaboration Between the City and Machine Learning Community is Crucial to Efficient Autonomous Vehicles Routing
Anastasia Psarou, Ahmet Onur Akman, Åukasz Gorczyca +3
Autonomous vehicles (AVs), possibly using Multi-Agent Reinforcement Learning (MARL) for simultaneous route optimization, may destabilize traffic networks, with human drivers potent…