activity
20242026
collaborators

8 papers

eess.SY2026

Distributive Perimetral Queue Balancing Mechanisms: Towards Equitable Urban Traffic Gating and Fair Perimeter Control

Kevin Riehl, Lea Künstler, Ying-Chuan Ni +4

Perimeter control is an effective urban traffic management strategy that regulates inflow to congested urban regions using aggregate network dynamics. While existing approaches pri…

cs.GT2025

Equilibria in routing games with connected autonomous vehicles will not be strong, as exclusive clubs may form

Rafał Kucharski, Anastasia Psarou, Natello Descormier

User Equilibrium is the standard representation of the so-called routing game in which drivers adjust their route choices to arrive at their destinations as fast as possible. Askin…

cs.MA2025

Autonomous vehicles need social awareness to find optima in multi-agent reinforcement learning routing games

Anastasia Psarou, Łukasz Gorczyca, Dominik Gaweł +1

Previous work has shown that when multiple selfish Autonomous Vehicles (AVs) are introduced to future cities and start learning optimal routing strategies using Multi-Agent Reinfor…

cs.MA2025

Impact of Collective Behaviors of Autonomous Vehicles on Urban Traffic Dynamics: A Multi-Agent Reinforcement Learning Approach

Ahmet Onur Akman, Anastasia Psarou, Zoltán György Varga +2

This study examines the potential impact of reinforcement learning (RL)-enabled autonomous vehicles (AV) on urban traffic flow in a mixed traffic environment. We focus on a simplif…

cs.LG2025

URB -- Urban Routing Benchmark for RL-equipped Connected Autonomous Vehicles

Ahmet Onur Akman, Anastasia Psarou, Michał 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…

cs.MA2025

RouteRL: Multi-agent reinforcement learning framework for urban route choice with autonomous vehicles

Ahmet Onur Akman, Anastasia Psarou, Łukasz Gorczyca +3

RouteRL is a novel framework that integrates multi-agent reinforcement learning (MARL) with a microscopic traffic simulation, facilitating the testing and development of efficient…