3 papers
cs.HC2026
Realistic adversarial scenario generation via human-like pedestrian model for autonomous vehicle control parameter optimisation
Yueyang Wang, Mehmet Dogar, Russell Darling +1
Autonomous vehicles (AVs) are rapidly advancing and are expected to play a central role in future mobility. Ensuring their safe deployment requires reliable interaction with other…
cs.AI2025
Realistic pedestrian-driver interaction modelling using multi-agent RL with human perceptual-motor constraints
Yueyang Wang, Mehmet Dogar, Gustav Markkula
Modelling pedestrian-driver interactions is critical for understanding human road user behaviour and developing safe autonomous vehicle systems. Existing approaches often rely on r…
cs.HC2024
Modeling Pedestrian Crossing Behavior: A Reinforcement Learning Approach with Sensory Motor Constraints
Yueyang Wang, Aravinda Ramakrishnan Srinivasan, Yee Mun Lee +1
Understanding pedestrian behavior is crucial for the safe deployment of Autonomous Vehicles (AVs) in urban environments. Traditional pedestrian behavior models often fall into two…