9 papers
Linking Behaviour and Perception to Evaluate Meaningful Human Control over Partially Automated Driving
Ashwin George, Lucas Elbert Suryana, Lorenzo Flipse +5
Partial driving automation creates a tension: drivers remain legally responsible for vehicle behaviour, yet their active control is significantly reduced. This reduction undermines…
Beyond Conservative Automated Driving in Multi-Agent Scenarios via Coupled Model Predictive Control and Deep Reinforcement Learning
Saeed Rahmani, Gözde Körpe, Zhenlin +4
Automated driving at unsignalized intersections is challenging due to complex multi-vehicle interactions and the need to balance safety and efficiency. Model Predictive Control (MP…
Artificial Intelligence for Modeling and Simulation of Mixed Automated and Human Traffic
Saeed Rahmani, Shiva Rasouli, Daphne Cornelisse +3
Autonomous vehicles (AVs) are now operating on public roads, which makes their testing and validation more critical than ever. Simulation offers a safe and controlled environment f…
CARE Drive A Framework for Evaluating Reason-Responsiveness of Vision Language Models in Automated Driving
Lucas Elbert Suryana, Farah Bierenga, Sanne van Buuren +6
Foundation models, including vision language models, are increasingly used in automated driving to interpret scenes, recommend actions, and generate natural language explanations.…
A Framework for Human-Reason-Aligned Trajectory Evaluation in Automated Vehicles
Lucas Elbert Suryana, Saeed Rahmani, Simeon Craig Calvert +2
One major challenge for the adoption and acceptance of automated vehicles (AVs) is ensuring that they can make sound decisions in everyday situations that involve ethical tension.…
A Framework for Ethical Decision-Making in Automated Vehicles through Human Reasons-based Supervision
Lucas Elbert Suryana, Saeed Rahmani, Simeon Craig Calvert +2
Ethical dilemmas are a common challenge in everyday driving, requiring human drivers to balance competing priorities such as safety, efficiency, and rule compliance. However, much…