127 citations · 288 across the 53 of their papers we have counts for
12 papers · 1 filter
Controllable Generative Trajectory Prediction via Weak Preference Alignment
Yongxi Cao, Julian F. Schumann, Jens Kober +2
Deep generative models such as conditional variational autoencoders (CVAEs) have shown great promise for predicting trajectories of surrounding agents in autonomous vehicle plannin…
How Much Is Too Much? Adaptive, Context-Aware Risk Detection in Naturalistic Driving
Amir Hossein Kalantari, Eleonora Papadimitriou, Arkady Zgonnikov +1
Reliable risk identification based on driver behavior data underpins real-time safety feedback, fleet risk management, and evaluation of driver-assist systems. While naturalistic d…
STEP: Structured Training and Evaluation Platform for benchmarking trajectory prediction models
Julian F. Schumann, Anna Mészáros, Jens Kober +1
While trajectory prediction plays a critical role in enabling safe and effective path-planning in automated vehicles, standardized practices for evaluating such models remain under…
Towards Human-Centric Evaluation of Interaction-Aware Automated Vehicle Controllers: A Framework and Case Study
Federico Scarì, Olger Siebinga, Arkady Zgonnikov
As automated vehicles (AVs) increasingly integrate into mixed-traffic environments, evaluating their interaction with human-driven vehicles (HDVs) becomes critical. In most researc…
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…
Principles and Reasons Behind Automated Vehicle Decisions in Ethically Ambiguous Everyday Scenarios
Lucas Elbert Suryana, Simeon Calvert, Arkady Zgonnikov +1
Automated vehicles (AVs) increasingly encounter ethically ambiguous situations in everyday driving--scenarios involving conflicting human interests and lacking clearly optimal cour…
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.…
Active inference as a unified model of collision avoidance behavior in human drivers
Julian F. Schumann, Johan Engström, Leif Johnson +4
Collision avoidance -- involving a rapid threat detection and quick execution of the appropriate evasive maneuver -- is a critical aspect of driving. However, existing models of hu…
Realistic Adversarial Attacks for Robustness Evaluation of Trajectory Prediction Models via Future State Perturbation
Julian F. Schumann, Jeroen Hagenus, Frederik Baymler Mathiesen +1
Trajectory prediction is a key element of autonomous vehicle systems, enabling them to anticipate and react to the movements of other road users. Evaluating the robustness of predi…
Feasible Action Space Reduction for Quantifying Causal Responsibility in Continuous Spatial Interactions
Ashwin George, Luciano Cavalcante Siebert, David A. Abbink +1
Understanding the causal influence of one agent on another agent is crucial for safely deploying artificially intelligent systems such as automated vehicles and mobile robots into…
Understanding Driver Cognition and Decision-Making Behaviors in High-Risk Scenarios: A Drift Diffusion Perspective
Heye Huang, Zheng Li, Hao Cheng +4
Ensuring safe interactions between autonomous vehicles (AVs) and human drivers in mixed traffic systems remains a major challenge, particularly in complex, high-risk scenarios. Thi…
Hybrid Human-Machine Perception via Adaptive LiDAR for Advanced Driver Assistance Systems
Federico Scarì, Nitin Jonathan Myers, Chen Quan +1
Accurate environmental perception is critical for advanced driver assistance systems (ADAS). Light detection and ranging (LiDAR) systems play a crucial role in ADAS; they can relia…