Data for: Human-like pedestrian models for automated driving systems

This dataset contains the evaluation data supporting the study of a computational rationality based pedestrian model for automated-driving simulation. The pedestrian model is formulated as a partially observable Markov decision process and trained with reinforcement learning in the CARLA simulator. The uploaded Excel file includes data used to evaluate crossing outcomes, human-like crossing behaviors, map transfer, and adaptation to different traffic environments.