Reinforcement Learning (RL) has shown excellent performance in solving decision-making and control problems of autonomous driving, which is increasingly applied in diverse driving scenarios. However,
This dataset focuses on enhancing CAV behavior during insertion maneuvers in highway environments (A63 motorway). It covers two scenarios: Ego merging from an entry ramp and Ego on the main road with
The inflexible human-autonomy relationship within autonomous driving scenarios still has not realized deep intelligent synergy, therefore unable to provide adaptive and context-sensitive decision-