<p>To navigate in human social spaces, self-driving cars and other robots must show social intelligence. This involves predicting and planning around pedestrians, understanding their personal space, and establishing trust with them. The present paper gives an overview of our ongoing work on modelling and controlling human–self-driving car interactions using game theory, proxemics and trust, and unifying these fields via quantitative models and robot controllers.</p>
History
School affiliated with
School of Computer Science (Research Outputs)
Publisher
Social Robot Navigation: Advances and Evaluation
Date Submitted
2022-05-16
Date Accepted
2022-04-10
Date of First Publication
2022-05-22
Date of Final Publication
2022-05-22
Event Name
Social Robot Navigation: Advances and Evaluation (SEANavBench 2022)