TY - GEN
T1 - How shall i drive? interaction modeling and motion planning towards empathetic and socially-graceful driving
AU - Ren, Yi
AU - Elliott, Steven
AU - Wang, Yiwei
AU - Yang, Yezhou
AU - Zhang, Wenlong
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/5
Y1 - 2019/5
N2 - While intelligence of autonomous vehicles (AVs) has significantly advanced in recent years, accidents involving AVs suggest that these autonomous systems lack gracefulness in driving when interacting with human drivers. In the setting of a two-player game, we propose model predictive control based on social gracefulness, which is measured by the discrepancy between the actions taken by the AV and those that could have been taken in favor of the human driver. We define social awareness as the ability of an agent to infer such favorable actions based on knowledge about the other agent's intent, and further show that empathy, i.e., the ability to understand others' intent by simultaneously inferring others' understanding of the agent's self intent, is critical to successful intent inference. Lastly, through an intersection case, we show that the proposed gracefulness objective allows an AV to learn more sophisticated behavior, such as passive-aggressive motions that gently force the other agent to yield.
AB - While intelligence of autonomous vehicles (AVs) has significantly advanced in recent years, accidents involving AVs suggest that these autonomous systems lack gracefulness in driving when interacting with human drivers. In the setting of a two-player game, we propose model predictive control based on social gracefulness, which is measured by the discrepancy between the actions taken by the AV and those that could have been taken in favor of the human driver. We define social awareness as the ability of an agent to infer such favorable actions based on knowledge about the other agent's intent, and further show that empathy, i.e., the ability to understand others' intent by simultaneously inferring others' understanding of the agent's self intent, is critical to successful intent inference. Lastly, through an intersection case, we show that the proposed gracefulness objective allows an AV to learn more sophisticated behavior, such as passive-aggressive motions that gently force the other agent to yield.
UR - http://www.scopus.com/inward/record.url?scp=85071512222&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85071512222&partnerID=8YFLogxK
U2 - 10.1109/ICRA.2019.8793835
DO - 10.1109/ICRA.2019.8793835
M3 - Conference contribution
AN - SCOPUS:85071512222
T3 - Proceedings - IEEE International Conference on Robotics and Automation
SP - 4325
EP - 4331
BT - 2019 International Conference on Robotics and Automation, ICRA 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 International Conference on Robotics and Automation, ICRA 2019
Y2 - 20 May 2019 through 24 May 2019
ER -