TY - GEN
T1 - Robot-assisted pedestrian regulation in an exit corridor
AU - Jiang, Chao
AU - Ni, Zhen
AU - Guo, Yi
AU - He, Haibo
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/11/28
Y1 - 2016/11/28
N2 - Due to the faster-is-slower phenomenon in emergency escape, it is desirable to regulate pedestrian flow at the exit or a bottleneck. Modification of pedestrian facilities was previously studied to increase the efficiency and safety by the transportation community. We propose a robot-assisted pedestrian regulation scheme and study passive human-robot interaction (HRI), where the robot acts as a dynamic obstacle that interacts with pedestrians. Such a robot-assisted solution replaces expensive infrastructure modification with real-time reconfigurability. In the paper, we first formulate a robotassisted flow optimization problem based on the social force models of pedestrian dynamics with embedded HRI forces. We then present an online learning algorithm based on adaptive dynamic programming (ADP) to generate motion control so that the robot can replan and adapt its motion to realtime pedestrian flows. The ADP control process uses observed flow information only but not the models of pedestrians, and provides feedback control with online learning and control capability. Simulation results demonstrate efficiency of the proposed method.
AB - Due to the faster-is-slower phenomenon in emergency escape, it is desirable to regulate pedestrian flow at the exit or a bottleneck. Modification of pedestrian facilities was previously studied to increase the efficiency and safety by the transportation community. We propose a robot-assisted pedestrian regulation scheme and study passive human-robot interaction (HRI), where the robot acts as a dynamic obstacle that interacts with pedestrians. Such a robot-assisted solution replaces expensive infrastructure modification with real-time reconfigurability. In the paper, we first formulate a robotassisted flow optimization problem based on the social force models of pedestrian dynamics with embedded HRI forces. We then present an online learning algorithm based on adaptive dynamic programming (ADP) to generate motion control so that the robot can replan and adapt its motion to realtime pedestrian flows. The ADP control process uses observed flow information only but not the models of pedestrians, and provides feedback control with online learning and control capability. Simulation results demonstrate efficiency of the proposed method.
UR - http://www.scopus.com/inward/record.url?scp=85006351755&partnerID=8YFLogxK
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U2 - 10.1109/IROS.2016.7759145
DO - 10.1109/IROS.2016.7759145
M3 - Conference contribution
AN - SCOPUS:85006351755
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 815
EP - 822
BT - IROS 2016 - 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems
T2 - 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2016
Y2 - 9 October 2016 through 14 October 2016
ER -