Optimization of merging pedestrian flows based on adaptive dynamic programming
Date of Original Version
Pedestrian flows in densely-populated areas may cause crowd accidents, and effective pedestrian flow regulation is highly desirable for flow optimization. In this paper, we investigate the problem of regulating two merging pedestrian flows by introducing a mobile robot moving within the flow. The pedestrian flows are regulated through dynamic human-robot interaction during their collective motion. We propose a method based on adaptive dynamic programming (ADP) to learn the optimal motion control of the robot in real time and the pedestrian outflow through the bottleneck area is maximized. Extensive simulations are performed using social force models of pedestrian motion. Simulation results show that the pedestrian outflow is significantly improved with our proposed ADP control.
Proceedings of the American Control Conference
Jiang, Chao, Yi Guo, Zhen Ni, and Haibo He. "Optimization of merging pedestrian flows based on adaptive dynamic programming." Proceedings of the American Control Conference 2019-July, (2019): 2626-2632. doi:10.23919/acc.2019.8814597.