Optimization of merging pedestrian flows based on adaptive dynamic programming

Chao Jiang, Yi Guo, Zhen Ni, Haibo He

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

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.

Original languageEnglish
Title of host publication2019 American Control Conference, ACC 2019
Pages2626-2632
Number of pages7
ISBN (Electronic)9781538679265
DOIs
StatePublished - Jul 2019
Event2019 American Control Conference, ACC 2019 - Philadelphia, United States
Duration: 10 Jul 201912 Jul 2019

Publication series

NameProceedings of the American Control Conference
Volume2019-July
ISSN (Print)0743-1619

Conference

Conference2019 American Control Conference, ACC 2019
Country/TerritoryUnited States
CityPhiladelphia
Period10/07/1912/07/19

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