MPC-based Pedestrian Routing for Congestion Balancing.

Marcel Menner,Stefano Di Cairano, Masaki Hamada, Kota Gushima

CCTA(2023)

引用 0|浏览1
暂无评分
摘要
This paper presents a model predictive control (MPC)-based algorithm for guiding/routing pedestrians to balance congestion levels in crowded places such as train stations. The proposed algorithm uses arrow displays at junctions, whose guidance direction and display intensity are computed using MPC by leveraging pedestrian flow predictions. The MPC uses a congestion prediction model relating the display action to the percentage of pedestrians that are expected to change their intended walking direction, i.e., the percentage of pedestrians that are being re-routed. Simulation results show that the congestion imbalance can be reduced significantly using the proposed algorithm.
更多
查看译文
关键词
congestion balancing,congestion imbalance,congestion prediction model,crowded places,model predictive control-based algorithm,MPC-based pedestrian routing,pedestrian flow predictions,train stations
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要