TR2023-099

MPC-based Pedestrian Routing for Congestion Balancing

    •  Menner, M., Di Cairano, S., Hamada, M., Gushima, K., "MPC-based Pedestrian Routing for Congestion Balancing", IEEE Conference on Control Technology and Applications (CCTA), DOI: 10.1109/​CCTA54093.2023.10252891, August 2023.
      BibTeX TR2023-099 PDF
      • @inproceedings{Menner2023aug,
      • author = {Menner, Marcel and Di Cairano, Stefano and Hamada, Masaki and Gushima, Kota},
      • title = {MPC-based Pedestrian Routing for Congestion Balancing},
      • booktitle = {IEEE Conference on Control Technology and Applications (CCTA)},
      • year = 2023,
      • month = aug,
      • doi = {10.1109/CCTA54093.2023.10252891},
      • url = {https://www.merl.com/publications/TR2023-099}
      • }
  • MERL Contact:
  • Research Areas:

    Control, Dynamical Systems, Optimization

Abstract:

This paper presents a model predictive control (MPC)-based algorithm for guiding/routing pedestrians to bal- ance 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.