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Ant Colony Based Evacuation Route Optimization Model for Mixed Pedestrian-Vehicle Flows

In: Pedestrian and Evacuation Dynamics 2012

Author

Listed:
  • Qiuping Li

    (Wuhan University, State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing
    Wuhan University, Engineering Research Center for Spatio-temporal Data Smart Acquisition and Application)

  • Zhixiang Fang

    (Wuhan University, State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing
    Wuhan University, Engineering Research Center for Spatio-temporal Data Smart Acquisition and Application)

  • Qingquan Li

    (Wuhan University, State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing
    Wuhan University, Engineering Research Center for Spatio-temporal Data Smart Acquisition and Application)

Abstract

Evacuation for large-scale activities usually involves a great number of pedestrians and vehicles. By applying ant colony optimization algorithm, an evacuation route optimization model for mixed pedestrian-vehicles flows is proposed in this paper. In this model, we construct a two-tier network structure in which the upper tier network is for path finding and evacuation route guidance, and the lower tier subnetwork which depicts the move directions of pedestrians and vehicles respectively is for the simulation of the movements as well as the conflicts between them. The experiment results show that the proposed model has the merit of modeling the interaction dynamics of pedestrians and vehicles and improving evacuation efficiency in an evacuation case of large-scale activities.

Suggested Citation

  • Qiuping Li & Zhixiang Fang & Qingquan Li, 2014. "Ant Colony Based Evacuation Route Optimization Model for Mixed Pedestrian-Vehicle Flows," Springer Books, in: Ulrich Weidmann & Uwe Kirsch & Michael Schreckenberg (ed.), Pedestrian and Evacuation Dynamics 2012, edition 127, pages 1213-1224, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-02447-9_100
    DOI: 10.1007/978-3-319-02447-9_100
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