Optimization of Crowd Evacuation With Leaders in Urban Rail Transit Stations - Zhou, Min; Dong, Hairong; Zhao, Yanbo; Ioannou, Petros A.; Wang, Fei-Yue (IEEE transactions on intelligent transportation systems, 2019)
The adoption of passenger leaders could make crowd evacuation in urban railway transit (URT) stations more efficient. The number, location, and the actions of the leaders are the most important elements in an evacuation strategy and have a great impact on evacuation efficiency. This paper proposes a hybrid bi-level model to optimize the number and initial locations of leaders as well as the routes of leaders during the evacuation, which explicitly incorporates the passengers' guidance demand and multi-leader coordination mechanism. The leaders' initial locations are generated by solving the maximal covering location problem (upper level model) and their evacuation routes are determined by a co-simulation heuristic approach (lower level model). The social force model and its modifications are used to model the dynamics of common evacuees, leaders, and followers in simulation models. The convergence performance of the proposed co-simulation heuristic approach and the effectiveness of the optimal evacuation strategy have been investigated and demonstrated using a case study of a typical island platform of Beijing's URT station. Three other evacuation strategies are considered for comparison purposes in order to show the influence of the number and initial locations of leaders as well as the multi-leader coordination mechanism during the evacuation process. Our analysis supported by simulations shows the following: 1) the optimal number of leaders exists for a given human cost and guidance demand constraints; 2) the distribution of leaders for maximal covering makes the evacuation of the followers more efficient; and 3) the proposed optimal evacuation strategy has better performance in terms of shorter evacuation time and higher utilization of exits compared with other considered strategies.