Dynamic Guidance Strategy for Pedestrian Travel in Large-Scale Activity under Harsh Environment

被引:2
作者
Huang, Wenbo [1 ]
Chen, Yanyan [1 ]
Chai, Shushan [2 ]
Bi, Huibo [1 ]
机构
[1] Beijing Univ Technol, Coll Metropolitan Transportat, Beijing Key Lab Traff Engn, 100 Pingleyuan, Beijing 100124, Peoples R China
[2] Res Inst Rd Safety MPS, Beijing 100062, Peoples R China
关键词
MESSAGE SIGNS; OPTIMAL LOCATIONS; INFORMATION; BEHAVIOR; NETWORK; DRIVERS; DESIGN; MODELS;
D O I
10.1155/2022/8581215
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Large-scale activities such as the Winter Olympics are usually held in areas with low temperature or other harsh environments, which greatly affects the spectating experience of pedestrians. In order to improve the travel efficiency and reduce the safety risk of pedestrians, an adaptive information-distribution strategy of VMS (variable message sign) for road networks is proposed to guide the pedestrians. In the proposed strategy, the dynamic feedback mechanism between the VMS information distribution and the state of crowded pedestrians is established, and the dynamic optimization model of the VMS information release layout is formulated. To evaluate the effectiveness of the strategy, a multiagent-based simulation method is proposed. Through numerical simulation, it is found that the guidance strategy can improve the movement efficiency by adjusting releasing duration of VMS information or improving the information obedience rate of pedestrians. In this paper, a large-scale competition area in the Xiaohaituo Mountain in Beijing was taken as an example to simulate the scenarios of ingress and egress with and without the strategy. The results show that the average walking time and the road congestion can be significantly reduced in the road network with the strategy, and the proportion of pedestrians with shorter travel time can be increased. Therefore, the research can provide theoretical foundation and data support for managers to guide passenger flows and improve the spectating experience.
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页数:16
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