MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology

Beijing, China

MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology

Beijing, China
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Li M.,MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology | Yue H.,MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology | Zhang B.Y.,MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology | Mi X.Y.,Hebei United University
Advanced Materials Research | Year: 2014

The spatial characteristic indicators of pedestrian facilities for evacuation are presented in order to contribute to the organization and management of pedestrian evacuation flow. An evacuation network is constructed based on the spatial layout of pedestrian facilities, in which the nodes represent moving sub-areas and two-way arc is on behalf of moving bottlenecks. Spatial characteristic indicators are built based on Multiple Origins Single Destination (MOSD) evacuation network including movement distance, movement amount, evacuation bottleneck, and evacuation aggregation extent. Through a case, the computation and application of the spatial characteristic indicators are presented in the layout analysis of pedestrian facilities, in which relevant improvement measures of spatial layout are advised. © (2013) Trans Tech Publications, Switzerland.


Wang J.,MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology | Xiong R.,MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology | Zhu Z.,MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology | Gao C.,MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology | Zhang Q.,MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology
International Journal of Simulation: Systems, Science and Technology | Year: 2016

The swarm intelligent such as vehicular ad hoc networks is applied to developing the decentralized advanced transportation information systems, such as real-time traffic guidance. In this paper, an intelligent traffic guidance algorithm is presented based on the swarm intelligent, and the influence of real-time guidance information on travelling time based on vehicular ad hoc networks is discussed. A car agent with the capacity of wireless communication can receive and perform the traffic guidance information in real-time using the adaptive traffic guidance algorithm. An incident scenario is established to evaluate the effect of equipment rate, communication distance and compliance rate on travelling time during traffic guidance. The simulation results illustrated that three factors contribute to characterize the travelling time of local road networks, and have a significant correlation with travelling time. The results also indicate that three factors exist the optimal value, and the perfect guidance effect can be obtained if the appropriate value ranges of equipment rate, communication distance and compliance rate are acquired, for example, the range of equipment rate is 40%~60% in this study. © 2016 UK Simulation Society. All rights reserved.


Hu C.-P.,MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology | Mao B.-H.,MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology | Zhu Y.-T.,MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology | Gan T.-T.,MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology | Zhang Z.,MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology
Jiaotong Yunshu Xitong Gongcheng Yu Xinxi/Journal of Transportation Systems Engineering and Information Technology | Year: 2014

This paper focuses on different route choice behaviors and characteristics for two types of passengers: the familiar type and unfamiliar type. It develops an optimization model for passenger flow routing with consideration of specific attributes of hub network. This study adjusts distribution schemes of the channel, which has certain impacts on passenger's route choice behaviors. It then minimizes the system cost from the perspective of hub manager. Considering the significant feature of the problem, this study also estimates the probability of each route selected by different types based on the Frank-Wolfe method and Logit model. Moreover, a genetic algorithm is used to solve the problem. Finally, a simple case study illustrates the effectiveness of the proposed method.

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