scholarly journals A Data-Efficient Approach for Evacuation Demand Generation and Dissipation Prediction in Urban Rail Transit System

2021 ◽  
Vol 13 (17) ◽  
pp. 9692
Author(s):  
Xiaoqing Dai ◽  
Han Qiu ◽  
Lijun Sun

Predicting evacuation demand, including its generation and dissipation process, for urban rail transit systems under disruptions, such as line and station closure, often requires comprehensive historical data recorded under homogeneous situations. However, data under disruptions are hard to collect due to various reasons, which makes traditional methods impractical in evacuation demand prediction. To address this problem from the modeling perspective, we develop a data-efficient approach to predict evacuation demand for urban rail transit systems under disruptions. Our model-based approach mainly uses historical data obtained from the natural state, when no shocks take place. We first formulate the mathematical representation of the evacuation demand for every type of urban rail transit station. Input variables in this step are location features related to the station under the disruption, as well as an origin–destination matrix under the natural state. Then, based on these mathematical expressions, we develop a simulation system to imitate the spatio-temporal evolution of evacuation demand within the whole network under disruptions. The transport capacity drop under disruptions is used to describe the disruption situation. Several typical scenarios from the Shanghai metro network are used as examples to implement the proposed method. The results show that our method is able to predict the generation and dissipation processes of evacuation demand, as well model how severely stations will be affected by given disruptions. One general observation we draw from the results is that the most vulnerable stations under disruption, where the locations peak evacuation demand occurs, are mainly turn-back stations, closed stations, and the transfer stations near closed stations. This paper provides new insight into evacuation demand prediction under disruptions. It could be used by transport authorities to better respond to the urban rail transit system disruption.

2018 ◽  
Vol 38 ◽  
pp. 03038
Author(s):  
Ran Liao

With the vigorous development of urban rail transit system, especially the construction of subway system, the safety of subway system draws more and more attention. The study of anti-seismic for underground structures has also become an important problem to be solved in the construction of Metro system. Based on the typical underground structure seismic damage phenomenon, this paper summarizes the seismic characteristics, research methods and design methods of underground structures to offer a guide for engineers.


2012 ◽  
Vol 5 ◽  
pp. 71-76
Author(s):  
Yu Ping Wang ◽  
Ya Ping Zhang ◽  
Hui Zhi Xu

As the major distributing center and intermediate transit point, the scale of transfer station in urban rail transit system directly affects the operational efficiency and overall cost of the entire system. So, accurately controlling the scale of transfer station becomes one of the most important aspects in improving service level and reducing the overall project cost. On the basis of summarizing the method on determining the scale of transfer station both home and abroad, the paper describes the role of the various facilities in rail transfer station, and illustrates the problems of our rail transfer station. Following the above discussion and investigation, the sizes of typical transfer station facilities are discussed and improved (e.g. vertical elevator). Taking the Longjiang Street station example, the proposed methods and models are verified and the analysis result shows that this transfer station should be cross platform interchange mode.


Transport ◽  
2021 ◽  
Vol 0 (0) ◽  
pp. 1-12
Author(s):  
Wencheng Huang ◽  
Yue Zhang ◽  
Yifei Xu ◽  
Rui Zhang ◽  
Minhao Xu Xu ◽  
...  

In order to evaluate the URTPSQ (Urban Rail Transit Passenger Service Quality) comprehensively, find the shortage of URTPSQ, find out the difference between the actual service situation and the passenger’s expectation and demand,and provide passengers with better travel services, a passenger-oriented KANO–Entropy–TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method is proposed and applied in this paper. Firstly, a KANO model is applied to select the service quality indicators from the 24 URTPSQ evaluation sub-indicators, according to the selection results, the KANO service quality indicators of URTPSQ are constructed. Then the sensitivity of the KANO service quality indicators based on the KANO model are calculated and ranked, the PS (Passenger Satisfaction) of each KANO service quality indicator by using the Entropy–TOPSIS method is calculated and ranked. Based on the difference between the sensitivity degree rank and the satisfaction degree rank of each KANO service quality indicator, determine the service quality KANO indicators of the URTPSQ that need to be improved significantly. A case study is conducted by taking the Chengdu subway system in China as a background. The results show that the Chengdu subway operation enterprises should pay attention to the must-be demand first, then the one-dimensional demand, finally the attractive demand. The three indicators, including transfer on the same floor in the station, service quality of staffs of urban rail transit enterprises,and cleanness in the station and passenger coach, need to be improved urgently. For the managers and operators of urban rail transit system, the passengers’ must-be demand should be satisfied first if the KANO model is applied to evaluate the service. The indicators with highest sensitivity degree and lowest TOPSIS value should be improved based on the KANO–Entropy–TOPSIS model.


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