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Urban Rail Transit

Urban Rail Transit

Data Statistics and Development Analysis of Urban Rail Transit in China in 2020

YE Xiaoping;FENG Aijun

Tunnel Construction,2021,Vol 41,No. 05


Innovative Practice of Urban Express Rail Lines in Guangzhou

JING Guosheng;HUANG Rongxin;XIE Zhiming

Urban Transport of China,2020,Vol 18,No. 01

【Abstract】 To meet the demand for development from the Greater Bay Area of Guangdong-Hong Kong-Macao in the new era, the rail transit network must adapt to the situation characterized by the travel need of high frequency and high speed between cities and shift the focuses from the maximizing service coverage to high service efficiency in order to optimize the development planning of public land use. By examining the three development stages described as the space extension, urban-rural integration, and hub-type network layout, this paper summarizes the achievements and inadequacies of Guangzhou urban express rail service. The paper then suggests the future key improvement of accelerating the development of the Bay Area railway and urban express rail service (above 60 km) as well as Line A (above 400 km). These developments can promote the innovative service connection among and between the national railway lines, inter-city rail lines and urban rail transit lines and successfully integrate the three networks, which helps to meet the Guangzhou travel demand around the Greater Bay Area and inside the metropolitan area.

Statistics on Annual Data of Urban Rail Transit in China in 2019

Tunnel Construction,2020,Vol 40,No. 05


Modeling and forecasting of COVID-19 spread in urban rail transit system

LEI Bin;LIU Xing-liang;CAO Zhen;HAO Ya-rui;ZHANG Yuan;CHEN Xin-miao

Journal of Traffic and Transportation Engineering,2020,Vol 20,No. 03

【Abstract】 Passengers in urban rail transit system amid COVID-19 are divided into the susceptible, the infected, and the exposed considering the travel characteristics of urban rail transit. On the assumption that allows the free spread of COVID-19, the infection probability of 0.41 is selected based on related studies. The travel of COVID-19 cases in urban rail transit is divided into inbound/outbound phase and riding phase. Considering the effective spread range of COVID-19 as well as the distribution and moving characteristics of passengers, the model of COVID-19 spread in the urban rail transit system is built. With the metro system in a certain city taken as the simulation case, a total of 13 infected cases in metro are assumed. With the accessibility of historical passenger data, the parameters in the model are determined. The possible infections at different loading levels are forecasted, and the elements related to possible infections are discussed. The analysis results indicate that when the loading level decreases to 10% of the average level, the possible infections in most cases are less than 1, which proves the effectiveness of control intensity of passengers in urban rail transit. The change in possible infections caused by the reduction in passenger number in the departure/arrival stations (less than 20%) is less than that caused by the reduction in passenger number in the compartment (60%–80%). Therefore, the passenger density in the compartment has a more significant impact on the possible infections than that in the station. In a stopover, if the ratio of the on/off board passenger number ratio is no more than 1, the possible infections can be controlled effectively. If station number is in positively linear correlation with possible infections, the function among the loading level, stop number, and possible infections will have satisfying goodness of fitting (determination coefficient is 0.700 1).

Annual Statistic Data of Urban Rail Transit in Chinese Mainland in 2018

Tunnel Construction,2019,Vol 39,No. 04


Connecting Bus Lines to Urban Rail Transit: A Case Study of Wuhan

LU Zechao;LIU Xia

Urban Transport of China,2019,Vol 17,No. 06

【Abstract】 To strengthen the linkages among public transit services, this paper proposes an optimization model for connecting bus service network to urban rail transit network with an ant colony algorithm. Considering the constraints of bus network layout and restriction between passenger demand for transfer and bus capacity, the model divides bus stops into different levels based on urban roadway classification to improve the flexibility in bus routes planning. The paper also introduces how to use the ant colony algorithm to optimize the model, which can improve the rate of convergence. With the connecting bus network within the surrounding areas of Optics Valley Square subway station as an example, the model demonstrates how the optimization of bus network works. The result shows that the ant colony algorithm significantly improves the connecting capacity between the classification-based bus network and rail transit, which can reduce the total system cost.

Statistics of Urban Rail Transit in Mainland of China, 2017

Tunnel Construction,2018,Vol 38,No. 03


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