scholarly journals Identification of Inelastic Subway Trips Based on Weekly Station Sequence Data: An Example from the Beijing Subway

2018 ◽  
Vol 10 (12) ◽  
pp. 4725 ◽  
Author(s):  
Hainan Huang ◽  
Yi Lin ◽  
Jiancheng Weng ◽  
Jian Rong ◽  
Xiaoming Liu
Keyword(s):  
Sequence Data ◽  
Revealed Preference ◽  
Urban Rail Transit ◽  
Distribution Analysis ◽  
Survey Validation ◽  
Urban Rail ◽  
Subway System ◽  
Weekly Sample ◽  
Main Component ◽  
Beijing Subway

Urban rail transit has become an indispensable option for Beijing residents. Subway inelastic users (SIUs) are the main component among all users. Understanding the proportion of SIUs and their characteristics is important in developing service promotions and helpful for subway agencies in making marketing policies. This paper proposes a novel and simple identification process for identifying regular subway inelastic trips (SITs) in order to distinguish SITs and non-SITs and extract their characteristics. Weekly station sequence (WSS) is selected as the data-based format, principles of SIUs are discussed and chosen, and the framework of SIT identification is applied to a large weekly sample from the Beijing Subway. A revealed preference (RP) survey and results analysis are undertaken to estimate the performance of the proposed methods. The RP survey validation shows that accuracy reaches as high as 94%, and the distribution analysis of SITs and their origin-destinations (ODs) indicate that the SIT characteristics extracted are consistent with the situation in Beijing. The proportion of SIUs is stable on workdays and is more than 80% during rush hour. The efforts described in this paper can provide subway managers with a useful and convenient method to understand the characteristics of subway passengers and the performance of a subway system.

scholarly journals Overview of Anti-Seismic Researches of Underground Structures

2018 ◽  
Vol 38 ◽  
pp. 03038
Author(s):  
Ran Liao
Keyword(s):  
Research Methods ◽  
Underground Structure ◽  
Seismic Damage ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Underground Structures ◽  
Transit System ◽  
Urban Rail ◽  
Subway System ◽  
Metro System

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.

Discovering the evolution of Beijing Rail Network in fifty years

2020 ◽  
Vol 34 (21) ◽  
pp. 2050212
Author(s):  
Zijia Wang ◽  
Jingqi Li ◽  
Liping Huang ◽  
Zhigang Yang
Keyword(s):  
Pearson Correlation ◽  
Service Level ◽  
Urban Rail Transit ◽  
Transit Network ◽  
Rail Network ◽  
Topological Evolution ◽  
Topological Network ◽  
Urban Rail ◽  
Subway System ◽  
One Year

Urban rail transit (URT) system plays a significant role in daily commuting. The main features of URT could be abstracted into two kinds of networks, topological network and transit network. The correlation between topological network and transit network could represent the service level of transportation which is also a main focus to some extent. In this study, static analysis based on one year or single analysis based on one aspect are abundant, the main reason of which is the deficiency of the consistent demand data. In this regard, a comprehensive analysis of the evolution and their correlation of the two network are carried out in this work. We first revisit the topological evolution of rail network on the basis of URT network statistic indicators with a fifty-year time span. Then, based on the traditional node-place model, a correctional node-place model between demand spatial distribution and closeness centrality is established. Pearson correlation coefficient is also employed for a precise analysis. Finally, the application of the model and the corresponding analysis on Beijing Subway System (BSS) examine and evaluate the development level and service level of URT system in Beijing, and some solid evidence for relative decision-making is provided.

scholarly journals A Method to Estimate URT Passenger Spatial-Temporal Trajectory with Smart Card Data and Train Schedules

2020 ◽  
Vol 12 (6) ◽  
pp. 2574
Author(s):  
Taoyuan Yang ◽  
Peng Zhao ◽  
Xiangming Yao
Keyword(s):  
Urban Rail Transit ◽  
Passenger Flow ◽  
Precise Estimation ◽  
Smart Card Data ◽  
Urban Rail ◽  
Flow Assignment ◽  
The Difference ◽  
Passenger Flow Assignment ◽  
Temporal Trajectory ◽  
Beijing Subway

Precise estimation of passenger spatial-temporal trajectory is the basis for urban rail transit (URT) passenger flow assignment and ticket fare clearing. Inspired by the correlation between passenger tap-in/out time and train schedules, we present a method to estimate URT passenger spatial-temporal trajectory. First, we classify passengers into four types according to the number of their routes and transfers. Subsequently, based on the characteristic that passengers tap-out in batches at each station, the K-means algorithm is used to assign passengers to trains. Then, we acquire passenger access, egress, and transfer time distribution, which are used to give a probability estimation of passenger trajectories. Finally, in a multi-route case of the Beijing Subway, this method presents an estimation result with 91.2% of the passengers choosing the same route in two consecutive days, and the difference of route choice ratio in these two days is 3.8%. Our method has high accuracy and provides a new method for passenger microcosmic behavior research.

scholarly journals Demand Analysis and Distribution of Single-Trip Ticket Cards for Urban Rail Transit

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Zi-jia Wang ◽  
Jing-qi Li ◽  
Jiang-yue Wu ◽  
Zhi-gang Yang
Keyword(s):  
Urban Rail Transit ◽  
Distribution Model ◽  
Rail Transit ◽  
Effective Management ◽  
Transit Systems ◽  
Urban Rail ◽  
Usage Patterns ◽  
Subway System ◽  
Loading And Unloading ◽  
Hybrid Distribution

In the current urban rail transit systems, nearly 15% of passengers are noncommuter travelers who use single-trip ticket cards (ticket cards). Accordingly, the effective management of ticket cards is of great importance. This article suggests a time series model for use in predicting ticket card storage based on the characteristics of ticket cards collected by an automatic fare collection (AFC) system. The distribution cycle, station types, and distribution volume of each station are also determined. Then, drawing on small package transportation feasibility theory, an unbalanced distribution model between production and demand (unbalanced distribution model), as well as a hybrid distribution model of loading and unloading (hybrid distribution model), is established. Application of these models to the Beijing Subway system is used to verify the efficiency and feasibility of such a hybrid distribution model. The analysis and results offer insights into usage patterns of urban rail transit ticket cards, providing solid evidence for a relative decision-making process.

scholarly journals An Improved Multi-Sensor MTI Time-Series Fusion Method to Monitor the Subsidence of Beijing Subway Network during the Past 15 Years

2020 ◽  
Vol 12 (13) ◽  
pp. 2125
Author(s):  
Li Duan ◽  
Huili Gong ◽  
Beibei Chen ◽  
Chaofan Zhou ◽  
Kunchao Lei ◽  
...  
Keyword(s):  
Time Series ◽  
Land Subsidence ◽  
Mean Squared Error ◽  
Deformation Monitoring ◽  
Urban Rail Transit ◽  
Stable Operation ◽  
Urban Rail ◽  
Urban Safety ◽  
Multi Temporal ◽  
Beijing Subway

Land subsidence threatens the stable operation of urban rail transit, including subways. Obtaining deformation information during the entire life-cycle of a subway becomes a necessary means to guarantee urban safety. Restricted by sensor life and cost, the single-sensor Multi-temporal Interferometric Synthetic Aperture Radar (MTI) technology has been unable to meet the needs of long-term sequence, high-resolution deformation monitoring, especially of linear objects. The multi-sensor MTI time-series fusion (MMTI-TSF) techniques has been proposed to solve this problem, but rarely mentioned. In this paper, an improved MMTI-TSF is systematically explained and its limitations are discussed. Taking the Beijing Subway Network (BSN) as a case study, through cross-validation and timing verification, we find that the improved MMTI-TSF results have higher accuracy (R2 of 98% and, Root Mean Squared Error (RMSE) of 4mm), and compared with 38 leveling points, the fitting effect of the time series is good. We analyzed the characteristics of deformation along the BSN over a 15-year periods. The results suggest that there is a higher risk of instability in the eastern section of Beijing Subway Line 6 (L6). The land subsidence characteristics along the subway lines are related to its position from the subsidence center, and the edge of the subsidence center presents a segmented feature.

Optimal Train Size and Headway for Urban Rail Transit System

2012 ◽  
Vol 253-255 ◽  
pp. 2020-2023
Author(s):  
Xue Jun Liu ◽  
Chuan Min Mi ◽  
Yuan Yuan Wang ◽  
Wei Vivien Shi
Keyword(s):  
Solution Procedure ◽  
Urban Rail Transit ◽  
Level Of Service ◽  
Load Factor ◽  
Rail Transit ◽  
Total System ◽  
Transit System ◽  
Demand Distribution ◽  
Urban Rail ◽  
Subway System

An analytical model and a solution procedure are proposed to optimize train size and headway for an urban rail transit system wherein passengers demand is assumed to be sensitive to fare and the level of service, in terms of load factor and waiting time. It is found that an optimal temporal headway and train size for different demand distribution that maximizes profit and minimize total system cost for the studied subway system can be efficiently solved.

The Optimization of Arriving and Departing Time of Trains in Urban Rail Transit Based on Passenger Transfer

2014 ◽  
Vol 587-589 ◽  
pp. 1958-1962
Author(s):  
Jie Ping Sun
Keyword(s):  
Travel Time ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Operation Process ◽  
Urban Rail ◽  
Practical Operation ◽  
Time Extension ◽  
Transfer Stations ◽  
Important Significance ◽  
Beijing Subway

In this paper, there is a study on the effect of the lack of coordination between trains in the network, such as waiting aggravation, travel time extension. Through the study of the practical operation process and passenger transfer characteristics of urban rail transit, according to the types of line crossing, taking the minimized waiting time of all transfer passengers in station as the object function, the optimization model was designed for three lines with two intersections, solve the model by using the Lingo, and transfer stations, Xidan and Dongdan station, from lines No.1 No.4 and No.5 of Beijing Subway Network are chosen as an example to validate its rationality and availability. The result shows that the model is of important significance to reduce the travel time for transfer passengers.

scholarly journals Using Vehicle Interior Noise Classification for Monitoring Urban Rail Transit Infrastructure

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 1112
Author(s):  
Yifeng Wang ◽  
Ping Wang ◽  
Qihang Wang ◽  
Zhengxing Chen ◽  
Qing He
Keyword(s):  
Urban Rail Transit ◽  
Interior Noise ◽  
Classification Model ◽  
Training Dataset ◽  
Vehicle Interior ◽  
Vehicle Interior Noise ◽  
Urban Rail ◽  
Subway System ◽  
Noise Classification ◽  
Maintenance Work

This study developed a multi-classification model for vehicle interior noise from the subway system, collected on smartphones. The proposed model has the potential to be used to analyze the causes of abnormal noise using statistical methods and evaluate the effect of rail maintenance work. To this end, first, we developed a multi-source data (audio, acceleration, and angle rate) collection framework via smartphone built-in sensors. Then, considering the Shannon entropy, a 1-second window was selected to segment the time-series signals. This study extracted 45 features from the time- and frequency-domains to establish the classifier. Next, we investigated the effects of balancing the training dataset with the Synthetic Minority Oversampling Technique (SMOTE). By comparing and analyzing the classification results of importance-based and mutual information-based feature selection methods, the study employed a feature set consisting of the top 10 features by importance score. Comparisons with other classifiers indicated that the proposed XGBoost-based classifier runs fast while maintaining good accuracy. Finally, case studies were provided to extend the applications of this classifier to the analysis of abnormal vehicle interior noise events and evaluate the effects of rail grinding.

Independent Technology of CBTC System and Management Innovation in Urban Rail Transit

2012 ◽  
Vol 236-237 ◽  
pp. 671-676 ◽  
Author(s):  
Shu Kui Ding
Keyword(s):  
Urban Rail Transit ◽  
Demonstration Project ◽  
Management Innovation ◽  
Wave Antenna ◽  
Core Technology ◽  
Urban Rail ◽  
Management Concepts ◽  
Technical Innovations ◽  
Minimum System ◽  
Beijing Subway

This paper introduces two technical innovations in the signal demonstration project of Beijing Subway Yizhuang Line: the “free wave antenna + waveguide” combined transmission and the "minimum system" simulation. It also summaries the demonstration project management concepts and innovative practice experiences. Analyzing the technology and management innovation, we expect to provide a reference for the progress of the autonomy of the other rail transport high-end and core technology.

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