Improving Synchronization in High-Speed Railway and Air Intermodality: Integrated Train Timetable Rescheduling and Passenger Flow Forecasting

2022 ◽  
pp. 1-17
Author(s):  
Yuyan Tan ◽  
Yibo Li ◽  
Ruxin Wang ◽  
Xiwei Mi ◽  
Yaxuan Li ◽  
...  
Keyword(s):  
High Speed ◽  
High Speed Railway ◽  
Passenger Flow ◽  
Train Timetable

scholarly journals A Hybrid Temporal-Spatio Forecasting Approach for Passenger Flow Status in Chinese High-Speed Railway Transport Hub

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Zhengyu Xie ◽  
Limin Jia ◽  
Yong Qin ◽  
Li Wang
Keyword(s):  
High Speed ◽  
Rapid Development ◽  
Distribution Center ◽  
Railway Transport ◽  
High Speed Railway ◽  
Safety Hazard ◽  
Passenger Flow ◽  
Potential Safety ◽  
Correlation Degree ◽  
The Status

With the rapid development of high-speed railway in China, high-speed railway transport hub (HRTH) has become the high-density distribution center of passenger flow. In order to accurately detect potential safety hazard hidden in passenger flow, it is necessary to forecast the status of passenger flow. In this paper, we proposed a hybrid temporal-spatio forecasting approach to obtain the passenger flow status in HRTH. The approach combined temporal forecasting based on radial basis function neural network (RBF NN) and spatio forecasting based on spatial correlation degree. Computational experiments on actual passenger flow status from a specific bottleneck position and its correlation points in HRTH showed that the proposed approach is effective to forecast the passenger flow status with high precision.

scholarly journals Simultaneous Optimization of Train Timetabling and Platforming Problems for High-Speed Multiline Railway Network

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Qin Zhang ◽  
Xiaoning Zhu ◽  
Li Wang ◽  
Shuai Wang
Keyword(s):  
High Speed ◽  
Optimization Problems ◽  
Programming Model ◽  
Simultaneous Optimization ◽  
Resource Assignment ◽  
Railway Network ◽  
High Speed Railway ◽  
Train Timetabling ◽  
Train Timetable ◽  
Railway Operation

The optimization problems of train timetabling and platforming are two crucial problems in high-speed railway operation; these problems are typically considered sequentially and independently. With the construction of high-speed railways, an increasing number of interactions between trains on multiple lines have led to resource assignment difficulties at hub stations. To coordinate station resources for multiline train timetables, this study fully considered the resources of track segments, station throat areas, and platforms to design a three-part space-time (TPST) framework from a mesoscopic perspective to generate a train timetable and station track assignment simultaneously. A 0-1 integer programming model is proposed, whose objective is to minimize the total weighted train running costs. The construction of a set of incompatible vertexes and links facilitates the expression of difficult constraints. Finally, example results verify the validity and practicability of our proposed method, which can generate conflict-free train timetables with a station track allocation plan for multiple railway lines at the same time.

Key Issues on Train Line Planning for Beijing-Shanghai High Speed Railway

2010 ◽  
Author(s):  
L. Nie ◽  
D. B. Fei ◽  
S. D. Zhou ◽  
H. L. Fu ◽  
L. Tong
Keyword(s):  
High Frequency ◽  
High Speed ◽  
Travel Demand ◽  
Time Window ◽  
Long Distance ◽  
Line Planning ◽  
High Speed Railway ◽  
Passenger Flow ◽  
Train Operation ◽  
Service Plan

The Beijing-Shanghai High speed railway line (Hereinafter referred to as “Jing-Hu HSL”) is one of the most important railway lines in the Chinese rapid passenger transportation network and will be put into operation at the end of 2011. Train line planning directly reflects the quality and competition ability of train services. The characteristics of operational conditions and passenger flow of this corridor HSL bring about a few new issues on train line planning like night train operation, train OD sets, cyclic operation, and train stop schedule. For the first issue, a large amount of long distance travel demand put forward the demand for night services, which causes great conflict with the time-window for maintenance work. The confliction can be solved by harmoniously utilizing the parallel lines. For the second one, in view of the differences of technical and economic factors between HSL and conventional railways, high frequency and medium-long distance train will dominate HSL’s train service plan rather than low frequency and long distance trains on conventional railways. Thus, part of long-distance passenger flow has to transfer at some stations. Considering the whole possible ODs over Jing-Hu HSL and the transfer condition of related stations, the optimal OD sets and corresponding transfer plan is suggested. High frequency makes HSL possible to operate trains cyclically to improve service quality. However, with too many train ODs and some special trains, e.g. night train, an incomplete cyclic train operation mode is more practical. The ODs which can provide cyclic service for Jing-Hu HSL need to be identified. For the last issue, although non-stop long-distance train is a very popular kind of service in China, it should be reconsidered for Jing-Hu HSL line because of massive intercity travel demand and regular stops required. Each of the above issues is very complex. What is more, they have close relationship between each other. Due to limited space, the methods used to solve these issues are given in conceptual way rather than detailed description of mathematical model. The research paves the way for future integration study to design an efficient, economic, convenient, and regular train service plan for Jing-Hu HSL.

Short-Time Fluctuation Characteristic and Combined Forecasting of High-Speed Railway Passenger Flow Based on EEMD

2013 ◽  
Vol 409-410 ◽  
pp. 1071-1074
Author(s):  
Xiu Shan Jiang ◽  
Rui Feng Zhang ◽  
Liang Pan
Keyword(s):  
Support Vector Machine ◽  
Empirical Mode Decomposition ◽  
High Speed ◽  
Ensemble Empirical Mode Decomposition ◽  
Support Vector ◽  
High Speed Railway ◽  
Passenger Flow ◽  
Mode Decomposition ◽  
Railway Passenger ◽  
Short Term Forecasting

Take Wuhan-Guangzhou high-speed railway for example. By adopting the empirical mode decomposition (EMD) attempt to analyze mode from the perspective of volatility of high speed railway passenger flow fluctuation signal. Constructed the ensemble empirical mode decomposition-gray support vector machine (EEMD-GSVM) short-term forecasting model which fuse the gray generation and support vector machine with the ensemble empirical mode decomposition (EEMD). Finally, by the accuracy of predicted results, explains the EEMD-GSVM model has the better adaptability.

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