Research on Multi-Objective Real-Time Optimization of Automatic Train Operation (ATO) in Urban Rail Transit

2018 ◽  
Vol 23 (2) ◽  
pp. 327-335 ◽  
Author(s):  
Tong He ◽  
Ruiqi Xiong
Keyword(s):  
Real Time ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Multi Objective ◽  
Time Optimization ◽  
Urban Rail ◽  
Train Operation ◽  
Automatic Train Operation ◽  
Real Time Optimization

Research on Methods for Urban Rail Transit Train Operation Regulation

2014 ◽  
Vol 536-537 ◽  
pp. 820-823
Author(s):  
Chao Cai
Keyword(s):  
Mathematical Model ◽  
Urban Rail Transit ◽  
Traffic Density ◽  
Rail Transit ◽  
Key Technology ◽  
Rapid Construction ◽  
Urban Rail ◽  
Train Operation ◽  
Automatic Train Operation ◽  
High Traffic Density

Train operation regulation is the key technology to ensure the orderly operation of trains, its value has been fully realized under the background of rapid construction and high traffic density in urban rail transit. This paper did a deep analysis on different strategies and methods for urban rail transit train operation regulation and the applications of these strategies and methods in different conditions. Furthermore, an automatic train operation regulation mathematical model was established. Then developed a software system in Visual C++ and used it to analysis and test the model by data of a real metro line, the result showed that both the model and the system were available.

scholarly journals Research on Obstacle Detection Method of Urban Rail Transit Based on Multisensor Technology

2021 ◽  
Vol 1 (1) ◽  
pp. 61-67
Author(s):  
Tianwen Xiao ◽  
Yongneng Xu ◽  
Huimin Yu
Keyword(s):  
Real Time ◽  
Detection Method ◽  
Obstacle Detection ◽  
Response Mode ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Detection Accuracy ◽  
Position Information ◽  
Urban Rail ◽  
Train Operation

With the rapid development of urban rail transit, passenger traffic is increasing, and obstacle violations are more frequent, and the safety of train operation under high-density traffic conditions is becoming more and more thought-provoking. In order to monitor the train operating environment in real time, this paper first adopts multi-sensing technology based on machine vision and lidar, which is used to collect video images and ranging data of the track area in real time, and then it performs image preprocessing and division of regions of interest on the collected video. Then, the obstacles in the region of interest are detected to obtain the geometric characteristics and position information of the obstacles. Finally, according to the danger level of the obstacles, determine the degree of impact on train operation , the automatic response mode and manual response mode of the signal system are used to transmit the detection results to the corresponding train to control train operation. Through simulation analysis and experimental verification, the detection accuracy and control performance of the detection method are confirmed, which provides safety guarantee for the train operation.

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