scholarly journals Research and Application of Intelligent Monitoring System Platform for Safety Risk and Risk Investigation in Urban Rail Transit Engineering Construction

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yong Wu ◽  
Liang-Yun Zhao ◽  
Ye-Xiang Jiang ◽  
Wei Li ◽  
Ye-Sheng Wang ◽  
...  
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Dual Control ◽  
Intelligent Monitoring ◽  
Safety Risk ◽  
Engineering Construction ◽  
The Real ◽  
Urban Rail

In recent years, the construction scale of urban rail transit project is still in a high growth stage. In addition, the geology and surrounding environment of crossing lines are complex, and all kinds of safety accidents are still in a high incidence stage. Based on the investigation and summary of safety risk events and their causes in urban rail transit engineering construction at home and abroad, this paper fully combines the current national security management policies, introduces the “dual control” concept of safety risk classification and hidden danger investigation, and develops the intelligent monitoring system platform for urban rail transit engineering construction based on advanced technologies such as intelligent Internet of Things, 3D visualization, and artificial intelligence. It realizes the intelligent collection and analysis of engineering field monitoring data, the dynamic early warning management of engineering risk sources, the process embedding “dual control” mechanism of safety risk and hidden danger investigation, the real-time supervision of large equipment operations such as shield and hoisting, and the real-time control of high-risk operation sections such as contact channels. At the same time, the traceability and assessment management of the safety supervision process are strengthened. The parties involved in the project can realize the synchronous sharing of information through the platform and improve the efficiency of on-site safety and quality control.

scholarly journals Passengers Flow Forecasting Model of Urban Rail Transit Based on the Macro-Factors

2012 ◽  
Vol 6-7 ◽  
pp. 688-693 ◽  
Author(s):  
Bin Shang ◽  
Xiao Ning Zhang
Keyword(s):  
Real Data ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Estimation Model ◽  
Population Total ◽  
Transit System ◽  
The Real ◽  
Passenger Flow ◽  
Urban Rail ◽  
Multiple Variables

In China, many cities are planning urban rail transit system, but a comprehensive passenger flow estimation model is still lacking. The total passenger flow of urban rail transit in a city depends on many factors, such as urban population, total length of rail lines, gross domestic production of the city etc. To estimate the total passenger flow of urban rail transit, a linear regression model with multiple variables is established in the paper, based on the real data collected in many cities with urban rail transit operating. The comparison of the estimated flow and the real flow in many cities shows that the model is very accurate in passenger flow forecasting.

scholarly journals Coupling real-time simulation of power supply, trains and dispatching for urban rail transit

2021 ◽  
Author(s):  
Yu Zhang ◽  
Zhaoyang Zhang ◽  
Li'en Xu ◽  
Ting Ying ◽  
Jianghong Li ◽  
...  
Keyword(s):  
Real Time ◽  
Power Supply ◽  
Power Supply System ◽  
Supply System ◽  
Simulation System ◽  
Urban Rail Transit ◽  
System Structure ◽  
Rail Transit ◽  
Free Expansion ◽  
Urban Rail

Abstract In order to study the interaction among the traction power supply, the train group and the operation dispatching of urban rail transit, a coupling simulation system of power supply system, trains and dispatching management is constructed. In order to solve the problems of different timescales and difficult cooperation operation for related subsystems, a multi-bus distributed real-time network architecture based on hierarchical management of communication data is established, and simulation management software is developed to facilitate the free expansion of the simulation system. Meanwhile, the track line, train operation and other large timescale subsystems are realized by the pure digital simulation. And the time-sensitive subsystems, such as train traction system, braking system, auxiliary power supply system and network system etc., are built by the semi-physical simulation. In this article, the system structure and the main implementation principle of each simulation subsystem are given in detail, and the system is tested and verified at the end. The results show that the simulation system can meet the expected requirements.

scholarly journals Study on the Influence of Urban Rail Transit on the Value of Real Estate Based on Information System

2015 ◽  
Vol 9 (1) ◽  
pp. 73-80
Author(s):  
Jiao Lichao
Keyword(s):  
Information System ◽  
Real Estate ◽  
Real Estate Market ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Market Information ◽  
The Real ◽  
The Real Estate ◽  
Urban Rail ◽  
The Impact

Urban rail transit has strong transportation capability, but little environmental pollution. Besides, it also saves land resource. These advantages make the urban rail transit gradually becomes an effective measure to solve city traffic problems. In order to analyze the impact of the scope and extent of urban rail transit on the real estate, this paper first introduces the composition of real estate market information system, explains the process of how the urban rail transit influences the value of real estate by taking the 1st project of line 1 of Zhengzhou urban rail transit in Henan province for example, finds the semi logarithmic model which has the best regression effects with three hedonic price models and the collected data from the real estate market information system, and finally works out the added value of real estate generated by the above urban rail transit.

Mean-variance model for optimization of the timetable in urban rail transit systems

2017 ◽  
Vol 232 (4) ◽  
pp. 1005-1020
Author(s):  
Hui Yang ◽  
Xiang Li ◽  
Xin Yang
Keyword(s):  
Real Life ◽  
Urban Rail Transit ◽  
Data Driven ◽  
Rail Transit ◽  
Variance Model ◽  
The Real ◽  
Urban Rail ◽  
Mean Variance ◽  
Cooperative Scheduling ◽  
Operational Data

Regenerative braking is an energy-efficient technology that converts kinetic energy to electrical energy during braking phases. For more efficient recovered energy utilization, the stochastic cooperative scheduling approach has been proposed for determining the dwell times at stations, wherein the accelerating trains can use the energy recovered from the adjacent braking trains as much as possible. Here, running times at the sections are considered as random variables with given probability functions. In this paper, the authors develop a data-driven stochastic cooperative scheduling approach in which the real data of the speed of trains are recorded and used in the place of motion equations. First, the authors formulate a stochastic mean-variance model, which maximizes the expected utilization and minimizes the variance of the quantity of the recovered energy. Second, a genetic algorithm that utilizes particle swarm optimization has been designed to find the optimal dwell times at stations. Finally, numerical examples are presented based on the real-life operational data from Beijing Yizhuang urban rail transit line in China. The results illustrate that the real-life operational data in the data-driven stochastic cooperative scheduling approach can provide a more accurate description about the movement of trains, which would result in more efficient energy saving, i.e. by 1.66%, in comparison with the stochastic cooperative scheduling approach. Most importantly, the data-driven stochastic cooperative scheduling approach results in lower variance by 68.69% and higher robustness.

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