Development Of Urban Rail Transit Research Articles

Research on Vibration and Secondary Noise Characteristics of Sensitive Buildings Along Metro Lines Induced by Metro Operation

With the rapid development of urban rail transit, the environmental vibration and secondary noise induced by metro train operation have become increasingly serious, posing stricter requirements on the vibration and secondary noise of sensitive building office (SBO) and sensitive building school (SBS). To predict and control the vibrations and secondary noise in sensitive buildings along the metro line induced by metro train operations. A prediction method for the vibration and secondary noise of sensitive buildings along the metro line during metro train operation has been proposed. The sub-model of train-track system coupled dynamics and the sub-model of track-tunnel-soil-building system dynamics are included. The influence of metro train operation on the vibration and secondary noise of SBO and SBS is studied. The influence of the distance between the metro line and the building on the vibration and secondary noise of the sensitive building is discussed, and an effective control scheme of vibration and secondary noise is proposed. Results show that the vibration frequencies of the SBS and the SBO caused by the metro train operation are concentrated at about 8[Formula: see text]Hz and 63[Formula: see text]Hz. The vibration below the second floor of SBO caused by the metro train operation exceeds the limit, and the secondary noise below the third floor of SBS exceeds the limit. The secondary noise inside the building of each floor of SBO exceeded the limit. Using secondary noise to evaluate the environmental impact of metro train operations is more stringent than relying solely on vibration assessments. secondary noise is recommended in engineering to assess the impact of metro train operation on sensitive buildings along line. Combined with vibration, secondary noise and construction requirements, SBS and SBO are recommended to be no less than 72[Formula: see text]m and 74[Formula: see text]m away from the metro line, respectively.

Unveiling the evolution of urban rail transit network: considering ridership attributes

ABSTRACT Previous research on urban rail transit (URT) evolution mainly focused on network topology, neglecting ridership attributes. This study extracts ridership and network topology indicators from Chinese URT data. Employing a self-organizing mapping neural network model, it divides China’s URT development into four stages. The initial stage and the development stage form the framework of URT network. The network diameter reaches the maximum in the networked operation stage. In the mature stage, URT network densification occurs alongside a significant increase in resident ridership. It is also found that each network indicator has a significant nonlinear relationship with ridership attributes. These findings are of guiding significance for urban planners to accurately understanding URT’s future development and rational network planning and construction.

The Externality Impact of Urban Rail Transit on Urban Real Estate Prices in China

China has the largest and fastest growing urban rail transit system in the world. The system plays an important role in China's urbanization process, city governance and residents' daily commutes. The development of urban rail transit (URT) has influenced China's urban spatial structure and real estate supply, and has produced externalities on real estate value, including both positive and negative externalities. The research shows a positive correlation between URT and China’s real estate prices in general. The closer rail transit systems are, the greater the premium on real estate prices. In addition, the impact of rail transit on real estate prices shows a trend of first increasing and then decreasing. Different land use types and urban areas will also be affected. The research also found that the three stages of URT construction: planning, engineering construction and traffic operation have different effects on housing prices. At the same time, the impact of URT on land price will also change with China's economic situation and urbanization process. These influencing mechanisms above between URT and real estate prices may be linked to some factors. This research attempts to explain it by introducing urban spatial and land rent transformation, changes in real estate supply and demand, gentrification process, and different employment and housing pattern. This research points out the shortcomings and possible research directions of existing studies. In order to provide a reference for academic research and government policy making.

Prediction of short-term passenger flow of subway based on LSTM model

With the continuous development of urban rail transit, the subway is becoming the travel choice for more and more people. And the increase in travel demand also brings about the problem of subway congestion. This paper will use the subway card swipe data of Hangzhou City from January 1st to 20th, 2019, which were counted after data cleaning. With root mean square error (RMSE), mean absolute percentage error (MAPE), coefficient of determination (R^2), and loss values as standards, the long short-term memorys (LSTM) parameters were adjusted. The LSTM model is trained with time and passenger flow data, and the model is used to predict the short-term passenger flow in and out of subway stations. From the prediction results, the LSTM model has a good adaptability to the subway station short-term passenger flow. The trend of the predicted line is the same as the real value, and the difference is also controllable. The short-term passenger flow prediction of subway stations is beneficial to reduce the loss caused by congestion and improve the travel efficiency of residents.

Parameter inversion analysis of rubber-mortar cohesive zone model in rubberized concrete

The rapid development of urban rail transit has brought convenience to travel, but also causes serious environmental vibration problems. Some scholars have proposed rubberized concrete invert-filling as a damping measure. The addition of rubber particles creates the rubber-mortar interface, which is an important factor that affects the damping performance of rubberized concrete. In this study, we propose an interface modification method of coating rubber with zinc stearate powder to improve the damping performance of rubberized concrete. The stiffness, strength, and fracture energy of the rubber-mortar interface were obtained by an inversion analysis technique based on numerical simulation and experimental results. The results show that: (1) The uniaxial tensile test determined the bonding strength of the rubber-mortar interface treated with water, sodium hydroxide, and zinc stearate as 0.144 MPa, 0.160 MPa, and 0.074 MPa, respectively. (2) Based on numerical simulations and experimental results, the bonding strength of the rubber-mortar interface treated by three methods was 0.142 MPa, 0.146 MPa, and 0.080 MPa, respectively, with relative errors of less than 10 %. (3) Compared with the interface obtained by water treatment, the interface modified by zinc stearate showed a 43.7 % reduction in bonding strength and a 46.0 % reduction in fracture energy.

Research on short-term passenger flow prediction method of urban railway based on machine learning

With the development of urban rail transit, the improvement of communication transmission technology, and big data processing level, the passenger flow data of urban rail transit continues to grow and can be effectively collected and stored, providing many basic data resources for analysis and passenger prediction research. With the development of artificial intelligence, short-term passenger flow prediction based on machine learning has received widespread attention. For this reason, based on the passenger flow data of Seoul Metro, this paper has carried out experiments and analysis on the existing models RNN-LSTM and ConvLSTM with better performance, providing theoretical support for short-term passenger flow prediction. The method in this paper solves the problem that a single traditional prediction model based on statistical theory is difficult to deal with large-scale complex data. It can complete the data processing task more accurately and efficiently, and has a good application prospect.

Stability Analysis and Safety Factors of the Excavation Face of a Pipe Screen Tunnel in a Soft Soil Area

With the rapid development of urban rail transit and underground space construction, the advantages of the concealed excavation method are gradually highlighted in the urban center area affected by a complex engineering environment. At present, the pipe curtain method with a flexible section and wide application of the soil layer is being widely used in engineering, but the research on the stability of the excavation face during the construction of the pipe curtain method in soft soil areas still has not formed a complete system. Therefore, this paper analyzes the stability of the excavation face under different reinforcement conditions and the influence of different spacing, numbers, and strength of MJS (metro jet system) zones on the stability of the excavation face of the pipe curtain method based on the actual project of the Guiqiao Road Station of the Shanghai Metro, China, and gives a reference for the reinforcement of the palm face in the excavation process of the pipe curtain method in soft soil areas. The study shows that the safety coefficient of the excavation face decreases with the increase in the slope angle of the excavation face, with the increase in spacing of the MJS zone, and with the increase in height of the MJS zone arrangement, while the safety coefficient of the excavation face increases with the increase in strength of the MJS zones themselves and the increase in the strength of the soil between the MJS zones. Further, the machine learning model is applied to predict the stability of the excavation face under different cases, and the relevant fitting accuracy is above 0.9, which can predict the stability of the excavation better.

Fault detection system of subway sliding plug door based on adaptive EMD method

With the rapid development of urban rail transit, the safety of subway sliding plug doors has become a great concern. To improve the operational reliability of the sliding plug door, we developed a fault detection system based on the adaptive empirical mode decomposition (AEMD). Firstly, we designed a hardware acquisition device and analysis software to collect motor current signal data during the opening and closing of the sliding plug door. Secondly, to address the impact of noise on signal analysis, the AEMD denoising method is proposed. This method employs EMD to obtain intrinsic mode functions (IMFs), and select the appropriate IMF components for reconstruction based on the adaptive threshold of Hausdorff distance, resulting in improved denoising effectiveness. Thirdly, waveform segments of different faults are sliced to reduce the amount of computation and effectively improve recognition accuracy. Meanwhile, this paper utilizes feature selection methods and machine learning techniques to classify the 12 subway sliding plug door faults. It is worth noting that most of these faults have not been extensively studied in previous classification research. The experimental results show that the identification accuracy reaches 98.96% on the practical platform. Moreover, the effectiveness and robustness of our proposed method are further validated through practical tests, ablation experiments, and comparisons with other relevant literature.

Multi-objective optimization for the daylighting and thermal comfort performance of elevated subway station buildings in cold climate zone of China

The rapid development of urban rail transit brings about the rapid growth of elevated subway station buildings, while the demand for comfortable waiting environments on the passenger platforms is also increasing. Due to the fact that elevated stations generally have a transparent envelope, there is a contradiction between daylighting, heating, and air conditioning. Therefore, multi-objective optimization design is essential. This article selects the cold regions of northern China as the research object. A field investigation was carried out, and Tianjin University Town Station was found to be a typical station in cold climate zone of China. A prototypical model was built based on it using Grasshopper in Rhino. Sensitivity analysis was used to screen key independent variables, and strength Pareto evolutionary algorithm II was used to optimize the daylighting and thermal comfort performance for the elevated subway station buildings. Two optimization processes, step-by-step and one-step, were used to obtain the non-dominated solution set, and the optimal solution was obtained by technique for order preference by similarity to an ideal solution analysis. The suggested values for the design variables of the prototypical model are also displayed. Reducing the skylight's window-to-wall ratio helps improve daylighting and thermal comfort. Besides, the one-step optimization method has higher efficiency and can obtain better results. The findings proposed here can guide the development of elevated subway station buildings in north China and other areas with similar conditions.

A Dynamic Addressing Hybrid Routing Mechanism Based on Static Configuration in Urban Rail Transit Ad Hoc Network

With the rapid development of urban rail transit, the traditional urban rail wireless network based on fixed infrastructure is not in a position to meet the increasingly complex communication demand. At the same time, Ad Hoc network, as a special wireless mobile network, is developing rapidly. Applying this self-organized networking architecture to the urban rail vehicle–ground communication network can overcome the problems existing in the traditional urban rail communication system. The routing protocols that can achieve low delay and highly reliable data transmission are important in the urban rail transit scenario. Therefore, combined with the wireless Ad Hoc network and the characteristics of the urban rail transit scenario, this paper proposes a dynamic addressing hybrid routing mechanism based on static configuration. Using an improved AODV routing discovery algorithm and then writing the routing table into the router in advance for static configuration not only reduces network overhead but also prolongs the network’s lifetime. It also saves the delay of routing discovery. Then, the cluster head node dynamically monitors the link status, dynamically finds the path when the link needs to be replaced, and selects different update paths according to different types of communication services. Finally, each algorithm’s network performance parameters, like the routing discovery overhead, residual link lifetime, packet delivery rate, throughput, and end-to-end delay, are analyzed and compared.

Elements of the core area transport system oriented to station–city integration

Currently, China's urban rail transit construction projects are faced with several challenges including inconsistent planning and execution, lack of alignment with urban development, overly protracted timelines for some projects, sub-optimal land utilization rates, and significant wastage of precious urban resources. To mitigate these issues, it is essential to enhance land utilization around stations, implement scientific planning, and adopt intelligent management for underground space development. Moreover, all parties involved in construction must adhere strictly to planning guidelines during project execution. This study investigates the integrated development strategy of urban rail transit stations and their correlating cities, with the primary objective of enhancing the land utilization of stations and their surrounding areas. This involves fortifying the functionality of transportation, commerce, offices, residences, entertainment, and leisure in these areas, thereby catering to the varying needs of residents for travel, work, or entertainment activities. This type of an approach is anticipated to ease the pressure on urban road traffic, stimulate the economic growth of the stations and the areas along the routes, decrease environmental pollution, conserve urban space resources, and address issues associated with urban rail transit development. The insights gained from this research offer a valuable reference for future rail transit construction endeavors, carrying substantial practical significance.

Response Monitoring and Analysis in Deep Foundation Pit Excavation: A Case Study in Soft Soil at Subway Tunnel Intersections

With the rapid development of urban rail transit and underground space development, the occurrence of excavation near existing tunnels is becoming more common. This excavation and unloading will inevitably cause soil deformation outside the pit and the tunnel buried therein. This paper presents an investigation into the entire excavation process and the deformation effects on the adjacent subway structure under complex construction environments, including soft soil foundations and adjacent subway intersections, based on measured data of pit construction. The horizontal and vertical displacements of deep soils in two pits were analyzed along with safety management measures to determine the horizontal displacement curve pattern and the lateral displacement development distribution law of deep soils. The analysis of subway deformation data shows that after excavation, the subway tunnel undergoes “lateral expansion” and “vertical compression” type deformation, accompanied by “in-pit” horizontal displacement and “settlement” vertical displacement. Furthermore, a correlation analysis reveals a clear linear relationship between pit deformation and subway structure deformation, which can be used as a prediction method for adjacent structure deformation. Finally, a comparative analysis of existing relevant influence zone models and tunnel deformation prediction formulas is carried out based on the monitoring. The results of this study have significant guiding implications for the excavation construction of soft soil foundations in the vicinity of subway crossings.

Stability Analysis of the Foundation Pit and the Twin Shield Tunnels during Adjacent Construction

Due to the rapid development of urban rail transit and the development and use of underground space, foundation pit construction near existing subway tunnels is becoming increasingly common. When adjacent foundation pit projects are being constructed, it is difficult to avoid the influence on existing subway tunnels, which threatens the safe operation of subway tunnels. Thus, this study focused on the stability of the adjacent construction of foundation pits and twin shield tunnels. The finite element limit analysis (FELA) method was used to analyze the influences of construction scheme and relative position of the twin shield tunnels and adjacent foundation pit on the global stability of adjacent construction. Based on the research results, the guidance and design for the construction scheme and relative position are provided. The stability analysis on the foundation pit during the construction process is performed. The criteria of adjacent influential partition are proposed, and the influence of various input parameters (c/γD, φ, L/D and C/D) on the global stability of adjacent construction is discussed, respectively. A new design equation of safety factor of global stability of adjacent construction is obtained by curve fitting.

Metro Electric Traction Load Forecasting Based on Prophet-GRU Hybrid Model

In order to further improve the metro electric traction load forecasting and provide support for energy conservation and sustainable development of urban rail transit. In this paper, a Prophet-GRU hybrid model based on weight selection is proposed. This model combines the advantages of Prophet and GRU, takes account of timing characteristics and influence factors synthetically, and improves the accuracy of electric traction load prediction. This paper first introduces the background of electric metro traction load and the model used in this paper and then proposes electric traction load forecasting based on the Prophet-GRU hybrid model. Taking a subway line as an example, firstly, the Prophet and GRU are used for prediction respectively, and then the error reciprocal method is used to combine the two models to obtain the final forecasting result. Compared with the single Prophet and GRU, it is verified that the model has a higher precision forecasting ability.

Study on Vibration Propagation Characteristics Caused by Segments Joints in Shield Tunnel

In recent years, with the development of urban rail transit, more and more attention has been paid to the vibration problems caused by its operation. As the main form of urban rail transit’s underground construction, the shield tunnel is the first to bear the brunt. However, the existing researches on the vibration of shield tunnel usually take it as a homogeneous barrel and do not consider the impact of its assembly joints on the vibration propagation. In this paper, to study the influence of the joints caused by the shield tunnel’s assembly forms on the propagation of vibration, two finite element models of shield tunnels with different assembly forms are established. The analysis and comparing results of these models show that the joints caused by segment assembly of shield tunnel have obvious hysteresis and reduction effect on the vibration waves and this ability is obviously related to its location. In addition, the ability to weaken the vibration wave is also related to the frequency of the vibration wave.

Analysis of the Impacts of Passenger Demand on the Profitability of Different Types of Urban Rail Transit

With the rapid development of urban rail transit (URT) in China, a contradiction between high costs and low passenger demand becomes prominent. Complete analysis of the impacts of passenger demand on the profitability of URT can be difficult to conduct, due to the multifaceted impact of passenger demand with multidimensional characteristics. To this end, we propose a strategy that helps to analyse the profitability of different types of URT, taking into account the spatial and temporal characteristics of demand. Based on data of the Shunde (SD) district in China, the profitability of metro, light rail transit (LRT), monorail and tram was evaluated. Results show the profitability under different demand levels. Tram might be the best choice at low demand levels. At medium demand levels, LRT and monorail are competitive. At high demand levels, LRT with medium to high capacity and low cost is a good alternative to metro, though the capacity of metro is higher. Utilizing the URT with high capacity under insufficient demand can aggravate the burden of depreciation, and make it hard to achieve profit. The spatial characteristics of the demand described in this paper reflect the problem of insufficient demand in marginal areas due to the diversified construction of URT.

Simulation-Based Optimization of Transport Efficiency of an Urban Rail Transit Network

It has been proven that developing urban rail transit (URT) is the key to solving the traffic problems in big cities, and transport efficiency is essential for scientific line planning and construction, operation management and sustainable development of urban rail transit. This paper focuses on the transport efficiency of the URT network and adopts shadow efficiency theory creatively to combine factors of passengers, capacity, and efficiency effectively. A quantitative calculation method of system utility based on “double time penalty” is proposed. According to the characteristics of Beijing URT, this paper puts forward a single optimization strategy and combinatorial optimization strategy and analyzes the results with DEA. The simulation of Beijing subway network proves the availability of the method and its optimization effects.

Energy-Saving Train Operation Synergy Based on Multi-Agent Deep Reinforcement Learning on Spark Cloud

With the development of urban rail transit, energy conservation has been highly concerned by the worldwide railway industry. The existing energy-saving control methods are hard to meet the requirements of large-scale multi-train intelligent cooperation. Furthermore, in order to optimize the overall energy consumption and make effective utilization of regenerative braking energy (RBE), the micro train driving strategies must be taken into account in the macro train schedule regulation. This article aims to establish a systematic optimization model to describe the train traffic environment and design a deep reinforcement learning (DRL) approach using multi-agent cooperative actor-critic (MACAC) to reschedule multiple trains for energy saving. Due to the high dimensional characteristic of control actions, the action representation technique is applied for generalization. The multiple agents are deployed on the Spark cloud platform to effectively improve the learning efficiency through multi-node parallel computing. The proposed MACAC approach on Spark cloud is capable of dealing with the intelligent learning and computing efficiency of large-scale train operation synergy, and saving energy to the maximum extent on the premise of satisfying various time constraints. The evaluation was carried out through the field data of Beijing Yizhuang subway line. The results show that the proposed MACAC approach can effectively learn to improve the energy efficiency, and the parallel computing method on Spark cloud is suitable for practical applications.

Integrated Development of Urban Rail Transit and Energy Systems Supported by Underground Space

Integrated Development of Urban Rail Transit and Energy Systems Supported by Underground Space

Fatigue Strength Assessment of an Aluminium Alloy Car Body Using Multiaxial Criteria and Cumulative Fatigue Damage Theory

With the rapid development of urban rail transit, metro vehicles have become preferred choices for urban transportation. It is important to accurately evaluate the fatigue strength of a car body to ensure subway safety. A new method based on multiaxial stress criteria and cumulative fatigue damage theory was proposed for the fatigue strength assessment of welded joints of an aluminium alloy head car body subjected to variable cyclic loads. A local coordinate system was established, according to the geometrical characteristics of the weld. Local stresses perpendicular and parallel to the weld seam were obtained to calculate the stress ratio, stress range, and allowable stress value corresponding to the stress component. Then, the fatigue strength utilization of the joints was estimated to determine whether the fatigue strength of the weld met the design requirements. Moreover, the estimated fatigue life of the car body was predicted with cumulative fatigue damage theory. This method considers both the material utilization degree in multiple stress states and the estimated body fatigue life of the car body. The research results provide a reference and a more comprehensive guarantee for the fatigue strength evaluation of a subway car body’s welded structure to ensure vehicle safety.