Rail Transit Line Research Articles

Secure virtual coupling control of connected train platoons under cyber attacks

Virtual coupling of automated trains has emerged as a promising technology to enhance the operational efficiency and line capacity of railway transportation systems. However, the vulnerability of such systems to malicious cyber attacks poses a significant threat to their stability, reliability and applicability. This article addresses the challenge of ensuring secure virtual coupling control of connected train platoons subject to various cyber attacks, including false data injection attacks, denial-of-service attacks, and replay attacks. First, based on the low-dimensional and noisy sensor measurements, novel set-valued observers are designed for each follower train to estimate their inaccessible full longitudinal motion states despite uncertainties and unknown attacks and noises. Then, distributed secure attack-compensation-based virtual coupling control laws are developed to ensure the platoon's stability and resilience against cyber attacks. Additionally, formal stability analysis of the resultant estimation error system and platoon tracking error system is provided. Furthermore, two algorithms are presented to elaborate the offline observer and controller design process as well as their online implementation. Finally, based on the data of a realistic urban rail transit line, simulation experiments are conducted to validate the efficacy of the proposed theoretical findings.

Performance of an operational shield tunnel due to construction of a large cross-sectional straight-walled arch tunnel above-crossing

Innovative strategies for managing deformation have been proposed based on insights from the Hohhot Urban Rail Transit's Line 2, where a large cross-sectional and straight-walled arch tunnel traverses the flank obliquely above and directly over an operational shield tunnel. These strategies involve implementing sandbag loading on both left and right drifts and progressively demolishing the CD (center diaphragm) method. Simulations have been conducted to comprehensively understand the deformation induced by constructing the large cross-sectional and straight-walled arch tunnel above the operational shield tunnel. These simulations have been complemented by on-site monitoring to authenticate the reliability of the simulated outcomes. The study findings underscore that the most effective deformation control entails applying a 2.0 m high sandbag load on the section directly above the operational left shield tunnel (spanning from trusses 49 th to 87th). This approach involves, for every alternate truss, the demolition of two consecutive trusses of CDs via an alternate bay construction method once the secondary lining is completed. The comparison between simulated and measured uplift reveals a notable alignment, with maximum uplift of the ballast bed and arch crown registering at 2.75 mm and 3.92 mm, respectively. The overall clearance convergence ranges from −2.69 mm to 1.50 mm, all within the prescribed control standards.

The Noise Exposure of Urban Rail Transit Drivers: Hazard Classification, Assessment, and Mitigation Strategies

Prolonged exposure to high-intensity noise environments in urban rail transit systems can negatively impact the health and work efficiency of drivers. However, there is a lack of comprehensive understanding of the noise pattern and, therefore, effective mitigation strategies. To control the noise in urban rail transit systems, this study proposes a comprehensive noise assessment framework, including metrics such as average sound pressure level, peak sound pressure level, percentile sound pressure levels, dynamic range, main frequency component, and cumulative time energy to evaluate the noise characteristics. We also employ a density-based spatial clustering of applications with noise (DBSCAN) method to identify the noise patterns with the evaluation of their hazard to urban rail transit drivers. The results have revealed that: (1) The equivalent continuous sound pressure level (Leq) in the cab of Lanzhou Urban Rail Transit Line 1 averages 87.12 dB, with a standard deviation of 8.52 dB, which reveals a high noise intensity with substantial fluctuations. (2) Ten noise patterns were identified, with frequencies varying from 14.47 Hz to 69.70 Hz and Leq varying from 60 dB to 115 dB. (3) The major noise sources from these patterns are inferred to be the train’s mechanical systems, wheel–rail interaction, aerodynamic effects, and braking systems. Combined with the noise patterns and urban rail transit’s operation environment, this study proposes tailored mitigation strategies for applications aimed at protecting drivers’ hearing health, enhancing work efficiency, and ensuring driving safety.

Study on the Reuse of Shield Mud from Clay Stratum in Synchronous Grouting Slurry

The purpose of this study is to investigate the feasibility of replacing the fly ash in synchronous grouting material by reusing the shield mud produced in the clay stratum during the shield construction of Wuhan Rail Transit Line 11. The test utilizes the shield mud from the clay stratum to replace the fly ash material in synchronous grouting at percentages of 20%, 40%, 60%, 80%, and 100%, and research and analyses are conducted on the fluidity, stability, strength, and resistance to water dispersion of the slurry after the replacement; at the same time, improvements in the undesirable phenomenon produced by the synchronous grouting slurry are also examined after the replacement. The results show that, when the fly ash is replaced by shield mud at 80%, the mortar still has good stability and strength performance, but, at the same time, the initial value of consistency and the phenomenon of flow time loss is too large. Through the adjustment of the water–binder ratio and the addition of an appropriate amount of a polycarboxylate superplasticizer agent, the adverse phenomenon of the slurry is effectively improved, and the compressive strength and ease of the slurry are also improved. At the same time, when adding an appropriate amount of hydroxyethyl methyl cellulose (HEMC), the slurry has good water dispersion resistance, but, with the gradual increase in HEMC, the fluidity of the slurry deteriorates and the compressive strength decreases. The test proves that the shield mud in the clay stratum can be used to replace most of the fly ash in an appropriate proportion, which not only solves the problem of the shield mud being difficult to work with, but also provides more valuable insights for tunneling projects.

Sustainable Transportation: Exploring the Node Importance Evolution of Rail Transit Networks during Peak Hours

The scientific and rational assessment of the evolution of node importance in rail transit line networks is important for the sustainability of transportation systems. Based on the complex network theory, this study develops a weighted network model using the Space L method. It first considers the network topology, the mutual influence of neighboring nodes of the transportation system, and the land use intensity in the station influence domain to construct a comprehensive index evaluation system of node importance. It then uses the covariance-weighted principal component analysis algorithm to more comprehensively evaluate the node importance evolution mechanism and analyzes the similarity and difference of the sorting set by adopting three different methods. The interaction mechanism between the distribution of important nodes and the evolution of land use intensity is explored in detail based on the fractal dimension theory. The Xi’an rail transit network is considered an example of qualitative and quantitative analysis. The obtained results show that the importance of nodes varies at different times of the day and the complexity of the morning peak is more prominent. Over time, articulated fragments with significance values greater than 0.5 are formed around the station, which are aligned with the direction of urban development, creating a sustainable mechanism of interaction. As the network’s crucial nodes in the center of gravity increase and the southern network expands, along with the increased intensity of the city’s land utilization, the degree of alignment in evolution becomes increasingly substantial. Different strategies for attaching the network, organized based on the size of Si can lead to the rapid damage of the network (reducing it to 0.2). The identification of crucial nodes highlighted in this paper serves as an effective representation of the functional characteristics of the nodes in transportation networks. The results obtained can provide a reference for the operation and management of metro systems and further promote the sustainable development of transportation networks.

LiDAR-Based Urban Three-Dimensional Rail Area Extraction for Improved Train Collision Warnings.

The intrusion of objects into track areas is a significant issue affecting the safety of urban rail transit systems. In recent years, obstacle detection technology based on LiDAR has been developed to identify potential issues, in which accurately extracting the track area is critical for segmentation and collision avoidance. However, because of the sparsity limitations inherent in LiDAR data, existing methods can only segment track regions over short distances, which are often insufficient given the speed and braking distance of urban rail trains. As such, a new approach is developed in this study to indirectly extract track areas by detecting references parallel to the rails (e.g., tunnel walls, protective walls, and sound barriers). Reference point selection and curve fitting are then applied to generate a reference curve on either side of the track. A centerline is then extrapolated from the two curves and expanded to produce a 2D track area with the given size specifications. Finally, the 3D track area is acquired by detecting the ground and removing points that are either too high or too low. The proposed technique was evaluated using a variety of scenes, including tunnels, elevated sections, and level urban rail transit lines. The results showed this method could successfully extract track regions from LiDAR data over significantly longer distances than conventional algorithms.

Predicting transit ridership using an agent-based modeling approach

Accurate ridership estimation is pivotal in the advancement of sustainable transit systems, be it for proposed or existing transit networks. A multitude of methods, including travel demand models, direct ridership models, and regression models, have been employed by practitioners and researchers to estimate ridership at both station and network levels. However, travel demand models, frequently utilized for new transit lines, exhibit intrinsic limitations due to their aggregate nature and complexity based on their types. Researchers have also identified deficiencies, such as the incapacity to capture small spatial resolutions and specific station characteristics, as these models are predominantly designed for large-scale analyses.This study aims to overcome these limitations by introducing a novel approach that utilizes three microscopic agent-based models to develop a travel demand modeling suite, providing a policy-sensitive forecasting tool. The suite comprises three agent-based models: SILO-MITO-MATSim. Validation of the model against previous year data is conducted, and projections are made for future years. The model is applied to estimate network-level ridership for the proposed ‘Purple Line,’ a light rail transit line planned by MDOT, MTA, Maryland, which will integrate with the Washington D.C. Metro, the fourth largest transit system in the USA, boasting an average daily ridership of half a million. The study’s findings indicate an anticipated ridership of approximately 31,230 passengers in the inaugural year of 2027. The proposed model offers a robust and policy-sensitive solution empowering decision-makers to make informed choices to support a sustainable transportation system.

A Cost-Effective Approach for the Integrated Optimization of Line Planning and Timetabling in an Urban Rail Transit Line

A Cost-Effective Approach for the Integrated Optimization of Line Planning and Timetabling in an Urban Rail Transit Line

Deterministic Localization for Fully Automatic Operation: A Survey and Experiments.

With the rapid development of fully automatic operation (FAO) and location-based services, the evaluation criteria of average localization accuracy can no longer meet our demands, in favor of deterministic localization. However, most localization researches modeled localization performance function and enhanced it by minimizing average localization root mean square error (RMSE). The performance degradation in a small region was not considered. In this paper, we present a survey of deterministic localization and analyze the relationship between accuracy and certainty. In this paper, two common solutions of localization enhancement are presented and their localization certainties are discussed. Furthermore, we carry out related localization enhancement experiments in rail transit line and analyze their improvement on deterministic localization. The experimental results show that the overall localization performance is improved, while the deterministic localization requires the stricter solution to promote.

Numerical Simulation Study on the Impact of Deep Foundation Pit Excavation on Adjacent Rail Transit Structures—A Case Study

Excavation in foundation pits can result in serious issues for nearby tunnel structures like deformation, differential settlement, and seepage damage, which profoundly impact project timelines and potentially endanger life and property safety. Therefore, it is imperative to investigate these impacts before and after construction and to facilitate timely adjustments of construction measures and reinforcement where possible. In this study, a foundation pit construction project near a rail transit line is employed as a case to comprehensive study the impact of on-site deep foundation pit excavation on adjacent rail transit structures by numerical simulation. A three-dimensional finite-element model of the foundation pit based on site geological characteristics and construction procedures is established to study the excavation and maintenance processes. Through analysis of key parameters including soil deformation, displacement, shear force, and bending moment of the tunnel structures, the designed protective structure is found to have effectively mitigated soil deformation, ensuring the stability of the foundation pit. As excavation progresses, lateral soil deformation and vertical uplift gradually increase but remain within specified control values. During various excavation stages, the maximum displacement of the tunnel structure gradually increases, with the increase rates of maximum settlement being 29.09%, 20.51%, and 6.45%, respectively. This indicates a gradual enhancement of the stability of the tunnel structure. Additionally, excavation of the foundation pit has a significant impact on the bending moment distribution of the tunnel structure but does not affect the axial force and shear force of the tunnel structure. The findings of this study offer crucial scientific insights for evaluating the safety and stability of construction near tunnel structures.

Joint optimization of train timetable and passing facility: A capacity allocation strategy

To addreess the challenge of overcrowding in the urban rail transit system, this paper proposes a novel joint optimization strategy that optimizes the timetable and the passing facility’s working status (PFWS) simultaneously according to the passenger demands. To this end, a mixed-integer nonlinear programming (MINLP) model is formulated to jointly minimize overcrowding on trains and platforms, as well as the passenger travel time. The passing facility setting and the passenger flow activities depiction are particularly taken into account by the rigorous constraints. Subsequently, we design a simulation-based hybrid variable neighborhood search (SHVNS) algorithm to efficiently generate near-optimal solution. This algorithm incorporates a variable neighborhood search (VNS) algorithm, a randomly reset strategy, and a simulation-based algorithm. The VNS algorithm includes five neighborhood operators to enhance search efficiency. Finally, various experiments with the real-world data from Chongqing rail transit line 6 in China are tested to prove the applicability and the performance of our proposed model and algorithm. The computational results show that the joint optimization strategy outperforms a current operation strategy in terms of the overcrowded situation on trains and platforms, often by more than 60%, and some management implications and theoretical support can be obtained for the urban rail transit operator.

The HWAM-EMD-GRU Forecasting Model for Short-Term Passenger Flow in an Airport Light Rail Transit Line

Accurate forecasting of airport light rail transit line (ALRTL) outbound passenger flow is critical to the optimal operations of both light rail and airport systems. Considering the nonlinearity, non-stationarity, uncertainty, and periodicity of outbound passenger flow in the ALRTL, we propose a combined forecasting model that integrates the Holt and Winters additive model (HWAM), empirical mode decomposition (EMD) and gated recurrent unit (GRU). Firstly, the edge effect of EMD will greatly affect the performance of the forecasting model. To overcome this, we extend the passenger flow by HWAM. After that, the decomposition method, EMD, can be applied to passenger flow, and several intrinsic mode function (IMF) components can be extracted. After extracting all the IMFs, the remaining part is referred to as the residual (Res) component. Then, a correlation test is performed on all the components, followed by their aggregation. Finally, the GRU is used to predict each of the aggregated components, and the prediction of aggregated components requires reconstruction. To verify the performance of the HWAM-EMD-GRU, we conducted a comparative study on the hourly passenger flow data for Beijing Daxing International Airport Express and set the autoregressive integrated moving average model, HWAM, Prophet, and GRU as the baseline. Predictions of the HWAM-EMD-GRU combined model demonstrated higher accuracy than baseline models, with a root mean square error of 83.52 (Prophet is 110.21) and mean absolute percentage error of 8.32% (Prophet is 12.48 %). The experimental result shows that the HWAM-EMD-GRU forecasting model offers more accurate predictions.

Metro Train Stopping Scheme Decision Based on Multisource Data in Express-Local Train Mode

Metro Train Stopping Scheme Decision Based on Multisource Data in Express-Local Train Mode

Numerical Analysis of the Influence of Tunnel Undercrossing Buildings on Pile Foundation

The construction of subways inevitably involves underpass buildings. To ensure the stability of buildings, taking the undercrossing buildings by the Chongqing Rail Transit Line 5 branch as an example. A three-dimensional numerical model of the pile foundation and tunnel was established using FLAC3D. The simulation results show: In the 1-1 profile, the maximum displacement is about 2.28 mm, and the displacement gradually decreases along the top of the tunnel. The maximum displacement in the profile is about 2.28 mm, and the displacement at the bottom of the pile foundation is about 0.3 mm.In the 2-2 profile, the maximum displacement is about 2.27 mm. At the building's pile foundation, the displacement is about 0.2 mm, and at the bottom of the pile foundation, the displacement is about 0.3 mm.In the 3-3 profile, the maximum displacement is 2.26 mm, located at the crown of the tunnel. The displacement at the building's pile foundation is less than 0.2 mm. Based on the analysis of the data from the FLAC3D three-dimensional numerical simulation results, The excavation of the tunnel has a minimal impact on the pile foundations of the aforementioned buildings, and the safety and stability of the buildings are not affected.

Towards a collective opinion generation approach with multiple objectives for evaluating rail transit station accessibility in urban areas

Urban rail transit can alleviate traffic congestion if sufficient ridership is achieved. The accessibility to rail transit stations largely determines public willingness to utilize urban rail transit. The current studies on the accessibility to rail transit stations tend to concentrate solely on individual rail transit lines or stations, neglecting the impact of the external macro-environment. Consequently, the outcomes of these measurements cannot accurately reflect the overall accessibility level of the region, nor do they furnish decision-makers with references for devising plans for rail transit development. This study introduces a novel approach for evaluating the accessibility to urban rail transit stations from a macro-level standpoint, utilizing expert knowledge. The present study conducts an analysis of the impact of political, economic, social, and technological factors on the accessibility to rail transit stations in urban areas. Subsequently, a comprehensive evaluation indicator system is developed based on the aforementioned analysis. Then, experts are summoned to provide their subjective evaluations for every indicator, which are depicted as probability distribution functions. The collective evaluation is derived through the aggregation of individual evaluations utilizing a bi-objective optimization approach that factors in both the collective fairness utility and the confidence level. Finally, the quantile average method is employed to consolidate the collective assessment outcomes of individual indicators, thereby deriving the level of accessibility to rail transit stations in urban areas. We design a small-scale application experiment and attempt to evaluate the accessibility to rail transit stations in Wuchang District, Wuhan with the proposed approach in order to demonstrate the feasibility of the approach.

Collaborative optimization of passenger flow control and bus-bridging services in commuting metro lines

With the advantages of high speed and punctuality, urban rail transit has become the preferred choice for many commuters. However, overcrowding of urban rail transit lines during peak hours is a common problem in megacities owing to the excessive passenger demand. To address this problem, this study proposes an integrated optimization method that combines passenger flow control and bus-bridging services. An integer nonlinear optimization model is developed to minimize the weighted passenger waiting time and operating cost of bus-bridging services by considering the coupling relationships between passenger movements on both the metro and buses. Then, the proposed model is equivalently transformed into a linear form with better mathematical properties, and variants of this model are further formulated to extend the usability. Finally, real-world case studies based on the operational data of the Beijing Metro Batong line are conducted to verify the effectiveness of the proposed methods. The computational results indicate that the proposed approach can effectively alleviate overcrowding and reduce passengers' waiting time, thereby improving the operational efficiency and safety of the urban rail transit system.

A method for monitoring the uneven settlement of shield tunnels considering the flattening effect using distributed strain data measured from BOTDA sensors

When investigating the uneven settlement monitoring of shield tunnels, the influence of the flattening effect under longitudinal bending is rarely considered, which leads to inaccurate and incomplete settlement monitoring. To address this issue, a method for monitoring the uneven settlement of shield tunnels that considers the flattening effect is proposed, which is achieved using high-density strain data from distributed Brillouin optical time domain analysis (BOTDA) sensors. The high-density measured strain data is used to combine global settlement with the additional influence of the flattening effect, which includes extrusion and shear effects. This approach allows the trend of uneven settlement to be effectively monitored. Furthermore, a finite element model updating process is implemented in advance to improve the accuracy of soil parameters and minimize calculation errors in practical engineering. To demonstrate the effectiveness of the proposed method, an application example from the Jinan Rail Transit Line 3 was utilized for numerical simulations and practical tests. The results of the application example reveal that the proposed method has a high accuracy, with measurements comparable to the total station-based method. This indicates that the proposed method is an effective and robust settlement monitoring approach and provides a referential basis for further tunnel operations and maintenance.

Causality between multi-scale built environment and rail transit ridership in Beijing and Tokyo

Recent years have witnessed researchers' academic interests in the relationship between the built environment and rail transit ridership. However, few studies have analyzed it from a beyond-station scale and causal perspective. To fill this gap, this study uses Beijing and Tokyo as cases and utilizes Bayesian networks and generalized propensity score matching to achieve causal discovery and causal inference of built environment and ridership. Moreover, we innovatively consider the line-scale built environment factors. Evidence suggests that transit agencies should promote the overall accessibility of stations along the line to employment concentration areas more than single-station accessibility in Beijing. Meanwhile, the positive impact of bus-rail transit line cooperation on ridership is limited in Beijing. Planners should consider the capacity of rail transit lines. The causal inference results are mainly in line with previous correlation studies, but some interesting differences exist. For example, the net effect of dense pedestrian roads on ridership is negative, reminding policymakers that they should avoid expanding pedestrian paths without developing ridership-attracting resources. This study uses causal theories to emphasize the necessity of corridor-based and modest development.

Prediction model of land surface settlement deformation based on improved LSTM method: CEEMDAN-ICA-AM-LSTM (CIAL) prediction model.

The uneven settlement of the surrounding ground surface caused by subway construction is not only complicated but also liable to cause casualties and property damage, so a timely understanding of the ground settlement deformation in the subway excavation and its prediction in real time is of practical significance. Due to the complex nonlinear relationship between subway settlement deformation and numerous influencing factors, as well as the existence of a time lag effect and the influence of various factors in the process, the prediction performance and accuracy of traditional prediction methods can no longer meet industry demands. Therefore, this paper proposes a surface settlement deformation prediction model by combining noise reduction and attention mechanism (AM) with the long short-term memory (LSTM). The complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and independent component analysis (ICA) methods are used to denoise the input original data and then combined with AM and LSTM for prediction to obtain the CEEMDAN-ICA-AM-LSTM (CIAL) prediction model. Taking the settlement monitoring data of the construction site of Urumqi Rail Transit Line 1 as an example for analysis reveals that the model in this paper has better effectiveness and applicability in the prediction of surface settlement deformation than multiple prediction models. The RMSE, MAE, and MAPE values of the CIAL model are 0.041, 0.033 and 0.384%; R2 is the largest; the prediction effect is the best; the prediction accuracy is the highest; and its reliability is good. The new method is effective for monitoring the safety of surface settlement deformation.

Research on Street Landscape Design Along Urban Rail Transit Lines

The study on the landscape design of urban streets along the rail transit lines is an important topic in urban planning and development. With the acceleration of urbanization, the construction and improvement of urban rail transit systems have become a top priority. However, there are numerous challenges and issues in the landscape design of streets along rail transit lines. In recent years, governments and relevant departments have actively promoted the construction of urban green streets and integrated ecological concepts into landscape design to address the pressures and challenges brought about by urbanization. Drawing on the experiences of ecological city construction, the establishment of urban green streets has become an effective approach to solving the functional and environmental problems of urban streets. By integrating green infrastructure into street design, it is possible to effectively manage stormwater and improve the street environment. Research indicates that the root cause of urban street flooding lies in the increase of impervious surface area, which alters the surface hydrological conditions and impedes the collection and utilization of rainwater. Therefore, the design of urban green streets should focus on functional zoning, awareness of stormwater management, and integration of urban cultural landscapes. Through the application of these design methods, not only can the existing problems of urban streets be solved, but valuable design experience and guidance can also be provided for future urban green street construction.