Urban Rail Transit最新文献

When no more than one train is feasibly contained in the separation headway times of two other trains, a triangular gap problem-based method is used to compute the consumed capacity in linear time. This is a strong condition limiting its applicability, while real-world operations often feature mixed traffic of various speeds, creating more complex structures beyond the characterization of a triangular gap. In this paper, we attempt to investigate the multi-train gap scenario and provide a general solution to the railway timetable structure and capacity analysis problem. Given a timetable, we use an incidence graph, the so-called train contraction minor, for representing the consecutive train operations and show that a longest path for spanning the compressed timetable is any path in a graph induced by some topological subsequence of trains that connects the predefined vertices in the train contraction minor. By vector-valued vertex labeling of this minor, we acquire an efficient algorithm that computes the consumed capacity of the timetable. Our algorithm runs in O(mn) time, where m and n are the number of trains and stations, respectively, and is free from the limitation and outperforms the near-linear time policy iteration implementation in the max-plus system of train operations. A toy example and a real-world case study demonstrate the effectiveness and computational performance of the proposed method. The proposed method based on train contraction minor contributes to the railway operations community by promoting the efficient computation of railway line capacity into linear time.

Harmonic distortions in DC third rail systems can cause overheating of electric motors and transformers. Single-tuned filters and shunt active harmonic filters (SAHFs) are often used to mitigate the harmonic distortions. However, there is a lack of studies on the effects of train dynamics on harmonic distortions. This paper aims to investigate the influence of dynamic train behaviors for a DC third rail system and provide recommendations for the design of single-tuned filters and SAHFs to mitigate the harmonic distortions. The traction power supply system of a DC third rail system in Malaysia is modeled using ETAP-eTraX and MATLAB-Simulink software for the investigation. The ETAP-eTraX software is used to accurately compute the dynamic behavior of the train, while MATLAB-Simulink allows for the assessment of the impact of train behavior on the rail track, as well as the harmonic effect of the railway power network on the train. The findings showed that the SAHF exhibits strong adaptability and superior filtering performance compared to the single-tuned filter in addressing dynamic harmonic distortion in traction power supply systems. This study emphasizes the significance of incorporating harmonic mitigation devices, particularly for managing dynamic harmonic distortion based on actual train consumption patterns.

In response to the global trend of urbanization, there has been an increasing focus on transit-oriented development (TOD). However, the prioritization of economic factors in the establishment of TOD often takes precedence over concerns for social equity. This research seeks to address this gap by examining the economic performance and demographic characteristics of 46 rail transit station areas (RSAs) in the city center of Dalian. The study employs the Gini coefficient and affinity clustering to assess the overall economic performance and inequality among different resident groups within RSAs. Furthermore, regression analysis is utilized to identify the key variables influencing economic performance equity in these areas. The results indicate significant disparities in economic dimensions among different resident groups, with station areas in commercial centers and functional core zones demonstrating higher economic performance. Housing prices and job–housing density are identified as crucial factors influencing consumer behavior across various station areas. Despite the presence of employment opportunities and urban development features in RSAs, differences in socioeconomic status and accessibility to public facilities significantly impact resident social equity. These results can assist policymakers in evaluating disparities in the allocation of RSAs among different regions and demographic groups. This study adds to the existing knowledge on equity in the economic performance of RSAs and supports the development of inclusive TOD strategies specific to different locations and populations.

The transit-oriented development (TOD) concept has become a significant catalyst for urban development in China, which has undergone rapid urbanization and has actively participated in the development of public transportation networks over the past 20 years. TOD not only guides the transformation of transportation modes but also leads the development of urban spaces. The extensive construction of urban rail transit in China highlights the universal patterns of TOD and reflects the uniqueness of Chinese practices. This paper analyzes the characteristics of urban development and TOD in developed countries, summarizing the common laws driving TOD in theoretical research. It then compares China, which is in a period of rapid rail transit construction, to identify the unique developmental laws of transit-oriented development of rail transit in China (TOD-RTC). The paper further examines the developmental characteristics of TOD-RTC in practice, considering both temporal and spatial aspects, and explores the reasons behind the formation of individual differences in TOD-RTC. Finally, it discusses the new value and potential that TOD brings to urban development, along with predicting future development trends.

With the rapid development of urban rail transit, the issue of stray current due to incomplete insulation between the rail and the earth is attracting increasing attention. Stray current seriously affects the safe operation of urban rail transit, pipelines and power grids, and pose challenges to the development of urban energy security. However, there are significant differences among the various methods for the analysis and verification of stray currents, and existing research works thus lack a mature theoretical framework. To address this, this paper presents an in-depth review on the study of stray current including the mechanism, technical standards, modelling, simulation and mitigation technologies. Firstly, the principle and standards of stray current are introduced from multiple perspectives (i.e. metro side, pipeline side and grid side). Then, the typical modelling and simulation of stray current are summarized and compared in detail. The representative stray current mitigation measures, together with the stray current hardware simulation technologies, are also discussed. In conclusion, this paper provides a comprehensive overview of key technologies involved in the modelling and simulation of stray current, and highlights the valuable research direction in stray current mitigation.

A comprehensive understanding of the multifaceted ramifications of the coronavirus disease 2019 (COVID-19) on transit ridership is imperative for the optimization of judicious traffic management policies. The intricate influences of this pandemic exhibit a high degree of complexity, dynamically evolving across spatial and temporal dimensions. At present, a nuanced understanding remains elusive regarding whether disparate influencing factors govern inbound and outbound passenger flows. This study propels the discourse forward by introducing a methodological synthesis that integrates time series anomaly detection, impact inference, and spatiotemporal analysis. This amalgamation establishes an analytical framework instrumental in elucidating the spatiotemporal heterogeneity intrinsic to individual impact events, grounded in extensive time series data. The resulting framework facilitates a nuanced delineation, affording a more precise extraction of the COVID-19 impact on subway ridership. Empirical findings derived from the daily trip data of the Beijing subway in 2020 substantiate the existence of conspicuous spatiotemporal variability in the determinants influencing relative shifts in inbound and outbound ridership. Notably, stations situated in high-risk areas manifest a conspicuous absence of correlation with outbound trips, exhibiting a discernibly negative impact solely on inbound trips. Conversely, stations servicing residential and enterprise locales demonstrate resilience, evincing an absence of significant perturbation induced by the outbreak.

Time reliability (TR) is a critical factor that affects the efficiency and service quality of the urban rail transit network (URTN). However, previous studies have not incorporated TR into the evaluation of URTN station importance, focusing instead on basic centrality measures. Therefore, this paper proposes a new metric of station-based TR for evaluating and ranking URTN station importance. The new metric in combination with traditional centrality measures was used by the weighted Technique for Order of Preference by Similarity to Ideal Solution (weighted TOPSIS) to identify the combined significance level of individual URTN station importance and rank them accordingly. To investigate the performance of this method, we exploit deliberate attacks on the top-ranked stations through different methods. A case study of Beijing’s URTN during the morning peak hour showed that the proposed method is generally a better indicator for identifying station importance in maintaining network connectivity. The case study also demonstrated the feasibility and validity of the model. This study can provide recommendations for the planning and operation of rail transit systems and can inform the effective design of station protection strategies.

Traditional support structures cannot meet the complex conditions of different excavation depths and areas in underground transportation hubs. On the basis of fully considering the spatial position relationship of foundation pit groups, this article proposes a multilevel retaining system that meets the requirements of multilevel foundation pit excavation. The evolution law of the support structure during the excavation process of the inner pit was explored using on-site monitoring and numerical simulation methods. The results indicate that the excavation of the inner pit reduces the passive earth pressure, and the deformation of the outer support structure can be effectively suppressed by setting a retaining structure or a bottom slab in the bench zone. The excavation of the inner pit causes significant vertical deformation of the support structure adjacent to the foundation pit, while the impact on the structure far away from the foundation pit is relatively small. According to the contact force chain and soil pressure between the two rows of support structure, the soil in this area is divided into a “relaxation zone” and a “compression zone.” The evolution mechanism of earth pressure in the case of mutual-effect failure between two rows of piles is revealed. This paper addresses the deformation properties of multilevel support structures as well as the mechanism of earth pressure evolution between structures.

With the tremendous increase in the number of vehicles, the dense traffic created can lead to accidents and fatalities. In a traffic system, the costs for accidents are immeasurable. Numerous studies have been carried out to predict the cost of fatal accidents but have provided the actual values. Therefore, in this study, a monkey-based modular neural system (MbMNS) is developed to identify accident cost. The accident cases and cost data were collected and preprocessed to remove the noise, and the required features were extracted using the spider monkey function. Based on the extracted features, the accidents and the costs were identified. For rail engineering, this will support evaluating the number of railroad crossing accidents with different time intervals. The impact of every accident was also measured with different cost analysis constraints, including insurance, medical, and legal and administrative costs. Therefore, the present study contributes to the field by collecting and organizing the present railroad level crossing accident data from crossing inventory dashboards. Then, the introduction of a novel MbMNS for the cost analysis is the primary contribution of this study to further enrich the railroad level crossing protection system. The third contribution is the tuning of the prediction layer of a modular neural network to the desired level to achieve the highest predictive exactness score. Hence, the designed MbMNS was tested in the Python environment, and the results were validated with regard to recall, accuracy, F-measure, precision, and error values; a comparative analysis was also conducted to confirm the improvement. The novel MbMNS recorded high accuracy of 96.29% for accident and cost analysis, which is better than that reported for other traditional methods.