Under inclement weather conditions such as rain and snow, the wheel-rail adhesion characteristics of urban rail transit systems significantly deteriorate, posing failure risks to the overspeed protection function of Automatic Train Control (ATC) systems. To enhance the global robustness of ATC systems, this study investigates optimization strategies for ATC overspeed protection control under low-adhesion conditions. First, the operational mechanism of ATC overspeed protection is systematically analyzed through the Safety Braking Model, Guaranteed Emergency Braking Rate (GEBR), and adhesion braking principles. Second, by examining the mismatch between the rigid GEBR setting in engineering practice and the stochastic fluctuation of adhesion coefficients in actual operations, this research reveals a chain failure mechanism: “adhesion degradation→braking performance reduction→GEBR dynamic mismatch→safety threshold breach in braking distance”. Finally, a MATLAB-based simulation model integrating dynamic wheel-rail adhesion characteristics is developed for ATC overspeed protection, with validation through specific accident cases. Results demonstrate that compared with existing rain-snow mode protection strategies, the proposed multi-objective collaborative optimization dynamic control strategy achieves refined coordination of GEBR values and system ceiling speed, effectively balancing train braking safety and system operational efficiency in low-adhesion environments.

To meet the demand for efficient, low-power, and secure authentication mechanisms in the safety monitoring and maintenance of rail transit equipment, this study systematically investigates the implementation of cross-domain identity authentication. First, a system architecture is designed using a super SIM card as the identity carrier, combined with Bluetooth Low Energy (BLE) technology for rapid data exchange between devices. Second, a high-efficiency anonymous identity authentication scheme integrating a blinded ECDSA algorithm is proposed. Finally, the proposed scheme is compared with supervised anonymous authentication schemes and other traditional authentication algorithms regarding computation and communication overheads. The results indicate that, compared to NIST-standard-based ECDSA and traditional ECC algorithms, the proposed scheme demonstrates superior performance in signature generation with the shortest overall runtime. Additionally, authentication efficiency is improved by 43.8% compared to supervised anonymous authentication schemes, verifying the effectiveness and feasibility of the proposed approach. These findings provide a valuable reference for intelligent security monitoring and maintenance of equipment in low-altitude economic sectors and the rail transit field.

In major metropolitan areas, the severe congestion during peak hours at urban rail transit stations necessitates comprehensive research on train timetable, particularly focusing on the implementation of short-turn and full-length routing strategies coupled with passenger flow control measures. This study takes the morning peak period of urban rail transit lines as its research subject, establishing an optimization model for train timetables by considering passenger travel costs and enterprise operational expenses as the objective functions, while incorporating constraints such as train departure intervals, vehicle capacity, passenger flow control, and routing strategies. Utilizing a linear weighting method to balance both passenger and operational costs, the research develops a genetic algorithm for model solution, with Hangzhou Metro Line 4 serving as a case study. The findings demonstrate that optimized train schedules effectively reduce passenger travel costs, while the implementation of short-turn and full-length routing strategies contributes to lowering operational expenses for enterprises. Furthermore, the integration of passenger flow control measures significantly alleviates station congestion levels. This research on timetable optimization, based on routing strategies and passenger flow control, provides valuable insights for rail transit enterprises in formulating effective peak-hour dispatching strategies.

Aiming at the problems existing in the practice, location and operation of Metro-based Underground Logistics System (M-ULS), the research ideas and improvement measures for the existing problems of M-ULS are proposed. Firstly, it summarises the shortcomings of domestic and foreign construction feasibility and practice research, and puts forward the medium- and long-term feasibility planning for the development of M-ULS; secondly, it analyses the differences between the siting of key nodes of M-ULS and the reality, and points out the ideas for subsequent research; finally, it summarises the factors affecting the overall operation of M-ULS and the influencing factors that have not yet been studied in depth, and points out several key technologies for realising the informatisation of the operation of M-ULS. and points out several key technologies to realise the informatisation of M-ULS operation. The results of the study show that China has a realistic foundation for the construction of M-ULS, but it needs to formulate appropriate cargo transport standards, establish a perfect evaluation system and improve the technologies required for information-based operation.

To alleviate platform congestion caused by a large number of passengers exiting metro stations near event venues before the start of large-scale events, this study proposes a method that staggers the arrival times of trains in both directions and incorporates a skip-stop strategy. A mathematical optimization model is developed to minimize the platform dwell time of outbound passengers, the risk of crowding on the platform, and the number of skip-stop operations. Furthermore, an iterated local search algorithm is designed, taking into account the characteristics of passenger flow and the metro timetable during large-scale events. The algorithm explores feasible neighboring solutions in two ways: by adjusting train running and stopping times, and by modifying stop plans. Using data from a major event in Nanchang as a case study, the effectiveness of the model and algorithm is validated. The results show that the proposed iterated local search algorithm can quickly obtain high-quality solutions. After optimization, the maximum number of passengers on the platform decreased from 2,951 to 1,006, the average platform exit time for passengers was reduced by 94.7 seconds, and the platform crowding risk was reduced by 94%. The strategies of staggering train arrivals and implementing skip-stops can effectively reduce passenger exit times and alleviate congestion at stations near event venues before large-scale events begin.

To address the challenge of certain rail transit lines facing closure due to continuously declining ridership, this study takes the evolutionary trajectory of Japan's rail transit development as a starting point and employs a multi-case comparative analysis. The research thoroughly investigates the triggering factors, policy frameworks, and supporting measures for the closure of low-ridership lines. The results show that changes in population and industrial structure, as well as shifts in travel modes, are the core factors leading to the sustained decline in rail transit ridership. At the same time, increased maintenance costs caused by aging infrastructure and severe revenue-expenditure imbalances have further worsened line operations. In response, Japan has established evaluation systems centered on transport density to classify and assess low-ridership lines, and has implemented systematic governance schemes covering ridership cultivation and cost control. For lines where closure is unavoidable, innovative alternatives such as Bus Rapid Transit (BRT) dedicated lanes and demand-responsive transit have been adopted, effectively addressing operational challenges and ensuring residents’ basic mobility needs. By comprehensively analyzing the problem of low-ridership rail transit closures and the corresponding measures taken in Japan, this study summarizes relevant experiences and lessons, aiming to provide references for the future operation and transformation of rail transit in China.

In order to analyze the development and current research status of urban rail transit network performance evaluation, in urban rail transit networks this paper conducts a quantitative analysis of the literature from the CNKI database based on CiteSpace software. This paper gradually focuses on three levels of research: urban rail transit, urban rail transit network, and urban rail transit network performance evaluation, and analyzes the information such as the number of publications, authors, literature sources and keywords. By tracing the important literature, the main indicators of rail transit network performance evaluation are summarized, and the advantages and disadvantages of different evaluation methods are commented. The results show that the research on performance evaluation of urban rail transit networks is undergoing several important transformations. Firstly, the analytical model is developed from unweighted network to weighted network model, which pays more attention to the differences between stations and intervals. Secondly, the research object was extended from the analysis of rail transit network to the comprehensive evaluation of coupled transportation networks such as railroad and railbus. Finally, the research focus of network performance has gradually shifted from the resistance ability under disasters or external shocks to the resilience evaluation including the postdisaster recovery ability.

The positive externalities of urban rail transit necessitate a comprehensive economic costbenefit analysis when evaluating project economic feasibility. In response to the latest requirements for preparing the outline and explanation of the project feasibility report, this study conducted a multidimensional study on the economic costbenefit of urban rail transit. Firstly, identify economic costs and benefits from three dimensions: government, enterprises, and the public, establish a threelevel quantitative+qualitative indicator system, expand quantitative indicators from 5 to 13, and add 14 qualitative indicators; Secondly, conduct research on key indicator analysis methods, propose quantitative methods for driving GDP, fiscal revenue, and increasing employment, break through the current difficulties in evaluating the macroeconomic contribution of urban rail transit, and improve the calculation methods for time saving benefits, fatigue reduction benefits, and traffic accident reduction benefits; Finally, it is clarified that there are 9 indicators that can be included and 4 indicators that cannot be included in the economic costbenefit analysis flow table, and a comprehensive evaluation of the project's economic costbenefit is conducted through case studies to provide support for earlystage decisionmaking and promote sustainable development of the industry.

To address the difficulty in selecting urban rail transit projects in large cities, a model for evaluating the selection of urban rail transit construction projects was constructed based on the analytic network process (ANP). Based on the policy requirements and the demands of relevant stakeholders, five evaluation criteria are proposed: urban coordination, social impact, construction implementation costeffectiveness, postconstruction traffic effects, and network service improvement. These criteria are further refined into nine evaluation indicators. An evaluation model operation platform was constructe, and the evaluation model was verified using a city in Southwest China as a case study. The technical route of the evaluation model conforms to the decisionmaking logic for selecting urban rail transit construction planning projects. The input data of the evaluation model are all data that can be obtained during the construction planning phase. The output results of the evaluation model can intuitively reflect the priority ranking of the candidate projects.

During subway train operation in tunnels, piston wind is generated, which significantly affects the tunnel flow field. Understanding piston wind characteristics is crucial for its effective utilization. It is of great significance to study the characteristics of piston wind for rational utilization of piston wind. Based on Bernoulli equation of unsteady flow, a lumped parameter theoretical model of piston wind in subway tunnel is established, and the characteristics of unsteady piston wind are analyzed. In order to verify the accuracy of the theoretical model, a reduced size model test bench of 1:16 was established, and the piston wind speed was tested experimentally. The comparison between the model value and the measured value shows that the Pearson correlation coefficient is higher than 0.98, and the average error is lower than 13%, which verifies the correlation and accuracy of the theoretical model. By using the lumped parameter theory model, the influence of different factors on the piston wind in subway tunnel is explored, and the grey correlation degree is analyzed. The results show that the congestion ratio is the biggest factor affecting the ventilation effect of the tunnel piston, followed by the train length and train speed, and the tunnel length is the least. Based on this, a fitting formula for the ventilation effect of the piston in common subway tunnels in China is proposed.