High-speed Railway Transport Research Articles

Transportation infrastructure, comparative advantage, and regional specialization: Evidence from China’s high-speed railway network

Using the quasi-natural experiment of China’s high-speed railway (HSR), this paper investigates the impact of transportation infrastructure on regional specialization, focusing on the differential effects on sectors with varying degrees of comparative advantages. Constructing a multi-region and multi-sector spatial economic model that includes Ricardian comparative advantage, we find that the reduction in trade costs leads to increases in market access but also intensifies local market competition, disproportionately benefiting sectors with comparative advantages. Empirical analysis of prefecture-level data from 2006 to 2016 reveals that HSR connection positively impacts industries with comparative advantages, but has negative impacts on industries without comparative advantages. This research introduces a new mechanism by which transportation infrastructure influences regional specialization: it disproportionately benefits industries with initial comparative advantages, thereby accelerating their growth relative to industries without comparative advantages. The findings provide valuable insights for policymakers aiming to optimize industrial structure planning in HSR-connected cities. Specifically, policymakers should consider both the reliance on HSR transportation and initial comparative advantages when planning industrial structures.

Scientific support for the design and construction of high-speed railway lines. Chronicle of the Development of Competencies for High-Speed Railway Transport in Russia

The construction of the first high-speed railway in Russia is long overdue. Such a project would be an organic continuation and a new turn in the one and a half century history of Russian railway workers’ struggle to increase train speeds on the country’s railways.

A parallel set-based model on the shortest travel time in long-distance transportation systems

The shortest travel time in long-distance transportation systems (LDTS) is a key indicator for measuring regional connectivity and mapping accessibility at national and global levels. For traditional methods, it is a great challenge to calculate the shortest travel time with millions of origin-destination pairs and evaluate the overall performance. To fill this technique gap, this study proposed a novel model to get all the trips with different numbers of transfers through a series of set-based methods and then calculate all the shortest travel time between stops. The set-based model was tested for calculating the shortest travel time in LDTS of China. Using the optimization algorithm, we can significantly reduce the number of transfer trips that need to be calculated. For instance, the number of transfer trips decreased by 96.17%, 98.15%, and 79.02%, for conventional railway, high-speed railway, and air transportation, respectively, when the number of transfers was two. The set-based model can be extended to calculate the door-to-door travel time between places, for instance, mapping the fine-scale accessibility at the national level. Furthermore, we proved that this set-based model, proposed in this study, could also be parallelized and applied to any other LDTS in the General Transit Feed Specification format.

Optimizing high-speed railway express system under uncertainty

The rapid expansion of high-speed railway (HSR) networks has elevated the HSR express system, which combines road and HSR transport, as a notable intermodal transport choice. This research delves into the optimization challenges present in the HSR express system's operation, given the unpredictable freight demands. These challenges encompass vehicle arrangement, station selection, freight allocation, and the optimization of HSR freight routes. To address these challenges, we introduce a two-stage mixed integer linear programming model aiming to optimize the anticipated net gains of the HSR express system. We also put forward a meta-heuristic method to efficiently solve the model. Empirical tests and sensitivity studies, grounded in a real-world example from the China Railway Nanchang Group Co., Ltd., are executed. Additionally, advanced techniques, including parallel computing tailored to the problem's nature, have been employed to trim down computational times, especially for intricate real-world scenarios. The findings from this study provide valuable insights for industry practitioners.

A comparative study of geosynthetically reinforced earth foundations in multi-utility transportation infrastructure for high-speed railways

A high-quality railway track resting on an excellent foundation is required to support high-speed railway transportation. The foundations of high-speed railway tracks are generally constructed on the lifted embankment with the improved ground using different reinforcement agents like geosynthetics and rigid lateral support. The present study performed dynamic finite element simulations on a ballasted rail track laid over a geosynthetically reinforced embankment with and without facing wall support. Three foundation geometries were analyzed to examine the effect of facing wall support and geosynthetics on the lateral resistance of the foundation. An area loaded with a constant pressure was moved at a constant speed, causing the load motion at different speeds in the 90–360 km/h range. Different parameters were calculated at node paths to help understand the lateral effect of moving load. The results showed that the lateral resistance based on nodal acceleration and velocity increased with facing wall support in the range of 40%–57%. Any increment over the minimum facing wall thickness of 300 mm does not significantly increase lateral resistance. Geosynthetics provided a vital function in the foundations with a less bulk volume of soil and increased the lateral resistance by 10%.

An Automatic Train Operation Based Real-Time Rescheduling Model for High-Speed Railway

With the continuous development of the Automatic Train Operation (ATO) system in high-speed railways, automatic driving is progressively supplanting manual operations, ushering in a new era of predictability and reliability for high-speed railway transport. Concurrently, the advent of the ATO system provides a notable impact on real-time rescheduling during disruptions, as it equips dispatchers with precise insights into train operation statuses. This paper is dedicated to a thorough analysis of how the transition to automatic driving in train operations influences the real-time rescheduling model. Based on the distinctive impact of the ATO system on real-time rescheduling, we have proposed a mixed-integer linear programming model that combines train re-timing, reordering, and the minimization of passenger delays. To validate the effectiveness of our model, we present several experiments conducted using data from the Beijing–Shanghai high-speed railway line. The results unequivocally demonstrate that our ATO-based model significantly mitigates train delay time, demonstrating its practical value in optimizing high-speed railway operations.

Key technologies and applications of intelligent dispatching command for high-speed railway in China

PurposeThe intelligent Central Traffic Control (CTC) system plays a vital role in establishing an intelligent high-speed railway (HSR) system. As the core of HSR transportation command, the intelligent CTC system is a new HSR dispatching command system that integrates the widely used CTC in China with the practical service requirements of intelligent dispatching. This paper aims to propose key technologies and applications for intelligent dispatching command in HSR in China.Design/methodology/approachThis paper first briefly introduces the functions and configuration of the intelligent CTC system. Some new servers, terminals and interfaces are introduced, which are plan adjustment server/terminal, interface for automatic train operation (ATO), interface for Dynamic Monitoring System of Train Control Equipment (DMS), interface for Power Supervisory Control and Data Acquisition (PSCADA), interface for Disaster Monitoring, etc.FindingsThe key technologies applied in the intelligent CTC system include automatic adjustment of train operation plans, safety control of train routes and commands, traffic information data platform, integrated simulation of traffic dispatching and ATO function. These technologies have been applied in the Beijing-Zhangjiakou HSR, which commenced operations at the end of 2019. Implementing these key intelligent functions has improved the train dispatching command capacity, ensured the safe operation of intelligent HSR, reduced the labor intensity of dispatching operators and enhanced the intelligence level of China's dispatching system.Originality/valueThis paper provides further challenges and research directions for the intelligent dispatching command of HSR. To achieve the objectives, new measures need to be conducted, including the development of advanced technologies for intelligent dispatching command, coping with new requirements with the development of China's railway signaling system, the integration of traffic dispatching and train control and the application of AI and data-driven modeling and methods.

Multi-Sensor Graph Transfer Network for Health Assessment of High-Speed Rail Suspension Systems

Suspension systems are significant for safe and comfort operation of high-speed trains. Health assessment is a useful tool to schedule maintenance plans of suspension systems, and furthermore ensure safety operation of high-speed railway transportation. In real operating condition, two problems, i.e. data imbalance and shortage of labelled data, result in difficult for health assessment of the suspension system using deep learning. In this work, a multi-sensor information fusion method, called as multi-sensor graph transfer network (MSGTN), is proposed in basis of deep transfer learning and graph neural network. In the proposed method, a domain-share multi-sensor graph neural network (MSGNN) is firstly proposed to extract features from vibration signals collected from three different positions in train vehicles. A graph-based fusion layer in MSGNN is proposed to fuse multi-sensor information by combining frequency response curves of the suspension system. The MSGTN mainly includes two parts in source and target domains respectively. In the source domain, a simple physical dynamic model of high-speed rail suspension system is built to generate labelled simulation datasets to pre-train MSGNN. In the target domain, the initial hyper-parameters of MSGNN are that of the pre-train model in the source domain. The labelled data in the target domain is fed to fine-tune MSGNN and then the final model for health assessment can be obtained by minimizing the loss function. The effectiveness of the proposed method was verified using real-work operation data.

Enhanced Hardness-Toughness Balance Induced by Adaptive Adjustment of the Matrix Microstructure in In Situ Composites.

With the development of high-speed and heavy-haul railway transportation, the surface failure of rail turnouts has become increasingly severe due to insufficient high hardness-toughness combination. In this work, in situ bainite steel matrix composites with WC primary reinforcement were fabricated via direct laser deposition (DLD). With the increased primary reinforcement content, the adaptive adjustments of the matrix microstructure and in situ reinforcement were obtained at the same time. Furthermore, the dependence of the adaptive adjustment of the composite microstructure on the composites' balance of hardness and impact toughness was evaluated. During DLD, the laser induces an interaction among the primary composite powders, which leads to obvious changes in the phase composition and morphology of the composites. With the increased WC primary reinforcement content, the dominant sheaves of the lath-like bainite and the few island-like retained austenite are changed into needle-like lower bainite and plenty of block-like retained austenite in the matrix, and the final reinforcement of Fe3W3C and WC is obtained. In addition, with the increased primary reinforcement content, the microhardness of the bainite steel matrix composites increases remarkably, but the impact toughness decreases. However, compared with conventional metal matrix composites, the in situ bainite steel matrix composites manufactured via DLD possess a much better hardness-toughness balance, which can be attributed to the adaptive adjustment of the matrix microstructure. This work provides a new insight into obtaining new materials with a good combination of hardness and toughness.

Simulation Analysis and Online Monitoring of Suspension Frame of Maglev Train

A maglev train is a new type of high-speed railway transportation. A high-temperature superconducting (HTS) maglev system is one of the typical representatives in the field of maglev trains. In order to research the levitation characteristics of an HTS maglev train, the force characteristics and operation performance of the train were researched. However, at present, there is still no research that simulates the real load situation of a running maglev train while analyzing the suspension frame. Regarding this issue, in this paper, the suspension frame is simulated and analyzed to simulate the real load situation of a maglev train. The results show that the suspension frame of an HTS maglev train can bear corresponding loads under different working conditions, and its strength and stiffness meet the requirements of use, safety, and reliability. Random irregularity in the permanent magnet track of an HTS maglev train route is inevitable, which will make the suspension frame produce a vibration response under different running speeds of the train. Vibration of the suspension frame of the train is inevitable. For the electromagnetic levitation (EMS) train, researchers considered monitoring the train status. However, at present, there is no suspension frame condition monitoring device for an HTS maglev train. In addition, the levitation height of the suspension frame affects the suspension performance and traction performance of the vehicle, and the vibration of the suspension frame during running affects the dynamic performance and safety of the suspension frame and the vehicle. Regarding the issue above, through a suspension frame monitoring system, the lateral and vertical vibration acceleration and levitation height of the suspension frame are monitored at different train speeds. The maximum value of vibration acceleration and the fluctuation range of levitation height are within the safe range. It is verified that the simulation analysis of the suspension frame of an HTS maglev train is correct, the suspension frame is safe, and the train can run safely.

Collaborative optimization for train stop planning and train timetabling on high-speed railways based on passenger demand.

In recent years, with increasing passenger travel demand, high-speed railways have developed rapidly. The stop planning and timetabling problems are the core contents of high-speed railway transport planning and have important practical significance for improving efficiency of passenger travel and railway operation Dong et al. (2020). This study proposes a collaborative optimization approach that can be divided into two phases. In the first phase, a mixed-integer nonlinear programming model is constructed to obtain a stop plan by minimizing the total passenger travel time. The constraints of passenger origin-destination (OD) demand, train capacity, and stop frequency are considered in the first phase. In the second phase, the train timetable is optimized after the stop plan is obtained. A multiobjective mixed-integer linear optimization model is formulated by minimizing the total train travel time and the deviation between the expected and actual departure times from the origin station for all trains. Multiple types of trains and more refined headways are considered in the timetabling model. Finally, the approach is applied to China's high-speed railway, and the GUROBI optimizer is used to solve the models in the above two stages. By analyzing the results, the total passenger travel time and train travel time decreased by 2.81% and 3.34% respectively. The proposed method generates a more efficient solution for the railway system.

An Examination of the Spatial Spillover Effects of Tourism Transportation on Sustainable Development from a Multiple-Indicator Cross-Perspective

Tourism is linked to multiple dimensions, such as the economy, society, and environment, and the relationships among its influencing factors are complex, diverse, and overlapping. This study constructed an evaluation index system to measure the degree of coordinated development of tourism, transportation, and the regional economy, then built a tourism-transportation-based Spatial Durbin Model (SDM) regarding the process of the coordinated development of tourism in the Beijing-Tianjin-Hebei region (BTHR) from 2010 to 2020. This paper explains the current status of sustainable tourism development in the BTHR and the impact and spillover effects of transportation on tourism development. The results show that the normalized tourism coordinated development index (NTCDI) of the BTHR increased from 13.61 in 2010 to 18.75 in 2019, then decreased to 14.45 in 2020. The results of SDM show that different transportation modes have different spillover effects on tourism. Specifically, civil aviation transportation has a positive impact and significant spillover on a city’s tourism revenue (TR), while high-speed railway transportation has a negative spillover effect. The model results also show that the degree of openness of the city and city economic development level have significant positive effects and spillover effects on tourism development. Finally, the implications of related variables are discussed, and some suggestions are put forward on tourism development in the BTHR. However, there are some limitations in this study. In the future, international cooperation and data sharing will be strengthened, and multivariate methods such as social network analysis, artificial intelligence, and machine learning will be further integrated to achieve accurate simulation and prediction of the spatial spillover effects of tourism transportation.

High-Speed Railway Access Pattern and Spatial Overlap Characteristics of the Yellow River Basin Urban Agglomeration

With the rapid development of high-speed railway (HSR) transportation in China, its impact on regional spatial patterns and shaping has become increasingly significant. This study took seven urban agglomerations in the Yellow River Basin as the research object, using the 2 h HSR access time in the Yellow River Basin to comparatively analyze the differences in HSR access in the urban agglomeration in the Yellow River Basin, and using the 3 h HSR access to central cities as the background to conduct regional division and overlapping space identification through cross-regional economic links, before finally selecting the overlapping city of Changzhi for long-term space development strategic planning. The main conclusions were as follows: First, the low-value area of HSR travel time in the Yellow River Basin urban agglomerations was biased toward the center of the urban agglomerations, while the peripheral areas were relatively high-value travel traffic circles, and the HSR travel time showed a circular spatial pattern characteristic of continuous expansion from the center to the peripheral areas. Four urban agglomerations in the upper reaches of the city achieved a 2 h access pattern within the urban agglomeration, whereas three urban agglomerations in the middle and lower reaches of the city only reached the 2 h access level in the center. Second, the Yellow River Basin was divided into six community spaces using the SLPA model based on the economic linkage between the central city and other cities, which were filtered by the 3 h access time from the central city to each city for HSR travel. Three of the six communities produced overlapping spaces, i.e., Community 3 and Community 4 produced overlapping spaces containing Linfen, Community 3 and Community 5 produced overlapping spaces containing Changzhi, Handan, and Xingtai, and Community 4 and Community 5 produced overlapping spaces containing Yuncheng and Sanmenxia. Third, the overlapping space of Changzhi City was selected as a case study for a visionary strategic planning outlook. Combining the geographic location characteristics and future development opportunities of Changzhi, we can try to transform a pass-through node like Changzhi into a hub node in the future, strengthening the gateway status and expanding the hinterland. According to the results of the research and analysis, policymakers can try to implement the expansion and renovation of HSR trunk lines, break the transportation bottlenecks in less developed areas, improve the coverage of the HSR network, and establish a “cross-urban agglomeration” cooperation and coordination mechanism.

Neural Network-Based Hybrid Forecasting Models for Time-Varying Passenger Flow of Intercity High-Speed Railways

Time-varying passenger flow is the input data in the optimization design of intercity high-speed railway transportation products, and it plays an important role. Therefore, it is necessary to predict the origin-destination (O-D) passenger flow at different times of the day in combination with the stable time-varying characteristics. In this paper, three neural network-based hybrid forecasting models are designed and compared, named Variational Mode Decomposition-Multilayer Perceptron (VMD-MLP), Variational Mode Decomposition-Gated Recurrent Unit Neural Network (VMD-GRU), and Variational Mode Decomposition-Bidirectional Long Short-Term Memory Neural Network (VMD-Bi-LSTM). First, the time-varying characteristics of passenger travel demand under different time granularities are analyzed and extracted by the VMD method. Second, three neural network prediction models are constructed to predict the passenger flow sequence after VMD decomposition and reconstruction. Experimental analysis is performed on the Guangzhou Zhuhai intercity high-speed railway in China, and the passenger flow at different time periods of the day under different time granularities is predicted. The following results were found: (i) The number of hidden neurons and the number of iterations of the hybrid forecasting model have a great impact on the prediction accuracy. The error of the VMD-MLP model fluctuates less and it performs more smoothly than both the VMD-GRU model and the VMD-Bi-LSTM model. (ii) The VMD-MLP, VMD-GRU, and VMD-Bi-LSTM models can basically reduce the MAPE error to less than 10%. With the increase of time granularity, RMSE and MAE errors tend to gradually increase, while the MAPE error tends to gradually decrease. (iii) For passenger flow under a smaller time granularity, the prediction accuracy of the VMD-MLP model is higher, while for passenger flow under a larger time granularity, the prediction accuracy of the VMD-GRU and VMD-Bi-LSTM models is higher. (iv) The proposed neural network-based hybrid models outperform the existing models and the hybrid models perform better than the single models.

EMU Route Plan Optimization by Integrating Trains from Different Periods

In recent years, the government of China has paid increasing attention to environmental protection issues and has frequently emphasized the importance of ecological civilization. The high-speed railway transportation mode has outstanding advantages in terms of land utilization, energy conservation and environmental protection. China’s high-speed railway networking features are increasingly prominent and are constructed based on the rapid passenger transport network. Additionally, they save resources and are environmentally friendly while meeting safety, punctuality and profitability standards. Electric multiple unit (EMU) routing plan optimization is an important issue for improving operational EMU efficiency and reducing operational costs. At present, the Chinese EMU routing plans for holidays and weekdays are prepared separately because the holiday train timetable requires more EMUs and maintenance tasks. Different integrative optimization measures are considered, and a model is constructed to integrate an optimized weekday and holiday EMU routing plan problem and minimize the EMUs used and EMU maintenance tasks. The proposed model is based on the branch-and-price algorithm, and a real-world case study is conducted. The real-world numerical experiment shows that the amount of EMU maintenance can be reduced to some extent through the integrated optimization of tasks, but it is difficult to reduce the number of EMUs due to the structure of the train operational timetable.

Earthquake resilience assessment and improving method of high-speed railway based on train timetable rescheduling

Owning the characteristics of fast transportation speed and large transportation volume, high-speed railway (HSR) transportation is one of the most critical ways for passenger and freight transportation between cities. On the HSR, trains operate according to the planned timetable normally. However, error and conflict will occur when facing unexpected disruptions for the inability of timely and correct rearrangement by human beings also due to those characteristics. Most literature contributions fail in considering the change in traffic demand after the disruption caused by specific disasters. To this end, a mixed integer linear programming (MILP) model considering the main track outage, track recovery, station recovery, and dynamic traffic demand to enhance seismic resilience is proposed to solve the timetable rescheduling problem (TRP) after earthquakes automatically and in timely. Moreover, the use of the original timetable as a guidance solution reduces the computation time significantly. The proposed method is performed on a realistic simulation of the Dalian-Shenyang section of the Harbin-Dalian HSR of the China HSR network against an earthquake. The outcomes provide the optimal timetable from the recovery period to resume to the original timetable that leads to the best resilience. A computational test of the proposed model on a heavily used part of the China HSR reveals that the method can find optimal solutions with the highest resilience in short computation times.

Перспективы развития сети высокоскоростных железных дорог в мире на ближайшее десятилетие

Purpose: To find main conceptions of the development of high-speed lines in the world, to outline leading countries in the sphere of high-speed railway network construction, to track high-speed railway network construction dynamics, to compare the shares of high-speed railways by individual continents and countries, to define Russia’s place in the sphere of high-speed transport, to outline individual country and continent perspectives for new high-speed line construction and new technology application during construction of the lines in the next decade. Methods: Comparison of construction scales for the outlined high-speed lines by individual countries, graphical analysis of high-speed network growth dynamics in five the most developed by this matter countries. Results: Leading countries in the sphere of high-speed transport network construction are distinguished, relevant values for volumes of existing high-speed network in the world different parts and some countries are presented, a classification of Russia passenger trains depending on the motion speed is given, specificities of organization of high-speed communication in our country are outlined, plans for new high-speed line construction in China, Russia and other countries are expounded, statistical data on high-speed railway spread in the world countries and by individual continents are presented, high-speed network construction dynamics in China, Japan and leading by this matter Europe countries is shown. Practical significance: The given article can serve as a basis for an acquaintance with a relevant status on the matter of existing high-speed railway transport networks, major countries are outlined herein which experience can be taken while creation of high-speed lines in Russia and being based on demonstrated graphical materials, it’s eventual to evaluate real perspectives by the volume of construction of high-speed network nowdays.

Fuzzy Programming Approach for the Electric Multiple Unit Circulation Planning Problem Using Simulated Annealing

Circulation planning for electric multiple units (EMUs) is regarded as one of the key operation issues for a high-speed railway transportation system. The EMU circulation plan consists of determining the connections of trains while accomplishing the passengers’ demands. EMUs need regular maintenance at a certain interval of kilometers or minutes for safety reasons. Consequently, the circulation plan must ensure that EMU trains can reach the maintenance depots in time for their required maintenance. This paper proposes a 0-1 integer programming model for the EMU circulation plan with the aim of minimizing the total costs of the mileage losses of the EMUs, which is incurred when they undergo a maintenance check before the corresponding travel mileage reaches the limit of the cycle. Given that the accumulated travel mileage of EMUs is allowed to be 10% above the standard mileage cycle in practice, an ingenious fuzzy maintenance constraint is presented to tackle the mileage cycle constraint with a certain elasticity. The exterior penalty function is employed to deal with the fuzzy constraint and a simulated annealing (SA) heuristic is employed to solve the model. The modeling and solving approach are applied to a practical instance in the context of China’s high-speed railway system. Compared with the average travel mileage of EMU trains using the manual solution, with the SA solution an increase of 293 km was observed. It can be then concluded that the optimization method presented in this paper can effectively improve the quality of the EMU circulation plan.

Modeling of vehicle movement in computer information-control systems

The subject of the article is the processes of synthesis of a mathematical model of control objects functioning in computer information-control systems of critical purpose for the needs of high-speed railway transport. The main emphasis is on modeling the movement of a passenger train in the high-speed system of Ukrzaliznytsia. The aim is to study the process of regulating the speed of railway vehicles under conditions of uncertainty in the primary information of microprocessor information-control systems of railway transport. Tasks: determination of the criterion of the safety of railway vehicle auto control; obtain a mathematical model of train movement under conditions of uncertainty; check the adequacy of the model. The method used is the mathematical apparatus of discrete models. The following results have been obtained. The mathematical model of train movement developed in this work includes not only information on train position, reference point, direction, and speed of the vehicle but also a variable control indicator to reflect the process of railway traffic adequately. The study shows that, based on the synthesized model, it is possible to use the so-called fuzzy distance between adjacent trains. This approach improves the accuracy of determining the critical distance between trains, the time required to eliminate the risk of collision, the start time of braking, and braking time considering the angle of inclination of the track, as well as the distance of the braking distance. The necessity to determine the control indicator, its value for many points of time, while there is a reduction in speed for the safe movement of trains. Based on the proposed mathematical model, a computer simulation of the process was performed to determine the required time reserve for the train driver to respond to changes in the speed of the previous train, as well as speed ranges that require immediate emergency action. Conclusions. The scientific novelty of the obtained results is the development of a mathematical model of the behavior of mobile units in computer systems for critical use for the needs of railway transport in the presence of failures in the primary information from sensors that record motion parameters. The behavior of the control system at different values of train speed and changes in the value of the interval of the accompanying journey is studied. The theory of traction calculations in computer control systems for mobile units has been further developed. The obtained scientific results will be used in the development of an application program for many critical computer systems for railway.

Vulnerability analysis of the Chinese coupled aviation and high-speed railway network

The integrated aviation and High-Speed Railway (HSR) transportation system plays a vital role for today’s inter-city transportation services. However, an increasing number of unexpected disruptions (such as operation failures, natural disasters, or intentional attacks) pose a considerable threat to the normal operation of the system, especially on ground transfer, leading to the extensive research on its vulnerability. Previous approaches mainly focus on interruptions within a single transportation mode, neglecting the role of ground transfer which serves as a coupled connection between aviation and High-Speed Railway. This paper proposes a network-based framework for evaluating the vulnerability of the Chinese Coupled Aviation and High-Speed Railway (CAHSR) network from the viewpoint of ground transfer interruption. Taking the end-to-end travel time and passenger flow information into consideration as an evaluation measure and analyzing from the perspective of urban agglomerations, an adaptive method is developed to identify the critical cities and further investigate their failure impacts on the geographic distribution of vulnerability. In addition, the proposed model explores variations of vulnerability under different failure time intervals. Based on the empirical study, some major conclusions are highlighted as follows: (A) Only a few cities show significant impacts on the network’s vulnerability when ground transfer interruptions occurred. (B) The distribution of vulnerability is not proportional to the distance between failure city and influenced city. (C) The vulnerability is more serious in the morning and evening when the ground transfer is disconnected. Our findings may provide new insights for maintenance and optimization of the CAHSR network and other real-world transportation networks.