Wuhan-Guangzhou High-speed Rail Research Articles

Short-term high-speed rail passenger flow prediction by integrating ensemble empirical mode decomposition with multivariate grey support vector machine

Short-term prediction of high-speed rail (HSR) passenger flow provides a daily ridership estimation for the near future, which is critical to HSR planning and operational decision making. This paper proposes a new methodology that integrates ensemble empirical mode decomposition with multivariate support vector machines (EEMD-MSVM). There are four steps in this hybrid forecasting approach: (i) explore the correlation of multivariate HSR passenger flows at various stations based on archived data; (ii) decompose empirical modes of historical passenger flows for each HSR station, using EEMD to generate a number of intrinsic mode functions (IMFs) and a trend term; (iii) predict the IMF for each correlated station pair using MSVM; and (iv) reconstruct the refined IMF components to predict daily multivariate HSR passenger flows. The proposed EEMD-MSVM approach is demonstrated with multiple OD pairs along the Wuhan-Guangzhou HSR in China. Results from various origin-destination pairs, show that the EEMD-MSVM approach outperforms the existing ensemble empirical mode decomposition with grey support vector machine approach (EEMD-GSVM). With the multivariate approach, the mean absolute percentage error in demand prediction is reduced by 13.9%, 1.2%, 1.0%, 2.0%, and 2.7% and the mean absolute deviation is reduced by 78.8, 38.0, 4.4, 4.6, and 3.9, between these OD pairs respectively. Such increase in short-term demand prediction accuracy can significantly improve HSR service planning, operations, and revenue management in the real world.

The Impact of High-Speed Rail on the Service-Sector Agglomeration in China

High-speed rail (HSR) can potentially influence various economic activities across space. Estimating the impacts of HSR on service-sector agglomeration (SSA) was proven to be difficult but meaningful. In this paper, prefectural-level data from 1998 to 2016 and a panel data program evaluation method are employed to evaluate the effect of the Wuhan–Guangzhou HSR (WGHSR) on the SSA along the route. In this way, we construct hypothetical counterfactuals for SSA index of the WGHSR cities in the absence of the HSR projects using the SSA index in selected non-HSR cities. By comparing the counterfactual index and the actual index, the evaluation of the WGHSR’s impact on the SSA along the route can be obtained. The results show that: (a) the WGHSR has increased the SSA by 9.44% on average for cities along the WGHSR, and (b) the impacts of the WGHSR on the SSA are heterogeneous. The WGHSR has brought about both spillover effect and “siphon” effect. In addition, whether the HSR influences and how much it could influence the SSA requires other supplementary conditions to be met. As a national strategy in China, the construction plan of HSR should fully consider its heterogeneity of impact on regional development. Policies should be formulated to drive the HSR’s spillover effect to promote regional sustainable development.

Stochastic Model of Train Running Time and Arrival Delay: A Case Study of Wuhan–Guangzhou High-Speed Rail

Train operations are subject to stochastic variations, reducing service punctuality and thus the quality of service (QoS). Models of such variations are needed to evaluate and predict the potential impact of disturbances and to avoid service punctuality reduction in train service management and timetabling. In this paper, through a case study of the Wuhan–Guangzhou (WH–GZ) high-speed rail (HSR), we show how a wealth of train operation records can be used to model the stochastic nature of train operations at each level, section and station. Specifically, we examine different distribution models for running times of individual sections and show that the Log-logistic probability density function is the best distributional form to approximate the empirical distribution of running times on the specified line. Next, we show that the distribution of running times in each section can be used to accurately infer arrival delays. Consequently, we construct the underlying analytical model and derive the respective arrival delay distribution at the downstream stations. The results support the correctness of the model presented and show that the proposed model is suitable for constructing the distribution of arrival delays at every station of the specified line. We show that the integrated distribution models of running times and arrival delays, driven by empirical data, can also be used to evaluate the QoS at individual track sections.

Impacts of high-speed rail on domestic air transportation in China

This study investigates the impacts of high-speed rail (HSR) on domestic air transportation in China using a new comprehensive modeling framework utilizing both demand and supply perspectives. For the first time the assessment was conducted using an improved panel regression model by taking into account of the detailed opening schedules of various HSR services during the period 2001–2014. The research findings reveal that the deployed HSR services have a significant substitutional effect on domestic air transportation in China, but the effect varies across different HSR routes, travel distance and city type. Specifically, the research found a decrease in domestic passengers of 28.2%, in flights of 24.6% and in seat capacity of 27.9% after the introduction of HSR services. The impacts are found much stronger among those air routes that connect major hub within a distance range of 500 to 800km. The uneven nature of the impact can be seen in the different experiences of selected cities. For example, air travel declined approximately 45% after commencement of the Wuhan-Guangzhou HSR, whereas it fell by 34% after the opening of the Beijing-Shanghai HSR.

Research on the Impact of Infrastructure Construction on Tourism Industry: Evidence from the “Wuhan-Guangzhou High-Speed Rail”

The “Wuhan-Guangzhou High-Speed Rail” opened on December 26, 2009, which could be regarded as a quasi-natural experiment that improved the quality of transportation infrastructure. With the cities having the stops of “Wuhan-Guangzhou High-Speed Rail” as the treatment group, other cities in the same provinces but without any high speed railway stops as the control group, this paper constructs the panel data from 2005 to 2013 and uses Difference in Differences method to investigate the impact of the opening of “Wuhan-Guangzhou High-Speed Rail” on the tourism economy. We find that tourism revenue in cities from treatment group increased by 13.734 billion to 22.482 billion yuan, and the total number of domestic tourist arrivals increased by 12.9814 million to 16.2512 million people. The conclusion proves that the construction of transportation infrastructure promotes the tourism industry, making up for the insufficient empirical research on the development of tourism.

Wu Guang High-Speed Rail Track Irregularity Power Spectrum Analysis

Irregularity is the locomotive and the main excitation source of vibration, is directly related to the smooth running of the train, safety and comfort, is to control the maximum operating speed of the train one of the main factors. The statistic specimen was collected by track geometry inspection car from Wuhan-Guangzhou high-speed rail. Based on the stationarity test of the specimen, Fast Fourier Transform (FFT) method was used to evaluate the spectrum of the whole specimen space. The power spectrum density (PSD) and related functions of track irregularity were obtained by MATLAB program. We analyzed it by comparing the fitting curve of the national speed lines and fitting curve of Qinhuangdao-Shenyang dedicated passenger railway line, by comparison, the Wuhan-Guangzhou high-speed railway track irregularity is much better than the national speed lines and Qinhuangdao-Shenyang dedicated passenger railway line. The parameter values of PSD fitting curve for track irregularity are obtained by the nonlinear curve-fitting algorithm in the least-squares sense, which has referencing value to maintenance high-speed rail.

Short-term forecasting of high-speed rail demand: A hybrid approach combining ensemble empirical mode decomposition and gray support vector machine with real-world applications in China

Short-term forecasting of high-speed rail (HSR) passenger flow provides daily ridership estimates that account for day-to-day demand variations in the near future (e.g., next week, next month). It is one of the most critical tasks in high-speed passenger rail planning, operational decision-making and dynamic operation adjustment. An accurate short-term HSR demand prediction provides a basis for effective rail revenue management. In this paper, a hybrid short-term demand forecasting approach is developed by combining the ensemble empirical mode decomposition (EEMD) and grey support vector machine (GSVM) models. There are three steps in this hybrid forecasting approach: (i) decompose short-term passenger flow data with noises into a number of intrinsic mode functions (IMFs) and a trend term; (ii) predict each IMF using GSVM calibrated by the particle swarm optimization (PSO); (iii) reconstruct the refined IMF components to produce the final predicted daily HSR passenger flow, where the PSO is also applied to achieve the optimal refactoring combination. This innovative hybrid approach is demonstrated with three typical origin–destination pairs along the Wuhan-Guangzhou HSR in China. Mean absolute percentage errors of the EEMD-GSVM predictions using testing sets are 6.7%, 5.1% and 6.5%, respectively, which are much lower than those of two existing forecasting approaches (support vector machine and autoregressive integrated moving average). Application results indicate that the proposed hybrid forecasting approach performs well in terms of prediction accuracy and is especially suitable for short-term HSR passenger flow forecasting.

A Study on High-Speed Rail Pricing Strategy in the Context of Modes Competition

High-speed rail (HSR) has developed rapidly in China over the recent years, for the less pollution, faster speed, comfort, and safety. However, there is still an issue on how to improve the seat occupancy rates for some HSR lines. This research analyzes the pricing strategy for HSR in Wuhan-Guangzhou corridor based on the competition among different transport modes with the aim of improving occupancy rates. It starts with the theoretical analysis of relationship between market share and ticket fare, and then disaggregate choice models with nested structure based on stated preference (SP) data are established to obtain the market share of HSR under specific ticket fare. Finally, a pricing strategy is proposed to improve the occupancy rates for Wuhan-Guangzhou HSR. The results confirm that a pricing strategy with floating fare should be accepted to improve the profit of HSR; to be specific, the ticket fare should be set in lower level on weekdays and higher level on holidays.

Competition between Wuhan-Guangzhou High-speed Railway and Civil Aviation Based on Disaggregate Model

With the operation of high-speed railways, the market share of air transportation has certain decrease, and there exist intense competitions between these two modes. Bases on the field data from the Wuhan-Guangzhou high-speed railway and the data from some air companies, this paper, develops a competition binary Logit model for Wuhan-Guangzhou high-speed rail and air transport with the non-set design model and relevant principles. The stated preference (SP) data are revised under revealed preference (RP) data, and the competition degree between high-speed railway and air transportation are measured by different air ticket price discount. The results indicate that when the ticket price discount of Wuhan-Guangzhou air is higher than 30%, there exist keen competitions between the high-speed railway and air transportation, and the higher the discount is the more competitions exist. This research is beneficial for balance the development of high-speed rail and air transportation and avoiding blind competitions of these two modes.

Red Clay Subgrade Settlement Calculation Methods in Ballastless Track Design on High-Speed Railway

Considering the characteristics of high-speed railway settlement requirement, i.e. high precision and strict control after construction, the subgrade settlement of the Wuhan-Guangzhou high-speed rail on the red clay area is calculated by ES method, e-lgp method, triaxial stress method, secant modulus method and field test method. In this essay, the accuracy of various calculation methods has been compared and corrected with the values from loading test. In this process, correction coefficients for various calculation methods have been obtained.

Radio Wave Propagation Scene Partitioning for High-Speed Rails

Radio wave propagation scene partitioning is necessary for wireless channel modeling. As far as we know, there are no standards of scene partitioning for high-speed rail (HSR) scenarios, and therefore we propose the radio wave propagation scene partitioning scheme for HSR scenarios in this paper. Based on our measurements along the Wuhan-Guangzhou HSR, Zhengzhou-Xian passenger-dedicated line, Shijiazhuang-Taiyuan passenger-dedicated line, and Beijing-Tianjin intercity line in China, whose operation speeds are above 300 km/h, and based on the investigations on Beijing South Railway Station, Zhengzhou Railway Station, Wuhan Railway Station, Changsha Railway Station, Xian North Railway Station, Shijiazhuang North Railway Station, Taiyuan Railway Station, and Tianjin Railway Station, we obtain an overview of HSR propagation channels and record many valuable measurement data for HSR scenarios. On the basis of these measurements and investigations, we partitioned the HSR scene into twelve scenarios. Further work on theoretical analysis based on radio wave propagation mechanisms, such as reflection and diffraction, may lead us to develop the standard of radio wave propagation scene partitioning for HSR. Our work can also be used as a basis for the wireless channel modeling and the selection of some key techniques for HSR systems.

INFRASTURE INVESTMENT IN CHINA: FROM CENTRAL MONOPOLY TO MULTI-LEVEL PARTNERSHIP

This study attempts to understand the post-reform decentralization of infrastructure investment and transfer of responsibility in China. Changes in the institutional configuration of infrastructure investment are a reflection of the ongoing process of state restructuring. Since the economic reform, infrastructure investment has transformed from being an exclusive central state-controlled operation to a central-local bargaining regime. The functions formerly exclusive to the central government are now scaling down to local governments, while scaling out to market actors. This has fuelled the formation of new partnerships in infrastructure development. However, the scaling down and scaling out processes have not led to the total retreat of the central state, nor the relaxation of state control. Using the Wuhan-Guangzhou High Speed Rail as an example, this paper investigates the inter-scalar and relational webs of multi-actor and multi-level governance in financing a major infrastructure project. Our main argument is that the state investment regime has now shifted from an exclusive, national monopoly to an intrinsic partnership, between different tiers of governments, and between the state and the market in order to meet the demands of development and to overcome the hurdles of state budget constraints.