Timetable Optimization for High-Speed Trains at Chinese Railways

Train timetabling for a double-track urban rail transit line under dynamic passenger demand

In August 2013 and for the third consecutive year, Melbourne has been accredited as the most liveable city in the world. However, the city is also known and credited for a less attractive reason as “The City of Level Crossings”; the city’s metropolitan area is home to 170 railroad level crossings (RLX). Since 2006, Melbourne has experienced unprecedented train patronage demand. Victorian transport authorities, facing capacity, demand and overcrowding problems, have acquired new train sets, established new timetables that introduced additional urban train services, and prepared long term plans to address the issue. However, the additional train services result in a ‘catch 22’ situation. The additional train traffic causes extra boom gate activity at railroad level crossings, which in turns leads to additional vehicles congestion on Melbourne’s roads. This research investigates and proposes the introduction of Zonal Operations (ZO) in the Caulfield Group corridor that includes some of Melbourne’s longest and busiest lines within the rail network. The research discusses the concept of ZO, analyses the claim that ZO resolves capacity and overcrowding problems, a claim proposed in research literature. In addition, this research confirms that ZO has the potential to reduce the number of times boom gates are lowered at RLXs, and to mitigate road traffic congestion at RLXs. By doing this, a better understanding is gained in how ZO in railways can be used to mitigate road traffic congestion issues at RLX locations.

Scheduling local and express trains in suburban rail transit lines: Mixed–integer nonlinear programming and adaptive genetic algorithm

The aim of the train timetabling problem is to find a conflict free timetable for a set of passenger and freight trains along their routes in an infrastructure network. Several constraints like station capacities and train dependent running and headway times have to be satisfied. In this work we deal with large scale instances of the aperiodic train timetabling problem for the German railway network. The problem is modelled in a classical way via time discretised networks, its Lagrange-dual is solved by a bundle method. In order to handle the enormous number of variables and constraints dynamic graph generation and dynamic rolling horizon techniques are employed.

Wheel polygonal wear, especially high-order polygonal wear, has emerged as a significant challenge for Chinese railways over the past decade. The wheels of high-speed trains, locomotives and metro trains suffered from polygonal wear. Wheel out-of-roughness (OOR) of more than 43,000 wheels was collected in this study, including 30,500 high-speed train wheels, 9,136 metro wheels, and 3,396 locomotive wheels, which were measured in various measurement campaigns using high-precision wheel roughness instruments. The features of wheel OOR are analysed based on big-data and formulas for the wheel roughness spectrum of the three rolling stocks are determined. It is found that high-order wheel polygonal wear is a common problem in locomotives, metro trains, and high-speed trains. The OOR of metro wheels is more pronounced compared to that of locomotive and high-speed train wheels. There is a clear correlation between the high incidence period of high-order wheel polygonal wear and the circumference of the wheels, especially for high-speed wheels. The distribution of radial run-out and the peak roughness level of low- and high-order wheel OOR are also obtained. This paper provides statistically meaningful information that can be used to develop wheel maintenance strategies considering vibration and noise, fatigue reliability, and ground-borne vibration.

Today, about 59,000 km of specialised high-speed railway lines are in operation worldwide, about 20,000 km are under construction, and more than 50,000 km are planned to be commissioned. The maximum commercial speed of passenger trains has increased to 350 km/h. The world’s first high-speed freight trains have been designed and put into trial operation. Mastering advanced technologies in the field of high-speed railway transport, as before, is an indicator of the country’s development level. The construction of high-speed lines (HSL), along with others, solves an important problem on a global scale — it makes a significant contribution to environmental protection.We used the materials of reports and papers published on foreign information platforms; the results of the research work of Russian scientists and engineers in the field of increasing train speeds.In the BRICS countries, construction and design work on high-speed railways is underway, but given the unique conditions of each country, the pace of development is different. China is the leader of scientific progress in this sector of the railway industry, which attracts the attention of the world scientific community, including the Russian one.In Russia, according to the Transport Strategy up to 2030 with a forecast for the period up to 2035, it is envisaged to develop a network of high-speed railway lines with the unification of the largest agglomerations of the European part of the country into zones of two-hour accessibility.It is necessary to continue study and improve knowledge in the field of high-speed railway transport development.

With many train operating companies sharing limited capacity on the UK rail network, the train timetabling problem is complex and difficult to solve. This paper reports on a cooperative coevolutionary approach for the automatic generation of planning train timetables at the early stages of the timetabling process, when the main objective is to try to accommodate the bids as much as possible and to identify the major conflicts that need resolving by negotiations with the train operating companies. Some test experiments based on artificial problem instances as well as a real network are discussed.

A new method is proposed for single-track railway freight train timetable with two-stage solution of train scheduling problem. The method describes train scheduling problem in matrix with the "signaling block" concept. The matrix represents entire block occupancy of trains between inter-stations and internal-stations while decomposing individual train occupancy, making optimization method more flexible in design and use. The "two-stage solution" refers to that of train timetable with "conflict solution" and "timetable optimization." At the beginning, related data for trains are entered to build the initial timetable, which is then transferred and saved as the matrix format. All conflicts between interstations and internal-stations are located; solutions are made with manual scheduling to generate a feasible timetable. In the second stage, departure and stop time of freight trains, and passenger trains if necessary, are adjusted with Fuzzy system. Before optimization, storage is made in ascending amount of extra-time percent in freight train schedule. Execution is made subject to pre-ordered results during optimization for computer program acceleration of current manual spotting solution to find reasonable and feasible solution. The two-stage method also takes less time than the regular railway timetable design methods in cost saving of manual labor and providing higher operation performance and efficiency.

Fuzzy optimal schedule of high speed train operation to minimize energy consumption with uncertain delays and driver's behavioral response

Modeling the first train timetabling problem with minimal missed trains and synchronization time differences in subway networks

This study analyzes the impact of a high-speed rail line on tax revenues and on the economy of affected regions within the country. The economic impact of infrastructure investment can be induced by changes in tax revenues when the infrastructure is in operation. Accurate regional GDP data are not necessarily available in many Asian countries. However, tax data can be collected. Therefore, this study uses tax revenue dates in order to estimate spillover effects of infrastructure investment. The Kyushu high-speed rail line was constructed in 1991 and was completed in 2003. In 2004, the rail line started operating from Kagoshima to Kumamoto. The entire line was opened in 2011. We estimated its impact in the Kyushu region of Japan by using the differencein-difference method, and compared the tax revenues of regions along the high-speed railway line with other regions that were not affected by the railway line. Our findings show a positive impact on the region’s tax revenue following the connection of the Kyushu rapid train with large cities, such as Osaka and Tokyo. Tax revenue in the region significantly increased during construction in 1991–2003, and dropped after the start of operations in 2004–2010. The rapid train’s impact on the neighboring prefectures of Kyushu is positive. However, in 2004–2013, its impact on tax revenue in places farther from the rapid train was observed to be lower. When th Kyushu railway line was connected to the existing high-speed railway line of Sanyo, the situation changed. The study finds statistically significant and economically growing impact on tax revenue after it was completed and connected to other large cities, such as Osaka and Tokyo. Tax revenues in the regions close to the high-speed train is higher than in adjacent regions. The difference-in-difference coefficient methods reveal that corporate tax revenue was lower than personal income tax revenue during construction. However, the difference in corporate tax revenues rose after connectivity with large cities was completed. Public private partnership (PPP) has been promoted in many Asian countries. However, PPP-infrastructure in India failed in many cases due to the low rate of return from infrastructure investment. This study shows that an increase of tax revenues is significant in the case of the Kyushu rapid train in Japan. If half of the incremental tax revenues were returned to private investors in infrastructure, the rate of return from infrastructure investment would significantly rise for long period of time. It would attract stable and long-term private investors, such as pension funds and insurance funds into infrastructure investment. The last section of the paper will address how incremental tax revenues created by the spillover effects of infrastructure will improve the performance of private investors in infrastructure investment.

This paper presents a train scheduling and a rescheduling models based on the generation of an alternative graph of the railway network. In the first model, the train scheduling problem has been solved to define the optimal timetable for a set of trains with the objective to minimize the travel times of passengers to reach their destination, outlining the related sequence of nodes and arcs of the graph to be covered by each group of passengers. Subsequently, a train rescheduling model is applied on an optimal timetable became infeasible due to unpredicted failures or disturbances introduced on the network. In this second approach, the objective is restore the railway service quality by reducing the delays for trains and passengers. The main contribution of this paper is to implement railway scheduling and rescheduling problem by linear programming formulations introducing in the second approach the innovative concept to prioritize the train that can access on the block section in case of conflicts on the network. The performances of the solution methods have been tested on real train timetable data related to a portion of railway in Liguria Region, in Italy.

To evaluate the predictive power of risk model by combining traditional epidemiological factors and genetic factors. Our previous GWAS data of lung cancer in Chinese were used in training set (Nanjing and Shanghai: 1473 cases vs. 1962 control) and testing set (Beijing and Wuhan: 858 cases vs. 1 115 control). All the single nucleotide polymorphisms (SNPs) associated with lung cancer risk were systematically selected and stepwise logistic regression analysis was used to select independent factors in the training set. The wGRS (weighted genetic score) was further used to calculate genetic risk score. To evaluate the contribution of the genetic factors, 3 risk models were established by using the training set, i.e. smoking model (based on smoking status) , genetic risk model (based on genetic risk score) and combined model (based on smoke and genetic risk score). The predictability of the models were evaluated by the areas under the receiver operating characteristic (ROC) curves, area under curve (AUC), net reclassification improvement (NRI) and integrated discrimination index (IDI). Besides, the results were further verified in the testing set. In the training set, it was found that the AUC of the smoking, genetic risk and combined models were 0.65 (0.63-0.66), 0.60 (0.59-0.62) and 0.69 (0.67-0.71), respectively. Compared with combined model, the predictive power of other two models significantly declined, the difference was statistically significant (P<0.001). Furthermore, compared with the smoking model, the NRI of the combined model increased by 4.57% (2.23%-6.91%) and IDI increased by 3.11% (2.52%-3.69%) in the training set, the difference was statistically significant (P<0.001). Similarly, in the testing set NRI increased by 2.77%, the difference was not statistically significant (P=0.069) , and IDI increased by 3.16%, the difference was statistically significant (P<0.001). This study showed that combining 14 genetic variants with traditional epidemiological factors could improve the predictive power of risk model for lung cancer. The model could be used in the screening of high-risk population of lung cancer in Chinese and provide evidence for the early diagnosis and treatment of lung cancer.

In recent years several long-span bridges have been constructed and put into service in China's high-speed railway lines. These bridges usually cross the major rivers of China which serve as vital shipping channels. The long-span structure becomes the superior and sometimes even sole scheme to carry high-speed tracks over the rivers without impacting the water transportation at the bridge site. High-speed trains require stable and smooth geometries of the tracks on long-span bridges to achieve successful and safe passages. Nevertheless, the above mentioned track geometries can be threatened by multiple stressors, e.g., high-speed trains, wind, temperature, among others. Structural health monitoring (SHM) systems have been applied to the long-span bridges, aiming to collect real-time information about both the stressors and structure responses. This information can be used to investigate the performance of bridge structures, and eventually to ensure the running safety of high-speed trains. In this context, the present paper examines the acceleration responses of a long-span steel arch bridge, i.e., the Nanjing Dashengguan Yangtze River Bridge, under operating high-speed train loads. This unique long-span railway bridge and its SHM system are introduced. A coupled dynamic model of the high-speed vehicle and b ridge structure system is subsequently developed. Acceleration responses at the typical locations resulting from the coupled dynamic analysis are compared to the SHM data. It is found that at several specific velocity values the maximum accelerations of the bridge produce respective peaks through the parametric study on train speeds. This interesting phenomenon calls for more detailed investigation on the concerned topic in the future.

An integrated energy-efficient and transfer-accessible model for the last train timetabling problem