Multiple-phase train trajectory optimization with signalling and operational constraints

The train trajectory optimization problem aims at finding the optimal speed profiles and control regimes for a safe, punctual, comfortable, and energy-efficient train operation. This paper studies the train trajectory optimization problem with consideration of general operational constraints as well as signalling constraints. Operational constraints refer to time and speed restrictions from the actual timetable, while signalling constraints refer to the influences of signal aspects and automatic train protection on train operation. A railway timetable provides each train with a train path envelope, which consists of a set of positions on the route with a specified target time and speed point or window. The train trajectory optimization problem is formulated as a multiple-phase optimal control model and solved by a pseudospectral method. This model is able to capture varying gradients and speed limits, as well as time and speed constraints from the train path envelope. Train trajectory calculation methods under delay and no-delay situations are discussed. When the train follows the planned timetable, the train trajectory calculation aims at minimizing energy consumption, whereas in the case of delays the train trajectory is re-calculated to track the possibly adjusted timetable with the aim of minimizing delays as well as energy consumption. Moreover, the train operation could be affected by yellow or red signals, which is taken into account in the train speed regulation. For this purpose, two optimization policies are developed with either limited or full information of the train ahead. A local signal response policy ensures that the train makes correct and quick responses to different signalling aspects, while a global green wave policy aims at avoiding yellow signals and thus proceed with all green signals. The method is applied in a case study of two successive trains running on a corridor with various delays showing the benefit of accurate predictive information of the leading train on energy consumption and train delay of the following train.     

动卧客运与快递货运的高速铁路夜间能力利用模式

目前我国高速铁路的日间行车能力已得到了较为充分的利用,而如何组织好高铁夜间垂直天窗与夜行列车之间的耦合关系、用好高铁夜间能力,是适应多样化市场需求的需要,也是进一步提升高铁经营效益的有效途径。对此,本文提出了动卧列车和货运动车组两种相对可行的高铁夜间运输产品,分别对其产品特征进行了分析,充分考虑高铁夜间天窗制约下两种列车的开行模式,基于市场需求提出了列车开行策略,并在充分对比两种产品的经济效益、客(货)源组织、能力分配等因素的基础上,给出了高铁夜间能力发展建议。     

Development and Impact of the Modern High‐speed Train: A Review

Abstract

The inauguration of the Shinkansen high‐speed train service between Tokyo and Osaka, Japan, at 210 kph maximum operating speed some 40 years ago marked the comeback of the train as an important passenger mode of transport. Since then high‐speed train (HST) services have been introduced in many countries and are planned in many more, and the train has once more become the dominant mode of transport on many routes. This review summarizes the different elements of HST operation with the aim of characterizing HST operation and putting in context its impact in terms of what it is best designed for and what it can deliver. The review concludes that the HST is best designed to substitute conventional railway services on routes where much higher capacity is required and to reduce travel time, further improving the railway service, also against other modes, therefore leading to mode substitution. However, the high investment in HST infrastructure could not be justified based on its economic development benefits since these are not certain. Finally, the following definition for HST services is suggested: high capacity and frequency railway services achieving an average speed of over 200 kph.     

Characterizing European high speed train stations using intermodal time and entropy metrics

This paper presents a quantitative method for characterizing high speed train stations in terms of passenger intermodality. The aim of the procedure is two-fold: firstly, the method is to be used as an objective measure for comparing stations in order to detect suboptimal points and improve the performance of stations as nodal points; secondly, the method provides a means to embed intermodality into regional accessibility models, allowing comprehensive modelling at lower scales. The empirical base of the work comprises data from 27 European high speed rail stations, which is deemed an appropriate statistical sample for the whole European rail network. Using the entropy metric, we found that several different patterns emerged: there was a clear hierarchy of stations which was linked to their respective roles within the system, while strong constraints impeded stations from performing optimally as true intermodal nodes.     

Characterisation of and reflections on the synergy of bicycles and public transport

The bicycle is often understood as a disjointed ‘feeder’ mode that provides access to public transport. We argue that combined use of the bicycle and public transport should be understood in a broader perspective, especially where bicycles link to higher speed and higher capacity public transport, such as the train. Cycling and public transport can have a symbiotic relationship forming a hybrid, distinct transport mode, which should be reflected in transport planning. The bicycle is as a way to soften the rigid nature of public transport and thus accommodate diverse individual travel needs and situations. Public transport can be seen as a means to dramatically extend cycling’s speed and spatial reach. We combine a system perspective with conceptual analysis to explore how, why and when this reconsideration is important. We use the Netherlands as illustrative case because of the relative maturity of its bicycle–train connections. The case shows that the synergy between rather opposite yet highly complementary aspects, high speed of the train, high accessibility of the bicycle and flexibility in combining both sub-modes, are the fundamental characteristics to understand the functioning of this system in a wider spatial context. In our conclusion we propose a research agenda, to further explore the relevance of this system for land-use and transport planning and distil wider implications for the international debate.     

Transportation and regional agglomeration in Japan: Through a long-term simulation model 1920–85

The present article reviews the effects of wartime and post-war policies on regional agglomeration of landuse and transportation activities in Japan. For this purpose the authors have formulated a long-term model over the period 1920–85, and conducted its final test. After confirming the accuracy of the entire model, it is used to evaluate the wartime policies which caused excessive employment agglomeration in Tokyo, and post-war policies concerning the high speed Shinkansen rail network. We conclude that the choices of alternative policies would have led to a more balanced regional structure than there is now, with less agglomeration in both Tokyo and the Kanto region.     

Financial lessons from Asian experience in constructing and operating high speed train networks

A serious interest in high speed train has been increasing all over the world. However, recent experiences in Asian countries show that high speed rail projects are not financially viable even in areas seemingly favorable to rail operations. Considering the existing intensive highway and airline network, putting public subsidies to high speed rail projects are barely justifiable from a purely economic point of view. What is required of any government which contemplates high speed rail construction as a policy option is to show taxpayers the cost/revenues difference between constructing a high speed rail line and expanding a capacity of other means, before proceeding.     

Solving network equilibrium problems on multimodal urban transportation networks with multiple user classes

The capacity of the high‐speed train to compete against travel demand in private vehicles is analysed. A hypothetical context analysed as the high‐speed alternative is not yet available for the route studied. In order to model travel demand, experimental designs were applied to obtain stated preference information. Discrete choice logit models were estimated in order to derive the effect of service variables on journey utility. From these empirical demand models, it was possible to predict for different travel contexts and individuals the capacity of the high‐speed train to compete with the car, so determining the impact of the new alternative on modal distribution. Furthermore, individual willingness to pay for travel time saving is derived for different contexts. The results allow us to confirm that the high‐speed train will have a significant impact on the analysed market, with an important shift of passengers to the new rail service being expected. Different transport policy scenarios are derived. The cost of travel appears to a great extent to be a conditioning variable in the modal choice. These results provide additional evidence for the understanding of private vehicle travel demand.     

Energy-efficient operation of rail vehicles

This paper describes an analytical process that computes the optimal operating successions of a rail vehicle to minimize energy consumption. Rising energy prices and environmental concerns have made energy conservation a high priority for transportation operations. The cost of energy consumption makes up a large portion of the Operation and Maintenance (O&M) costs of transit especially rail transit systems. Energy conservation or reduction in energy cost may be one of the effective ways to reduce transit operating cost, therefore improve the efficiency of transit operations.From a theoretical point of view, the problem of energy efficient train control can be formulated as one of the functions of Optimal Control Theory. However, the classic numerical optimization methods such as discrete method of optimum programming are too slow to be used in an on-board computer even with the much improved computation power, today. The contribution of this particular research is the analytical solution that gives the sequence of optimal controls and equations to find the control change points. As a result, a calculation algorithm and a computer program for energy efficient train control has been developed. This program is also capable of developing energy efficient operating schedules by optimizing distributions of running time for an entire route or any part of rail systems.We see the major application of the proposed algorithms in fully or partially automated Train Control Systems. The modern train control systems, often referred as “positive” train control (PTC), have collected a large amount of information to ensure safety of train operations. The same data can be utilized to compute the optimum controls on-board to minimize energy consumption based on the algorithms proposed in this paper. Most of the input data, such as track plan, track profile, traction and braking characteristics, speed limits and required trip time are located in an on-board database and/or they can be transmitted via radio link to be processed by the proposed algorithm and program.     

Integrating capacity analysis with high-speed railway timetabling: A minimum cycle time calculation model with flexible overtaking constraints and intelligent enumeration

Compared with most optimization methods for capacity evaluation, integrating capacity analysis with timetabling can reveal the types of train line plans and operating rules that have a positive influence on improving capacity utilization as well as yielding more accurate analyses. For most capacity analyses and cyclic timetabling methods, the cycle time is a constant (e.g., one or two hours). In this paper, we propose a minimum cycle time calculation (MCTC) model based on the periodic event scheduling problem (PESP) for a given train line plan, which is promising for macroscopic train timetabling and capacity analysis. In accordance with train operating rules, a non-collision constraint and a series of flexible overtaking constraints (FOCs) are constructed based on variations of the original binary variables in the PESP. Because of the complexity of the PESP, an iterative approximation (IA) method for integration with the CPLEX solver is proposed. Finally, two hypothetical cases are considered to analyze railway capacity, and several influencing factors are studied, including train regularity, train speed, line plan specifications (train stops), overtaking and train heterogeneity. The MCTC model and IA method are used to test a real-world case involving the timetable of the Beijing–Shanghai high-speed railway in China.     

Train boarding and alighting rates at high passenger loads

Line capacity in metro and high‐frequency suburban railways is as much determined by station stop times as by factors such as line speed or train acceleration. This paper applies the method developed by London Underground to estimate the time that trains spend at stations, as a function of the physical characteristics of the situation (e.g. train door width) and the numbers of passengers involved. Analysis was carried out on a number of alternative designs for refurbishment of South West Trains' Class 455 inner‐suburban rolling stock. Whilst there is indeed an interaction between boarding and alighting passengers, this paper demonstrates that the LUL relationship breaks down at the highest passenger loads. Moreover, results indicate that passenger flow is not equal between different parts of the same group of boarders or alighters.     

A hierarchical line planning approach for a large-scale high speed rail network: The China case

Planning a set of train lines in a large-scale high speed rail (HSR) network is typically influenced by issues of longer travel distance, high transport demand, track capacity constraints, and a non-periodic timetable. In this paper, we describe an integrated hierarchical approach to determine line plans by defining the stations and trains according to two classes. Based on a bi-level programming model, heuristics are developed for two consecutive stages corresponding to each classification. The approach determines day-period based train line frequencies as well as a combination of various stopping patterns for a mix of fast trunk line services between major stations and a variety of slower body lines that offer service to intermediate stations, so as to satisfy the predicted passenger transport demand. Efficiencies of the line plans described herein concern passenger travel times, train capacity occupancy, and the number of transfers. Moreover, our heuristics allow for combining many additional conflicting demand–supply factors to design a line plan with predominantly cost-oriented and/or customer-oriented objectives. A range of scenarios are developed to generate three line plans for a real-world example of the HSR network in China using a decision support system. The performance of potential train schedules is evaluated to further examine the feasibility of the obtained line plans through graphical timetables.     

High-Speed Rail Operations on an Existing Network: An Assessment Model for China

High-speed rail operations have the potential to reduce the long-term decline in rail passenger travel demand for the medium to long distance inter-urban markets. Such decline has been evident through most of the industrialized countries where air and road transport tend to be the dominant modes. In China, the operations of long distance high-speed rail on fully dedicated track is not very easy to implement, due to the high proportion of passengers who travel between high-speed and conventional railways. An alternative approach would be to allow for mixed operations with trains of various speeds on the same track. This article puts forward a simulation model designed to allow an evaluation of the most efficient distance for high-speed rail operations under mixed train speed scenarios. The model takes into account the main operating parameters such as passenger volumes, train speeds, capital and maintenance costs, train operating costs and energy consumption. The distance of high-speed train running on conventional rail that will yield the most economic benefit can be estimated using the model. The article includes the results of using the model for a specific example. It is concluded that large-scale high-speed trains have the potential to be successfully operated on conventional rail networks.     

Express guideway transit: A case for further development in transit automation

Safe and reliable coupling and decoupling of cars from a moving train is feasible with further developments in linear motor propulsion and control of transit vehicles. This allows the last car of a train to decouple and stop at a station for a relative long dwell time, before it accelerates and is coupled to a following train. Controlled doors in front and rear of the transit vehicle permit passengers to walk through the train to the car which stops at their destination. A proposed transit system using these features is described and compared to Bombardier's Advanced Rapid Transit. Potential advantages are high schedule speed, uncrowded trains, smaller and more stations, low energy requirements and a smaller vehicle fleet.     

Reinforcement learning approach for train rescheduling on a single-track railway

Optimal rail network infrastructure and rolling stock utilization can be achieved with use of different scheduling tools by extensive planning a long time before actual operations. The initial train timetable takes into account possible smaller disturbances, which can be compensated within the schedule. Bigger disruptions, such as accidents, rolling stock breakdown, prolonged passenger boarding, and changed speed limit cause delays that require train rescheduling. In this paper, we introduce a train rescheduling method based on reinforcement learning, and more specifically, Q-learning. We present here the Q-learning principles for train rescheduling, which consist of a learning agent and its actions, environment and its states, as well as rewards. The use of the proposed approach is first illustrated on a simple rescheduling problem comprising a single-lane track with three trains. The evaluation of the approach is performed on extensive set of experiments carried out on a real-world railway network in Slovenia. The empirical results show that Q-learning lead to rescheduling solutions that are at least equivalent and often superior to those of several basic rescheduling methods that do not rely on learning agents. The solutions are learned within reasonable computational time, a crucial factor for real-time applications.     

Coordinated cruise control for high-speed train movements based on a multi-agent model

This paper investigates the coordinated cruise control strategy for multiple high-speed trains’ movement. The motion of an ordered set of high-speed trains running on a railway line is modeled by a multi-agent system, in which each train communicates with its neighboring trains to adjust its speed. By using the potential fields and LaSalles invariance principle, we design a new coordinated cruise control strategy for each train based on the neighboring trains’ information, under which each train can track the desired speed, and the headway distances between any two neighboring trains are stabilized in a safety range. Numerical examples are given to illustrate the effectiveness of the proposed methods.     

Analyzing passenger train arrival delays with support vector regression

We propose machine learning models that capture the relation between passenger train arrival delays and various characteristics of a railway system. Such models can be used at the tactical level to evaluate effects of various changes in a railway system on train delays. We present the first application of support vector regression in the analysis of train delays and compare its performance with the artificial neural networks which have been commonly used for such problems. Statistical comparison of the two models indicates that the support vector regression outperforms the artificial neural networks. Data for this analysis are collected from Serbian Railways and include expert opinions about the influence of infrastructure along different routes on train arrival delays.     

Passenger rail in North America in the light of developments in Western Europe and Japan

Because of different geo‐demographic and economic conditions, the impact of the new passenger modes (road and air) on rail travel was much larger in North America than in Europe. In 1960s and 1970s, as the railway share of intercity traffic in North America shrunk to a negligible one or two percent, the passenger trains were abandoned by private railway companies and taken over by state organizations, which have continued to operate traditional trains and generate mounting losses. On the technology side, no attempts have been made to improve competitiveness of trains vis‐a‐vis automobiles and airplanes.

In Europe and Japan, the railways responded to the challenge by (i) upgrading the performance (speed) and comfort of traditional trains operating on existing tracks and (ii) developing trains which could, on short and intermediate range distances, compete successfully, in terms of speed and economy, with the road and air modes. The Japanese (Shinkansen trains) and French (TGV trains) experience clearly shows that trains operating on dedicated lines at average speeds of 150 to 200 km/hr provide a superior transportation service and economy on high‐traffic intercity routes of up to about 500 km length. In this paper the factors responsible for the present status of passenger rail in North America are analysed, the current policies in the U.S. and Canada are evaluated in the light of experience to date and developments abroad, and suggestions for a long‐term passenger rail policy are made. This includes examination of (i) the viability of continued subsidization of traditional train services, (ii) the viability of operation of faster trains on existing tracks, (iii) the scope for introduction of modern, fast trains on dedicated lines in high‐density, intercity corridors, (iv) the application of fast trains as access to major airports and integration of airports with fast intercity lines, and (v) the impact of energy (oil) consumption in transportation.

     

A simulation model of train travel on a rail transit line

A simplified simulation model for the operational analysis of a rail rapid transit train is presented. The model simulates the movement of a train along a route, and develops the relationships of time—distance, time—speed and distance—speed. The inputs to the model are the profile of speed limits and the dynamic characteristics of the train. Without the information on the track geometry and tractive effort, the model determines the speed of the train at a location based on the previous and future speed limits relative to the location. It was found that the model can fairly accurately simulate the relationship between travel time and distance. A comparison of the train travel times between the actual and simulated runs is presented. Because of the simplicity of input and calculation method, the model can be a useful tool for the “desk-top” analysis of frequently occurring planning problems of a commuter rail or rail rapid transit line, such as the impacts of changes in speed limits, station locations, station stopping policy, addition/elimination of stations, and types of rail cars.