高铁车站接发车不均衡性分析

高速铁路车站接发车的不均衡性对高速铁路资源设备的合理分配具有重要影响。本文在对高铁车站的技术作业进行分析的基础上，对高铁车站接发车不均衡性进行了分析，结合经济学领域的泰尔指数计算方法，融合运输领域的时间与接发车数指标，提出了高铁车站接发车不均衡性的计算方法，用来描述车站一天内不同时段列车到达与出发的分布情况。实例计算得出到发场A接发车不均衡度为0.157，组间差距为0.092，组内差距为0.065，组间贡献率58.60%，组内贡献率为41.40%。可知到发场A接发车不均衡度较小，且到发场A的接发车不均衡主要体现在不同的接发车方向之间的不均衡。     

基于AHP-广义模糊软集的列车运行图评价

本文从列车速度、服务水平、鲁棒性、弹性及列车运行水平5个方面，构建列车运行图质量评价指标体系，通过AHP计算各指标权重，构建广义模糊软集模型确定列车运行图综合得分系数,实现列车运行图编制质量评估。为了对算法效果进行验证，以徐盐、连淮铁路网络中京沪高铁南京南至徐州东段、徐兰高铁徐州东至商丘郑徐场段、青盐铁路青岛北至连云港段三条线路为例进行运行图质量评价。结果表明,京沪高铁南京南至徐州东段的运行图综合质量最好，青盐铁路青岛北至连云港段运行图综合质量最差。     

蒙内铁路长大下坡道制动试验及计算分析

蒙内铁路作为连接东非第一大港蒙巴萨和肯尼亚首都内罗毕的一条客货并行一级线路,对肯尼亚国内以及东非地区的经济发展和政治稳定具有重要的意义,也对于我国"一带一路"战略的实施以巩固中-肯关系和中非关系有着至关重要的意义.由于较为特殊的地理原因使得蒙内铁路全线长大坡道占比超过50％,使得长大坡道上的行车安全成为蒙内铁路安全运营的重中之重.本文以11.7‰的长大下坡道为研究对象,介绍了以DF11机车牵引,17辆编组时以118km/h进行紧急制动试验的情况,制动距离为890m;紧急制动前有充足的充风时间,制动实施至列车管压减为0用时3s,符合规定要求.基于试验结果验证了理论计算和软件计算的可靠性和准确性,计算结果指出为了使17辆编组列车在800m制动距离以内完成制动,当坡度为12‰时,建议其制动速度不高于112km/h,坡度6‰以下时,建议其制动速度不高于118km/h.本文的分析和计算结果旨在为蒙内铁路长大下坡道的安全行车运营以及整体安全控制体系的制定提供有效可靠的试验依据和理论支撑.     

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.     

Balancing energy consumption and risk of delay in high speed trains: A three-objective real-time eco-driving algorithm with fuzzy parameters

Eco-driving is an energy efficient traffic operation measure that may lead to important energy savings in high speed railway lines. When a delay arises in real time, it is necessary to recalculate an optimal driving that must be energy efficient and computationally efficient.In addition, it is important that the algorithm includes the existing uncertainty associated with the manual execution of the driving parameters and with the possible future traffic disturbances that could lead to new delays.This paper proposes a new algorithm to be executed in real time, which models the uncertainty in manual driving by means of fuzzy numbers. It is a multi-objective optimization algorithm that includes the classical objectives in literature, running time and energy consumption, and as well a newly defined objective, the risk of delay in arrival. The risk of delay in arrival measure is based on the evolution of the time margin of the train up to destination.The proposed approach is a dynamic algorithm designed to improve the computational time. The optimal Pareto front is continuously tracked during the train travel, and a new set of driving commands is selected and presented to the driver when a delay is detected.The algorithm evaluates the 3 objectives of each solution using a detailed simulator of high speed trains to ensure that solutions are realistic, accurate and applicable by the driver. The use of this algorithm provides energy savings and, in addition, it permits railway operators to balance energy consumption and risk of delays in arrival. This way, the energy performance of the system is improved without degrading the quality of the service.     

Nonlinear programming methods based on closed-form expressions for optimal train control

This paper proposes a novel approach to solve the complex optimal train control problems that so far cannot be perfectly tackled by the existing methods, including the optimal control of a fleet of interacting trains, and the optimal train control involving scheduling. By dividing the track into subsections with constant speed limit and constant gradient, and assuming the train’s running resistance to be a quadratic function of speed, two different methods are proposed to solve the problems of interest. The first method assumes an operation sequence of maximum traction – speedholding – coasting – maximum braking on each subsection of the track. To maintain the mathematical tractability, the maximum tractive and maximum braking functions are restricted to be decreasing and piecewise-quadratic, based on which the terminal speed, travel distance and energy consumption of each operation can be calculated in a closed-form, given the initial speed and time duration of that operation. With these closed-form expressions, the optimal train control problem is formulated and solved as a nonlinear programming problem. To allow more flexible forms of maximum tractive and maximum braking forces, the second method applies a constant force on each subsection. Performance of these two methods is compared through a case study of the classic single-train control on a single journey. The proposed methods are further utilised to formulate more complex optimal train control problems, including scheduling a subway line while taking train control into account, and simultaneously optimising the control of a leader-follower train pair under fixed- and moving-block signalling systems.     

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。     

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.     

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.     

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.     

Reasonable scheduling for arrival–departure track operations in railway stations

We analyze the train types handled at a section station and the factors affecting the scheduling of the arrival–departure track operation, using the following conditions as our optimization goals: operating the arrival–departure tracks in accordance with a fixed operation scheme, and reducing the influence which the departing–receiving operations impose on shunting operations. We establish a 0–1 integer programming model for formulating a track operation plan. By applying modern sequencing theory, this is transformed into a fixed sequencing model of special parallel machines. We then design a heuristic algorithm to solve the model. Finally, the example of Yiyang railway station is used to verify the advantages of the model and the algorithm. A better operation plan is obtained using MATLAB 7.0 by applying the model and the algorithm provided in the paper, indicating the superiority of our study’s approach.     

The train platforming problem: The infrastructure management company perspective

If railway companies ask for station capacity numbers, their underlying question is in fact one about the platformability of extra trains. Train platformability depends not only on the infrastructure, buffer times, and the desired departure and arrival times of the trains, but also on route durations, which depend on train speeds and lengths, as well as on conflicts between routes at any given time. We consider all these factors in this paper. We assume a current train set and a future one, where the second is based on the expected traffic increase through the station considered. The platforming problem is about assigning a platform to each train, together with suitable in- and out-routes. Route choices lead to different route durations and imply different in-route-begin and out-route-end times. Our module platforms the maximum possible weighted sum of trains in the current and future train set. The resulting number of trains can be seen as the realistic capacity consumption of the schedule. Our goal function allows for current trains to be preferably allocated to their current platforms.Our module is able to deal with real stations and train sets in a few seconds and has been fully integrated by Infrabel, the Belgian Infrastructure Management Company, in their application called Ocapi, which is now used to platform existing and projected train sets and to determine the capacity consumption.     

瓮马铁路南北延伸线引入都匀地区方案研究

通过分析都匀地区既有铁路现状及规划铁路,结合瓮马铁路货物流向,提出了瓮马铁路南延线引入黔桂线的必要性。结合都匀地区地形、城市规划和自然保护区范围,研究了瓮马铁路在黔桂线的前方站(都匀北站)或黔桂线绿荫湖站设置交接场引入都匀地区的方案,考虑到运营管理分解划分明确,减少折角运输,一次性建成南北直通通道,吸引国铁直通车流等因素,宜采用设置都匀北站交接场的方案。根据线路引入既有黔桂线接轨点的不同,对双线区间接轨方案、新都匀站站房同侧引入方案和新都匀站站房对侧引入方案进行分析,从工程量、工程投资、运输组织、施工难度及风险、投资建设模式等方面比较,得出双线区间接轨引入都匀地区方案最优。