High-Speed Trains Automatic Operation with Protection Constraints: A Resilient Nonlinear Gain-based Feedback Control Approach

This paper addresses the control design for automatic train operation of high-speed trains with protection constraints.A new resilient nonlinear gain-based feedback control approach is proposed,which is capable of guaranteeing,under some proper non-restrictive initial conditions,the protection constraints control raised by the distance-to-go(moving authority)curve and automatic train protection in practice.A new hyperbolic tangent function-based model is presented to mimic the whole operation process of high-speed trains.The proposed feedback control methods are easily implementable and computationally inexpensive because the presence of only two feedback gains guarantee satisfactory tracking performance and closed-loop stability,no adaptations of unknown parameters,function approximation of unknown nonlinearities,and attenuation of external disturbances in the proposed control strategies.Finally,rigorous proofs and comparative simulation results are given to demonstrate the effectiveness of the proposed approaches.

Automatic Driving Operation Strategy of Urban Rail Train Based on Improved DQN Algorithm

To realize a better automatic train driving operation control strategy for urban rail trains,an automatic train driving method with improved DQN algorithm(classical deep reinforcement learning algorithm)is proposed as a research object.Firstly,the train control model is established by considering the train operation requirements.Secondly,the dueling network and DDQN ideas are introduced to prevent the value function overestimation problem.Finally,the priority experience playback and“restricted speed arrival time”are used to reduce the useless experience utilization.The experiments are carried out to verify the train operation strategy method by simulating the actual line conditions.From the experimental results,the train operation meets the ATO requirements,the energy consumption is 15.75%more energy-efficient than the actual operation,and the algorithm convergence speed is improved by about 37%.The improved DQN method not only enhances the efficiency of the algorithm but also forms a more effective operation strategy than the actual operation,thereby contributing meaningfully to the advancement of automatic train operation intelligence.

JR East aims for driverless Shinkansen operation

East Japan Railway Company(JR East)is aiming to“realize driverless train operation”as one of the key measures to respond to rapid changes in the business environment.Currently,Automatic Train Operation(ATO)equipment is not installed on the Shinkansen,but there are plans to introduce ATO or driverless operation in the near future.From 2018-2021,the Ministry of Land,Infrastructure,Transport and Tourism(MLIT)held the“ATO Technology Study Group for Railways”in which the concept of technical requirements necessary for driverless operation was discussed.In 2021,JR East conducted the GOA4 demonstration test on the Joetsu Shinkansen.In this test,we were able to confirm the basic functions of Shinkansen vehicles such as automatic departure control,speed control,fixed position stop control,and remote stop control using ATO.We aim to realize unattended operation(GOA4)for deadhead trains between Niigata Station and the Niigata Shinkansen Rolling Stock Center by the end of the 2020 s,and driverless operation(GOA3)for passenger trains of the Joetsu Shinkansen by the mid-2030s and continue to develop the necessary technologies and build systems.

Energy Saving for Automatic Train Control in Moving Block Signaling System

With rapid development of the railway traffic, the moving block signaling system （MBS） method has become more and more important for increasing the track capacity by allowing trains to run in a shorter time-headway while maintaining the required safety margins. In this framework, the tracking target point of the following train is moving forward with its leading train. This paper focuses on the energy saving tracking control of two successive trains in MBS. Nonlinear programming method is used to optimize the energy-saving speed trajectory of the following train. The real-time location of the leading train could be integrated into the optimization process. Due to simplicity, it can be used for online implementation. The feasibility and effectiveness are verified through simulation. The results show that the new method is efficient on energy saving even when disturbances present.

Research on Multi-Objective Real-Time Optimization of Automatic Train Operation(ATO) in Urban Rail Transit

The determination and optimization of Automatic Train Operation(ATO) control strategy is one of the most critical technologies for urban rail train operation. The practical ATO optimal control strategy must consider many goals of the train operation, such as safety, accuracy, comfort, energy saving and so on. This paper designs a set of efficient and universal multi-objective control strategy. Firstly, based on the analysis of urban rail transit and its operating environment, the multi-objective optimization model considering all the indexes of train operation is established by using multi-objective optimization theory. Secondly, Non-dominated Sorting Genetic Algorithm II(NSGA-II) is used to solve the model, and the optimal speed curve of train running is generated.Finally, the intelligent controller is designed by the combination of fuzzy controller algorithm and the predictive control algorithm, which can control and optimize the train operation in real time. Then the robustness of the control system can ensure and the requirements for multi-objective in train operation can be satisfied.

改进麻雀算法在列车ATO多目标优化中的应用

针对列车自动驾驶(ATO)运行过程多目标优化问题,以列车运行安全性、列车动力学模型等因素为约束条件,考虑列车准时性、能耗、舒适性等指标,使用模糊隶属度法建立多目标优化模型。利用罚函数处理约束条件,将停车误差与限速作为惩罚项并构造出适当的惩罚函数加入到目标函数中,从而得到增广目标函数,提出基于改进麻雀算法(ISSA)的求解策略。为提高麻雀算法(SSA)的全局寻优能力,避免收敛于局部最优,引入Logistic映射、自适应超参数、变异算子对传统麻雀算法进行改进,通过测试函数对算法性能进行验证,表明ISSA算法的收敛速度、寻优精度比传统SSA算法好。以工况转换点为决策变量,通过ISSA算法对工况转换点的位置及速度进行寻优,进而获得目标速度-距离曲线。最后选取城轨车辆参数与线路数据进行仿真验证,仿真结果表明:所提优化策略相较于未优化前,舒适性提高了21.22%,能耗降低了22.41%,准时性与停车误差满足要求;与PSO优化方法相比,收敛速度更快,运行时间几乎一样的情况下能耗降低了12.74%,节能效果更佳;停车误差降低了20.45%,舒适性保持在舒适范围之内;对于速度-距离曲线,巡航距离更长、惰行距离变短、最高运行速度降低。由此可见,达到了综合优化ATO的目的,验证了ISSA优化策略的有效性。

Research on Optimization of Freight Train ATO Based on Elite Competition Multi-Objective Particle Swarm Optimization

In view of the complex problems that freight train ATO (automatic train operation) needs to comprehensively consider punctuality, energy saving and safety, a dynamics model of the freight train operation process is established based on the safety and the freight train dynamics model in the process of its operation. The algorithm of combining elite competition strategy with multi-objective particle swarm optimization technology is introduced, and the winning particles are obtained through the competition between two elite particles to guide the update of other particles, so as to balance the convergence and distribution of multi-objective particle swarm optimization. The performance comparison experimental results verify the superiority of the proposed algorithm. The simulation experiments of the actual line verify the feasibility of the model and the effectiveness of the proposed algorithm.

Braking distance prediction for vehicle consist in low-speed on-sight operation:a Monte Carlo approach

The first and last mile of a railway journey, in both freight and transit applications, constitutes a high effort and is either non-productive(e.g. in the case of depot operations) or highly inefficient(e.g. in industrial railways). These parts are typically managed on-sight, i.e. with no signalling and train protection systems ensuring the freedom of movement. This is possible due to the rather short braking distances of individual vehicles and shunting consists. The present article analyses the braking behaviour of such shunting units. For this purpose, a dedicated model is developed. It is calibrated on published results of brake tests and validated against a high-definition model for lowspeed applications. Based on this model, multiple simulations are executed to obtain a Monte Carlo simulation of the resulting braking distances. Based on the distribution properties and established safety levels, the risk of exceeding certain braking distances is evaluated and maximum braking distances are derived. Together with certain parameters of the system, these can serve in the design and safety assessment of driver assistance systems and automation of these processes.

珠三角城际CTCS2+ATO列控系统控车舒适性研究及案例分析

针对珠三角城际线上CRH6A-0405动车组装备的CTCS2-200K+ATO列控车载设备,在控制列车减速进站过程中舒适性欠佳问题,研究ATO系统的工作原理及其控车策略、ATO系统所使用的PID滑模控制器及其模型和相关参数,以及ATO系统控车舒适性的评价指标及影响因素。对列车进站进入降速区前存在异常加速而导致的冲击率过大问题,采取降低列车高速运行时的滑模增益系数避免控制命令饱和的优化方案;对站前减速过程速度与距离采用线性关系导致减速过程不平稳问题,提出将速度与距离关系按照二次函数进行映射的优化方案。现场验证表明:优化后的速度曲线更加平滑,减速过程更加连贯平稳。

基于CTCS2+ATO的市域铁路列车追踪间隔时间研究

基于CTCS2+ATO的市域铁路,综合考虑列车长度、运行速度、列车类型、道岔限速、到发线布置、信号系统、车载ATP控车模型、车站作业时间等因素影响,对列车区间追踪间隔、车站追踪间隔和折返追踪间隔进行研究计算,为系统设计能力指标、相关工程行车组织设计和列车运行图编制提供理论研究支撑。

南京地铁6号线ATO+方案研究

为推进南京智慧城轨的建设发展,提高列车运行智能化程度,在南京地铁6号线建设时期提出设计变更,将既有机场线与宁溧线同步进行改造:提出ATO+方案,即在既有系统功能基础上增加ATO+驾驶模式,以实现部分自动功能;参照全自动运行模式,提出ATO+方案的8个运营场景。该方案涉及既有线信号系统、车辆系统、站台门系统的改造:信号系统改造车载硬件和软件,增加ATO+驾驶模式,轨旁信号系统升级软件兼容不同配置功能的列车混合运行;车辆系统改造与信号系统的接口电路,增加列车控制线,实现ATO+驾驶模式下的列车控制;站台门系统增加站台门与车门间防夹探测功能。具体实施兼顾改造前、后列车的混合运行,以保证改造过渡期不影响列车的正常运营。ATO+方案的实施,可以大大减少司机的干预,提升行车自动化程度和运营效率,为后续类似线路建设和既有线升级改造提供参考。

城市轨道交通线路列车ATO运行曲线分析及整改措施

城市轨道交通作为一种准时速达、舒适安全的大运量交通方式,不仅能够高效实现旅客的中转距离周转,还能切实满足城市日常的交通运输需求,这一特点使得城市轨道交通在科技的作用下越发趋向于全自动化发展。但在运行的过程中仍然存有一定的问题,并从列车运行曲线中得以显现。基于此,本文以此为要点对城市轨道交通线路列车ATO运行曲线进行深度分析,并结合实际问题制定有效的整改措施,以此来提高城市轨道交通线路列车自动化运行的安全性与稳定性。

Automatic Train Operation Based on Adaptive Terminal Sliding Mode Control

This paper presents an adaptive terminal sliding mode control(ATSMC) method for automatic train operation. The criterion for the design is keeping high-precision tracking with relatively less adjustment of the control input. The ATSMC structure is designed by considering the nonlinear characteristics of the dynamic model and the parametric uncertainties of the train operation in real time. A nonsingular terminal sliding mode control is employed to make the system quickly reach a stable state within a finite time, which makes the control input less adjust to guarantee the riding comfort. An adaptive mechanism is used to estimate controller parameters to get rid of the need of the prior knowledge about the bounds of system uncertainty. Simulations are presented to demonstrate the effectiveness of the proposed controller, which has robust performance to deal with the external disturbance and system parametric uncertainties. Thereby, the system guarantees the train operation to be accurate and comfortable.

干线铁路CTCS-2级列控系统融合ATO的方案研究

研究目的:随着珠三角城际铁路的开通,自动驾驶首次在大铁领域得到应用,它能实现列车运行自动控制,提高系统自动化程度和运输效率。由于干线铁路状况更加复杂,如何在干线铁路中应用自动驾驶尚未有明确的技术方案。基于此,本文主要分析干线铁路的特点和自动驾驶的需求,提出干线铁路CTCS-2级列控系统融合ATO的技术方案。研究结论:(1)干线铁路应用自动驾驶最可行的自动化等级应为GoA 2级,即半自动化驾驶运行模式;(2)干线铁路应实现的自动驾驶功能主要为区间自动驾驶、区间运行自动调整、进站对标停车和车门防护;(3)考虑干线铁路的特点和既有设备的变动要求,干线铁路C2系统融合ATO在工程实施中推荐采用基于司机估值的技术方案;(4)本研究成果可为干线线路列控系统引入自动驾驶提供一定的借鉴。

ETCS系统应用ATO技术发展综述

为提高干线铁路的运输效率和能力,欧洲铁路部门开始研究欧洲列控系统(ETCS)应用自动驾驶(ATO)的可行性。通过分析ETCS系统应用自动驾驶(ATO over ETCS)的研究背景和过程,阐述系统架构、工作原理、自动驾驶的功能需求以及系统规范的架构体系。同时介绍即将投入运营的ETCS系统应用自动驾驶实例,并分析它们的结构和基本原理。

基于参考模型的ATO自适应控制算法研究

提高列车自动驾驶ATO(Automatic Train Operation)系统的控制精度是实现全程无人驾驶的关键。本文首先分析列车制动系统的动态性能,然后基于该制动系统的状态空间模型构建一种模型参考自适应控制系统,并在理论上证明该控制算法的渐近稳定性,同时指出该类控制算法存在引起控制器震荡的固有弊端。随后,通过在原自适应控制系统中引入合适的辅助系统,构建基于增广误差的自适应控制系统,该算法不仅克服了前一种方法的固有缺陷,而且具有更加严谨的理论结构。最后,数学仿真结果显示本文所提算法能有效补偿列车运行过程中存在的不确定性因素,使列车精确地追踪目标制动曲线,验证了本文所提方法的有效性。

面向高速铁路的CTCS+ATO列控系统研究

为提高高速铁路运输效率和自动化程度,根据珠三角城际铁路CTCS2+ATO列控系统的运用经验,提出高速铁路引入自动驾驶(ATO)的方案。方案采用CTCS+ATO系统结构,根据系统配置分为CTCS+ATO-PFC(Partial Function Configuration)和CTCS+ATO-FFC(Full Function Configuration)两个等级。分别对每个等级的系统功能、地面和车载设备配置进行定义,并提出系统分级实施方案。CTCS+ATO列控系统方案综合考虑我国列控系统的现状和发展方向,为我国高速铁路引入自动驾驶提供参考依据。

基于模糊自适应PID控制的ATO系统控制算法

为了研究ATO系统控制算法的智能性和高效性,在传统PID算法的基础上,充分考虑到列车系统的非线性和复杂性,结合模糊控制理论能进行实时非线性调节的优点,提出了模糊自适应PID控制算法。并在Matlab/Simulink中建立了ATO系统的仿真模型和算法控制模块。将两种算法分别运用到ATO系统中,对目标速度曲线进行跟踪,从停车精度、追溯性、准时性、节能性、舒适性五个方面对二者的控制性能进行比较分析。仿真结果表明,将模糊自适应PID算法运用到ATO系统中,列车的控制性能能够很好地满足ATO系统的各个性能指标要求。

车载ATO运行等级模式曲线的计算模型研究

车载ATO的运行等级模式曲线计算是车载ATO的重要功能之一。本文通过分析车载ATO自动调速功能,确定了ATO运行等级模式曲线的设计需求。针对设计需求,结合列车运行状态转移模型,以准点、舒适、节能等为速度控制目标,对不同的城轨列车运行计划(包括运行时间和运行路径)建立了车载ATO运行等级模式曲线的计算模型。通过仿真验证,本文建立的运行等级模式曲线计算模型基本满足车载ATO自动调速功能的设计需求,为自动调速模块提供控制目标曲线。

基于灰色系统理论高速列车ATO速度控制器研究

速度控制器是ATO系统的核心单元,也是列控系统的重要组成部分,针对目前高速列车无ATO功能的情况,研究智能的ATO系统速度控制器对实现高速列车自动驾驶具有的重要意义。通过分析CTCS-3级列控系统的结构和功能,提出了在CTCS-3级列控系统中增加ATO系统速度控制器的方案。首先设计了速度控制器与车载及地面设备的连接方式,实现了信息交互;而后应用灰色系统理论善于研究外延明确内涵不清系统的特点,建立速度控制器模型,进行预测及决策计算,得到比较合理的列车自动驾驶控制策略;最后采用遗传算法对其进行优化,得到最优控制策略。仿真结果表明,该方法实现了高速列车在CTCS-3级列控系统下的自动驾驶,列车运行的各项性能都得到了提高。