【作者】 赵莹；

【导师】 步兵；

【作者基本信息】 北京交通大学 ， 交通信息工程及控制， 2025， 硕士

【摘要】 基于车车通信的列车控制系统(Train-to-Train Communication Based Train Control System,T2T-CBTC)包含车车和车地无线通信制式,是城市轨道交通未来发展的重要趋势。与基于通信的列车控制(Communication Based on Train Control System,CBTC)系统相比,T2T-CBTC采用车车(Train-to-Train,T2T)和车地(Train-to-Ground,T2G)通信相结合的传输机制完成信息交互,保证列车的安全高效运行。新型的传输机制势必引入更多的传输差错,对列车运行效率造成影响。因此,需要提出一种量化评价T2T-CBTC无线传输系统可信性的分析方法,研究传输差错作用下无线通信性能对传输系统可信性的影响,以及传输系统可信性对列车实际运行控制性能的影响。本文分析了T2T-CBTC系统的通信机制以及其对传输可信性需求,提出了定量评价传输系统可信性的方法。采用有色Petri网对T2T-CBTC无线传输系统进行建模以研究传输系统的可信性,基于动力学模型及列车紧急制动和常用制动场景,进一步分析了传输系统可信性对列车控制性能的影响。论文做了以下工作:(1)基于T2T-CBTC系统组成架构及控车原理,分析了车车和车地通信链路的具体传输内容。基于系统可信性一般性定义和T2T-CBTC系统对于可信性的需求,完成传输系统可信性及属性的定义和量化指标,并提出了基于信息熵权法的可信性属性权重计算方法,以得到传输系统可信性值。(2)分析了T2T-CBTC系统中的三种传输差错:列车非正常切换、链路中断及重连、数据传输失败及重传,进一步研究传输差错发生概率以及数据通信时延。基于分层赋时的有色Petri网(Colored Petri Network,CPN),建立包含三种无线传输差错的传输系统模型。从T2T和T2G结合的通信机制角度出发,研究列车接收前车和地面设备信息的时间间隔,完成了基于通信时延和丢包的传输系统可信性量化模型;(3)基于动力学模型建立通信延迟下多列车追踪模型,并确定列车间最小追踪间隔为列控系统性能指标,给出了传输系统可信性与列控系统性能之间的函数表达式。针对列车紧急制动和常用制动发生概率的场景进行数学建模,得到传输可信性对列车运行控制的影响。最后提出一种T2T-CBTC传输系统可信性的优化措施。(4)仿真验证与结果分析。借助CPN Tools对T2T-CBTC无线传输系统进行了仿真,得到通信性能参数。然后通过MATLAB仿真无线通信性能(丢包率、接收时间窗、ATP限定时间)与T2T-CBTC和CBTC传输系统可信性的关系。仿真T2T-CBTC系统中列车追踪间隔模型、列车紧急制动和常用制动场景,得到传输系统可信性与列车控制性能之间的关系。实验结果表明,T2T-CBTC传输系统的可信性低于CBTC系统;验证了本文提出的T2T-CBTC无线传输系统优化措施的有效性。仿真结果表明,T2T-CBTC传输系统可信性为99.73%,优化后的T2T-CBTC传输系统可信性能提高到99.88%,比CBTC提高了0.12%。本文含图31幅,表7个,参考文献73篇。更多还原

【Abstract】 The Train-to-Train Communication Based Train Control System(T2T-CBTC)integrates both Train-to-Train(T2T)and Train-to-Ground(T2G)wireless communication systems,representing a significant trend in the future development of urban rail transit.Compared to the traditional Communication Based Train Control(CBTC)system,T2T-CBTC employs a combined T2T and T2G communication mechanism for information exchange,ensuring the safe and efficient operation of trains.However,the new transmission mechanism is likely to introduce additional transmission errors,which could potentially impact the operational efficiency of trains.Therefore,it is necessary to propose an analytical method for quantitatively evaluating the dependability of the T2T-CBTC wireless transmission system.This method should examine the impact of transmission errors on wireless communication performance and analyze how the dependability of the transmission system affects the actual operation control performance of trains.In this thesis,a method for quantitatively evaluating the dependability of the transmission system is proposed by analyzing the communication mechanism of the T2T-CBTC transmission system and the demand for transmission dependability.To study the dependability of the transmission system,a Colored Petri Network(CPN)model is used to model the T2T-CBTC wireless transmission system.The impact of the transmission system’s dependability on the train control performance is further analyzed based on the train dynamics model,as well as the emergency braking and service braking scenarios.The main contributions of this thesis are as follows:(1)Based on the composition architecture and train control principle of T2T-CBTC system,the specific transmission content of the T2T and T2G communication links is analyzed.Based on the general definition of system dependability and the T2T-CBTC system’s requirements for dependability,the definition and quantification metrics for transmission system dependability and its attributes are provided.To obtain the dependability value of the transmission system,a method for calculating the weight of dependability attributes based on the information Entropy Weight Method is proposed.(2)This thesis analyzes three types of transmission errors within the T2T-CBTC system:abnormal train handover,link interruption and reconnection,and data transmission failure and retransmission.The probabilities of these errors and their impact on communication latency are further studied.A hierarchical timed CPN model is developed to represent the transmission system,incorporating three types of wireless transmission errors.Considering the concurrent transmission links of T2T and T2G communication,this thesis studies the time intervals required for trains to receive information from the forging train and the ground equipment.Based on communication latency and packet loss,a quantitative model for transmission system dependability has been established;(3)A multi-train tracking model under communication latency is developed using dynamics model.The minimum tracking interval is determined as a performance indicator for the train control system,and a functional expression describing the relationship between transmission system dependability and train control system performance is provided.Mathematical modeling of scenarios involving emergency and service braking probabilities is performed to analyze the impact of transmission dependability on train control.Finally,an optimization measure to improve the dependability of the T2T-CBTC transmission system is proposed;(4)Simulation verification and result analysis.Using CPN Tools,the T2T-CBTC wireless transmission system is simulated to obtain the communication performance parameters.Then,the relationship between the wireless communication performance(packet loss rate,receiving time window,ATP limited time)and the dependability of the T2T-CBTC and CBTC transmission system is simulated by MATLAB software.The train tracking interval model,as well as the emergency and service braking scenarios in the T2T-CBTC system,are simulated to analyze the relationship between transmission system dependability and train control performance.The experimental results show that the dependability of the T2T-CBTC transmission system is lower than that of CBTC system;The effectiveness of the proposed optimization measure for the T2T-CBTC wireless transmission system is also verified.The simulation results show that the dependability of the T2T-CBTC transmission system is 99.73%,and the dependability of the optimized T2T-CBTC transmission system can be improved to99.88%,which is 0.12%higher than CBTC.This thesis includes 31 figures,7 tables and 73 references.更多还原