面向T-CPS的微观交通认知方法及相关研究
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摘要
随着交通问题日趋严峻，如何以科学的方法准确认知交通现象，如何以先进的技术支撑交通系统的发展，以有效缓解交通拥堵、降低排放/能耗和提高行驶安全，是亟待解决的重要问题。目前，交通信息化与智能化已成为国际上交通系统现代化的主要发展方向，是当代科学技术前沿领域。而由于交通系统本质是非线性、强耦合、泛时空复杂系统，而传统交通系统的感知、计算、通信和控制等过程之间缺乏广泛的互联互通互操作，导致交通系统尚未实现充分的协调与优化。信息物理系统(Cyber Physical Systems, CPS)技术和交通流理论的出现，为上述问题的解决提供了新的途径。因此，在CPS的架构下，研究交通现象的认知方法及相关问题，具有重要的理论和实际意义。
本文主要围绕面向交通信息物理系统(Transportation Cyber Physical Systems,T-CPS)的微观交通认知方法展开研究。具体内容包括：重点针对传统交通系统的感知、计算、通信和控制等过程之间缺乏广泛的互联互通互操作，提出T-CPS面向服务的基本架构。基于微观交通流理论，系统的讨论微观认知模型的优化速度函数、稳定性分析、非线性分析及零动态等关键问题，进而研究基于FVD认知模型的交通拥堵反馈控制。考虑T-CPS环境下综合交通信息对跟驰车辆行为的影响，提出一种基于多前车位置、速度差和加速度差信息(Multiple Headway, Velocity&Acceleration Difference, MHVAD)的跟驰模型，以准确客观的认知交通现象。理论分析和数值仿真均验证了MHVAD模型的有效性。
论文的主要工作包括：
①充分利用CPS中物理系统与信息系统之间的相互作用与反馈特点，提出包含感知、通信、计算、控制和服务五个层次的T-CPS基本架构。
传统交通系统由于缺乏广泛的互联互通互操作，尚未实现充分的协调与优化。而CPS是通过集成3C(Computation, Communication, Control)技术将信息基元与物理元素融为一体，并基于信息系统和物理系统之间的相互作用与反馈，进而实现对物理系统的精确认知和有效控制的前沿技术。本文基于CPS概念并结合交通系统的特点，构建面向服务的T-CPS基本架构，诠释了相应层次的功能，讨论了T-CPS的特点及若干关键技术，为下一代智能交通系统(Intelligent Transportation System, ITS)发展提供理论支撑。
②针对交通现象认知的微观方法——跟驰模型，系统的讨论了跟驰模型的优化速度函数、稳定性分析、非线性分析及零动态等关键问题。
交通流跟驰模型是T-CPS中从微观层面认知交通流状态变化的主要方法之一，一直以来广受学者的关注。现有的跟驰模型大部分均是基于OV模型扩展而来，而OV模型的核心就在于优化速度函数，因此掌握优化速度函数的特点对于研究基于跟驰模型的交通认知方法至关重要；
在基于跟驰模型的交通认知研究中，模型的稳定性分析是一个重要内容。本文系统的讨论了跟驰模型的局部稳定和渐近稳定问题。此外，为了有效分析跟驰模型的稳定性问题，本文给出了一类二阶系统构造Lyapunov函数的引理，并予以严格证明。随后，据此讨论了交通流跟驰模型的Lyapunov稳定性问题；
为了揭示交通系统的非线性特性，本文从两方面入手，一方面根据传统的方法，应用微小变量法来导出跟驰模型的mKdV方程；另一方面，引入零动态的概念，导出跟驰模型的零动态方程，这是跟驰模型研究中的一个新的尝试。
③从反馈及系统控制的角度，研究基于跟驰模型的交通拥堵反馈控制问题
交通系统本质上是一个复杂的系统。根据物理学的基本规律可知，力是物体运动的原因，而加速度则是改变物体运动状态的原因。为了从系统和控制的角度来展开研究，本文通过设计加速度信息作为反馈信号，并基于FVD模型，讨论了基于跟驰模型的交通拥堵反馈控制问题，仿真结果表明了本方法的有效性。
④考虑T-CPS环境下综合交通信息对跟驰车辆行为的影响，提出了MHVAD跟驰模型。
为了更加准确的认知实际的交通现象，综合考虑前导车辆的数量、位置、速度差和加速度差等信息的共同影响，提出了MHVAD跟驰模型。并讨论了MHVAD模型的稳定性，同时分别从启动过程、停止过程和演化过程三方面讨论了MHVAD模型的动态性能，并与现有模型进行比较，结果表明MHVAD模型的性能较优，从而为准确的认知交通流运行规律提供基础。
综上所述，本文提出了面向服务的T-CPS基本架构，系统讨论了T-CPS中微观认知方法——跟驰模型的优化速度函数、稳定性分析、非线性分析、零动态等关键问题，研究了基于跟驰模型的拥堵反馈控制问题，提出了一种基于多前车位置、速度差和加速度差信息(MHVAD)的跟驰模型，理论分析和仿真实验均验证了上述工作的有效性。
Regards to the increasingly severe traffic problems，it is an important issuedemanding prompt solution that how to accurately cognize the traffic phenomena in reallife with scientific methods, and how to relieve traffic jam, reduce emissions/energyconsumption and improve driving safety with advanced technology development oftransportation system. Currently, the informatization and intelligence of transportationhas become the main development direction of the modernization of internationaltransportation system, which is the front area in subject of contemporary science andtechnology. However, the traditional transportation system has not yet achieved fullcoordination and optimization as a result of the lack of extensive interconnection,intercommunication and interoperability among the process of perception,communication, computation and control. And with the emergence of cyber-physicalsystem (CPS) and traffic flow theory, a new way to solve the above problems from theviewspoint of advanced technology and accurate perception arises. Therefore, it is withimportant theoretical and practical significance to study the traffic cognition method andrelated problems in the transportation cyber physical systems (T-CPS) environment.
This dissertation focus on the T-CPS oriented microscopic traffic cognitivetechniques and related key problems. Specially, a service-oriented architecture for theT-CPS is put forward according to the lack of extensive interconnection,intercommunication and interoperability among the process of perception,communication, computation and control of the traditional transportation system. Thenthe systematic discussions of optimal velocity function, stability analysis, nonlinearanalysis and zero-dynamics of microscopic car-following model are conducted based onmicroscopic traffic flow theory. Moreover, the feedback control of traffic congestion isinvestigated from the system and control perspective, and thereby, a called multipleheadway, velocity&acceleration difference (MHVAD) car-following model is proposedtaking into account the comprehensive information in the T-CPS environment. In theend, theoretical analysis and numerical simulation both prove the validity of MHVADmodel.
The main works of this dissertation are as follows:
①Considering the interaction and feedback between the physical system andcyber system of CPS, the basic architecture of T-CPS including perception, communication, computation, control and service is proposed.
Since the traditional transportation system has not yet achieved full coordinationand optimization as a result of the lack of widespread interconnection,intercommunication and interoperability. And CPS is a multi-dimensional complexsystem, integrating of cyber element and physical element through the3C (Computation,Communication, Control) technology. Its main characteristic is achieving the preciseperception and effective control of the physical system through the interaction andfeedback between the cyber system and physical system. So the dissertation introducesthe CPS into transportation system and puts forward a service-oriented architecture forT-CPS, and then explains the function of corresponding layers, finally discusses somekey techniques and applications of T-CPS to provide theory support for next generationof ITS.
②Regards to the microscopic cognitive technique for trafficphenomenon——car-following model, the systematic discussions of the key issues ofthe following model, such as optimal velocity function, stability analysis, nonlineardynamic analysis and the zero dynamics are carried out.
Car-following model attracted more attention is one of the main approaches tocognize the revolution of traffic state from the microscopic viewpoint in T-CPS. Andcurrently, many car-following models are improved as a function of OV model,nevertheless, the key of OV model lies on the optimal velocity function. Therefore, it isof importance to study the cognitive technique based on car-following model with thecharacteristics of optimal velocity function.
The stability analysis of car-following model is one important aspect in the trafficcognitive based on car-following model. And the local stability and the asymptoticstability of car-following model are systematic discussed in this dissemination. Inconsideration of the strong coupling and nonlinear characteristics of traffic system, toanalyze the stability effectively, a lemma of Lyapunov function construction for oneclass of second-order system is put forward and proved according to the related controltheory, and then, the Lyapunov stability of car-following model is discussed.
To reveal the nonlinear characteristics of traffic system, on one hand, the mKdVequation of car-following model is derived through the small variation methodaccording to the traditional approach; while on the other hand, a new attempt to obtainthe zero dynamics equation of car-following model is carried out with emphasis on theconcept of zero dynamics.
③The feedback control of traffic jam based on car-following model isinvestigated from the system and control viewpoint.
The traffic system is essentially a complex system. According to the fundamentallaws of physics, force is the reason for the movement of objects, while the accelerationis the reason for changing the state of the movement of objects. To conduct a study fromthe system and control perspective, the acceleration information is designed as thefeedback signal, and the feedback control of traffic jam based on car-following model isdiscussed based on the FVD model. And smulation results show the effectiveness of theproposed method in the final.
④A MHVAD car-following model is proposed in consideration of thecomprehensive information in T-CPS environment.
To cognize the traffic phenomenon accurately, a MHVAD car-following model isput forward taking into account the comprehensive impacts of the number, position,velocity difference and acceleration difference of preceding vehicles. And the stabilityof MHVAD model is conducted in detail. Then the dynamic performance of MHVADmodel is discussed from the start process, stop process and revolution process.Compared with the existing models, the simulation results show that the performance ofMHVAD model is better than that of those models, which can provide the basis fortraffic state cognitive accurately.
In conclusion, the basic architecture of T-CPS is proposed, and regards to themicroscopic cognitive technique for traffic phenomenon——car-following model, thesystematic discussions of its optimal velocity function, stability analysis, nonlinearanalysis are conducted, moreover, the zero dynamics of car-following model is made,then, the feedback control of traffic jam is studied, and in the end, a MHVADcar-following model is proposed and theoretical analysises and simulation resultsvalidate the effectiveness of the work.
本文主要围绕面向交通信息物理系统(Transportation Cyber Physical Systems,T-CPS)的微观交通认知方法展开研究。具体内容包括：重点针对传统交通系统的感知、计算、通信和控制等过程之间缺乏广泛的互联互通互操作，提出T-CPS面向服务的基本架构。基于微观交通流理论，系统的讨论微观认知模型的优化速度函数、稳定性分析、非线性分析及零动态等关键问题，进而研究基于FVD认知模型的交通拥堵反馈控制。考虑T-CPS环境下综合交通信息对跟驰车辆行为的影响，提出一种基于多前车位置、速度差和加速度差信息(Multiple Headway, Velocity&Acceleration Difference, MHVAD)的跟驰模型，以准确客观的认知交通现象。理论分析和数值仿真均验证了MHVAD模型的有效性。
论文的主要工作包括：
①充分利用CPS中物理系统与信息系统之间的相互作用与反馈特点，提出包含感知、通信、计算、控制和服务五个层次的T-CPS基本架构。
传统交通系统由于缺乏广泛的互联互通互操作，尚未实现充分的协调与优化。而CPS是通过集成3C(Computation, Communication, Control)技术将信息基元与物理元素融为一体，并基于信息系统和物理系统之间的相互作用与反馈，进而实现对物理系统的精确认知和有效控制的前沿技术。本文基于CPS概念并结合交通系统的特点，构建面向服务的T-CPS基本架构，诠释了相应层次的功能，讨论了T-CPS的特点及若干关键技术，为下一代智能交通系统(Intelligent Transportation System, ITS)发展提供理论支撑。
②针对交通现象认知的微观方法——跟驰模型，系统的讨论了跟驰模型的优化速度函数、稳定性分析、非线性分析及零动态等关键问题。
交通流跟驰模型是T-CPS中从微观层面认知交通流状态变化的主要方法之一，一直以来广受学者的关注。现有的跟驰模型大部分均是基于OV模型扩展而来，而OV模型的核心就在于优化速度函数，因此掌握优化速度函数的特点对于研究基于跟驰模型的交通认知方法至关重要；
在基于跟驰模型的交通认知研究中，模型的稳定性分析是一个重要内容。本文系统的讨论了跟驰模型的局部稳定和渐近稳定问题。此外，为了有效分析跟驰模型的稳定性问题，本文给出了一类二阶系统构造Lyapunov函数的引理，并予以严格证明。随后，据此讨论了交通流跟驰模型的Lyapunov稳定性问题；
为了揭示交通系统的非线性特性，本文从两方面入手，一方面根据传统的方法，应用微小变量法来导出跟驰模型的mKdV方程；另一方面，引入零动态的概念，导出跟驰模型的零动态方程，这是跟驰模型研究中的一个新的尝试。
③从反馈及系统控制的角度，研究基于跟驰模型的交通拥堵反馈控制问题
交通系统本质上是一个复杂的系统。根据物理学的基本规律可知，力是物体运动的原因，而加速度则是改变物体运动状态的原因。为了从系统和控制的角度来展开研究，本文通过设计加速度信息作为反馈信号，并基于FVD模型，讨论了基于跟驰模型的交通拥堵反馈控制问题，仿真结果表明了本方法的有效性。
④考虑T-CPS环境下综合交通信息对跟驰车辆行为的影响，提出了MHVAD跟驰模型。
为了更加准确的认知实际的交通现象，综合考虑前导车辆的数量、位置、速度差和加速度差等信息的共同影响，提出了MHVAD跟驰模型。并讨论了MHVAD模型的稳定性，同时分别从启动过程、停止过程和演化过程三方面讨论了MHVAD模型的动态性能，并与现有模型进行比较，结果表明MHVAD模型的性能较优，从而为准确的认知交通流运行规律提供基础。
综上所述，本文提出了面向服务的T-CPS基本架构，系统讨论了T-CPS中微观认知方法——跟驰模型的优化速度函数、稳定性分析、非线性分析、零动态等关键问题，研究了基于跟驰模型的拥堵反馈控制问题，提出了一种基于多前车位置、速度差和加速度差信息(MHVAD)的跟驰模型，理论分析和仿真实验均验证了上述工作的有效性。
Regards to the increasingly severe traffic problems，it is an important issuedemanding prompt solution that how to accurately cognize the traffic phenomena in reallife with scientific methods, and how to relieve traffic jam, reduce emissions/energyconsumption and improve driving safety with advanced technology development oftransportation system. Currently, the informatization and intelligence of transportationhas become the main development direction of the modernization of internationaltransportation system, which is the front area in subject of contemporary science andtechnology. However, the traditional transportation system has not yet achieved fullcoordination and optimization as a result of the lack of extensive interconnection,intercommunication and interoperability among the process of perception,communication, computation and control. And with the emergence of cyber-physicalsystem (CPS) and traffic flow theory, a new way to solve the above problems from theviewspoint of advanced technology and accurate perception arises. Therefore, it is withimportant theoretical and practical significance to study the traffic cognition method andrelated problems in the transportation cyber physical systems (T-CPS) environment.
This dissertation focus on the T-CPS oriented microscopic traffic cognitivetechniques and related key problems. Specially, a service-oriented architecture for theT-CPS is put forward according to the lack of extensive interconnection,intercommunication and interoperability among the process of perception,communication, computation and control of the traditional transportation system. Thenthe systematic discussions of optimal velocity function, stability analysis, nonlinearanalysis and zero-dynamics of microscopic car-following model are conducted based onmicroscopic traffic flow theory. Moreover, the feedback control of traffic congestion isinvestigated from the system and control perspective, and thereby, a called multipleheadway, velocity&acceleration difference (MHVAD) car-following model is proposedtaking into account the comprehensive information in the T-CPS environment. In theend, theoretical analysis and numerical simulation both prove the validity of MHVADmodel.
The main works of this dissertation are as follows:
①Considering the interaction and feedback between the physical system andcyber system of CPS, the basic architecture of T-CPS including perception, communication, computation, control and service is proposed.
Since the traditional transportation system has not yet achieved full coordinationand optimization as a result of the lack of widespread interconnection,intercommunication and interoperability. And CPS is a multi-dimensional complexsystem, integrating of cyber element and physical element through the3C (Computation,Communication, Control) technology. Its main characteristic is achieving the preciseperception and effective control of the physical system through the interaction andfeedback between the cyber system and physical system. So the dissertation introducesthe CPS into transportation system and puts forward a service-oriented architecture forT-CPS, and then explains the function of corresponding layers, finally discusses somekey techniques and applications of T-CPS to provide theory support for next generationof ITS.
②Regards to the microscopic cognitive technique for trafficphenomenon——car-following model, the systematic discussions of the key issues ofthe following model, such as optimal velocity function, stability analysis, nonlineardynamic analysis and the zero dynamics are carried out.
Car-following model attracted more attention is one of the main approaches tocognize the revolution of traffic state from the microscopic viewpoint in T-CPS. Andcurrently, many car-following models are improved as a function of OV model,nevertheless, the key of OV model lies on the optimal velocity function. Therefore, it isof importance to study the cognitive technique based on car-following model with thecharacteristics of optimal velocity function.
The stability analysis of car-following model is one important aspect in the trafficcognitive based on car-following model. And the local stability and the asymptoticstability of car-following model are systematic discussed in this dissemination. Inconsideration of the strong coupling and nonlinear characteristics of traffic system, toanalyze the stability effectively, a lemma of Lyapunov function construction for oneclass of second-order system is put forward and proved according to the related controltheory, and then, the Lyapunov stability of car-following model is discussed.
To reveal the nonlinear characteristics of traffic system, on one hand, the mKdVequation of car-following model is derived through the small variation methodaccording to the traditional approach; while on the other hand, a new attempt to obtainthe zero dynamics equation of car-following model is carried out with emphasis on theconcept of zero dynamics.
③The feedback control of traffic jam based on car-following model isinvestigated from the system and control viewpoint.
The traffic system is essentially a complex system. According to the fundamentallaws of physics, force is the reason for the movement of objects, while the accelerationis the reason for changing the state of the movement of objects. To conduct a study fromthe system and control perspective, the acceleration information is designed as thefeedback signal, and the feedback control of traffic jam based on car-following model isdiscussed based on the FVD model. And smulation results show the effectiveness of theproposed method in the final.
④A MHVAD car-following model is proposed in consideration of thecomprehensive information in T-CPS environment.
To cognize the traffic phenomenon accurately, a MHVAD car-following model isput forward taking into account the comprehensive impacts of the number, position,velocity difference and acceleration difference of preceding vehicles. And the stabilityof MHVAD model is conducted in detail. Then the dynamic performance of MHVADmodel is discussed from the start process, stop process and revolution process.Compared with the existing models, the simulation results show that the performance ofMHVAD model is better than that of those models, which can provide the basis fortraffic state cognitive accurately.
In conclusion, the basic architecture of T-CPS is proposed, and regards to themicroscopic cognitive technique for traffic phenomenon——car-following model, thesystematic discussions of its optimal velocity function, stability analysis, nonlinearanalysis are conducted, moreover, the zero dynamics of car-following model is made,then, the feedback control of traffic jam is studied, and in the end, a MHVADcar-following model is proposed and theoretical analysises and simulation resultsvalidate the effectiveness of the work.
引文
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