基于电磁导航的车路协同仿真系统研究
|
摘要
车路协同作为智能交通运输系统的重要组成部分,为缓解道路拥挤、提高道路通行能力、改善道路交通安全等发挥了重要作用。采用实际智能车进行车路协同研究成本过高,然而软件仿真平台的实验环境过于理想,因此,本文设计并实现了车路协同硬件仿真系统。
本文所设计车路协同硬件仿真系统由仿真车系统和道路设施系统组成。针对视觉导航可靠性较差的问题,本文仿真车采用电磁导航方式,仿真车采用里程计结合RFID射频识别特征路标的方式实现车辆的定位,采用WiFi无线传输技术实现车辆间的无线通信。实际实验表明,该仿真车能够在动力学、导航、定位、无线通信等方面很好地仿真实际智能车。
本文设计了正弦信号发生器用于产生一定频率的交流电源驱动赛道下方的导引线。通过比较目前信号发生器的不同设计方案,设计了基于精密函数发生芯片MAX038的信号发生器。该信号发生器主要包括信号生成模块、输出放大模块、电流和频率测量模块、人机交互模块。为了保证导引信号的频率稳定性,设计了基于单片机的频率闭环控制电路。该信号发生器通过闭环控制保证了输出信号的频率稳定性,实验结果表明该信号发生器完成了设计目标,具有一定的稳定性和可靠性。
高效的路口多车协作可以减少道路拥堵的情况发生,提高交通流量和交通系统运行的效率。针对无交通灯十字路口,本文提出了一种基于博弈论的路口多智能车协作算法。首先,利用场图工具建立路口车辆冲突模型。然后,针对冲突车辆设计了基于博弈论的协调算法。使用本文开发的硬件仿真平台,对提出的算法进行了验证。实验结果表明,采用本文算法车辆通过路口的时间比采用冲突表算法缩短了约40%,本文提出的算法在保证车辆安全通过路口的同时,提高了路口的通行效率。
本文针对双向双车道交通场景下的智能车辆超车问题进行了研究,提出了基于反应式智能体的超车算法。在车辆超车过程中,根据车辆对周围环境的感知建立相应的虚拟环境,在虚拟环境中建立反应式多智能体系统,根据物理学启发定义智能体之间以及智能体与虚拟环境间的相互作用,最后通过对多智能体的空间分布的全局评价指标得到车辆超车动作的控制指令。经过实验表明,本章提出的算法可以保证车辆超车过程中的安全性。
Vehicle-to-Infrastructure cooperation system has become the forefront of technology and research focus in the field of intelligent transport system. It plays an important role in easing the road congestion, increasing the road capacity and improving the traffic safety. The cost is too high in the research of cooperative vehicle infrastructure system using actual intelligent vehicle. However, the experimental environment is ideal in software simulation. For these reason, this thesis designs and implements a hardware simulation system for vehicle-to-infrastructure cooperation system.
The hardware simulation system designed in this thesis consists of mini intelligent vehicle system and road infrastructure system. The mini intelligent vehicle use electromagnetic navigation, owing to the poor reliability for visual navigation. The mini intelligent vehicle implements its longitudinal localization through combination of odometer and road sign detection using RFID,and the communication between vehicles is based on WiFi wireless transmission technology. In summary, The mini intelligent vehicle can simulate real intelligent vehicle in kinetics, navigation, localization and wireless communication.
By comparing the different design solution of signal generator, a sine signal generator based on MAX038 is designed to produce a certain frequency AC power to drive the guide line. The basic research content includes sine signal generator and current amplification module, current and frequency measure module, human-computer interaction module. The signal generator provides close-loop stable control of frequency, to make the frequency output smoothly. The experiment revealed that the signal generator could generate a sine signal with high precision and steady that meet with theoretical design.
Intelligent vehicles’cooperative driving in intersection can reduce the congestion occurs and improve the passing rates. The thesis introduces an algorithm based on dynamic game for intelligent vehicles cooperation at the unsignalized intersection. Conflict between intelligent vehicles is described by using field graph tool. A conflict avoidance algorithm was built up with dynamic game theory. The hardware simulation system designed in this thesis is used to test the algorithm. The algorithm not only coordinates the intelligent vehicles among intersection without collision,but also improve the passing rates by about 40% compared to the collision table based algorithm.
The thesis presents an algorithm based on reactive multi-agent system to the overtaking problem of vehicle. During the overtaking process, the overtaking vehicle creates a virtual environment based on vehicle’s perceptions of the material environment around it. A decision vector for the vehicle is elaborated from the evaluation of a set of indicators characterizing the global state of a system of reactive agents (RMAS), which is evolve in the virtual environment. Agent-to-agent and agent-to-environment interactions are inspired by physics, in order to produce a distribution of agents over the virtual environment. Experiments show that the algorithm can guarantee the safety of vehicle during the overtaking process.
本文所设计车路协同硬件仿真系统由仿真车系统和道路设施系统组成。针对视觉导航可靠性较差的问题,本文仿真车采用电磁导航方式,仿真车采用里程计结合RFID射频识别特征路标的方式实现车辆的定位,采用WiFi无线传输技术实现车辆间的无线通信。实际实验表明,该仿真车能够在动力学、导航、定位、无线通信等方面很好地仿真实际智能车。
本文设计了正弦信号发生器用于产生一定频率的交流电源驱动赛道下方的导引线。通过比较目前信号发生器的不同设计方案,设计了基于精密函数发生芯片MAX038的信号发生器。该信号发生器主要包括信号生成模块、输出放大模块、电流和频率测量模块、人机交互模块。为了保证导引信号的频率稳定性,设计了基于单片机的频率闭环控制电路。该信号发生器通过闭环控制保证了输出信号的频率稳定性,实验结果表明该信号发生器完成了设计目标,具有一定的稳定性和可靠性。
高效的路口多车协作可以减少道路拥堵的情况发生,提高交通流量和交通系统运行的效率。针对无交通灯十字路口,本文提出了一种基于博弈论的路口多智能车协作算法。首先,利用场图工具建立路口车辆冲突模型。然后,针对冲突车辆设计了基于博弈论的协调算法。使用本文开发的硬件仿真平台,对提出的算法进行了验证。实验结果表明,采用本文算法车辆通过路口的时间比采用冲突表算法缩短了约40%,本文提出的算法在保证车辆安全通过路口的同时,提高了路口的通行效率。
本文针对双向双车道交通场景下的智能车辆超车问题进行了研究,提出了基于反应式智能体的超车算法。在车辆超车过程中,根据车辆对周围环境的感知建立相应的虚拟环境,在虚拟环境中建立反应式多智能体系统,根据物理学启发定义智能体之间以及智能体与虚拟环境间的相互作用,最后通过对多智能体的空间分布的全局评价指标得到车辆超车动作的控制指令。经过实验表明,本章提出的算法可以保证车辆超车过程中的安全性。
Vehicle-to-Infrastructure cooperation system has become the forefront of technology and research focus in the field of intelligent transport system. It plays an important role in easing the road congestion, increasing the road capacity and improving the traffic safety. The cost is too high in the research of cooperative vehicle infrastructure system using actual intelligent vehicle. However, the experimental environment is ideal in software simulation. For these reason, this thesis designs and implements a hardware simulation system for vehicle-to-infrastructure cooperation system.
The hardware simulation system designed in this thesis consists of mini intelligent vehicle system and road infrastructure system. The mini intelligent vehicle use electromagnetic navigation, owing to the poor reliability for visual navigation. The mini intelligent vehicle implements its longitudinal localization through combination of odometer and road sign detection using RFID,and the communication between vehicles is based on WiFi wireless transmission technology. In summary, The mini intelligent vehicle can simulate real intelligent vehicle in kinetics, navigation, localization and wireless communication.
By comparing the different design solution of signal generator, a sine signal generator based on MAX038 is designed to produce a certain frequency AC power to drive the guide line. The basic research content includes sine signal generator and current amplification module, current and frequency measure module, human-computer interaction module. The signal generator provides close-loop stable control of frequency, to make the frequency output smoothly. The experiment revealed that the signal generator could generate a sine signal with high precision and steady that meet with theoretical design.
Intelligent vehicles’cooperative driving in intersection can reduce the congestion occurs and improve the passing rates. The thesis introduces an algorithm based on dynamic game for intelligent vehicles cooperation at the unsignalized intersection. Conflict between intelligent vehicles is described by using field graph tool. A conflict avoidance algorithm was built up with dynamic game theory. The hardware simulation system designed in this thesis is used to test the algorithm. The algorithm not only coordinates the intelligent vehicles among intersection without collision,but also improve the passing rates by about 40% compared to the collision table based algorithm.
The thesis presents an algorithm based on reactive multi-agent system to the overtaking problem of vehicle. During the overtaking process, the overtaking vehicle creates a virtual environment based on vehicle’s perceptions of the material environment around it. A decision vector for the vehicle is elaborated from the evaluation of a set of indicators characterizing the global state of a system of reactive agents (RMAS), which is evolve in the virtual environment. Agent-to-agent and agent-to-environment interactions are inspired by physics, in order to produce a distribution of agents over the virtual environment. Experiments show that the algorithm can guarantee the safety of vehicle during the overtaking process.
引文
[1]中国汽车工业协会官方网站. http://www.caam.org.cn/,2011.1.10.
[2] National Intelligent Transportation Systems Program Plan. Intelligent Transportation Society of America, 1995.
[3] National Intelligent Transportation Systems deployment strategy: actions for achieving national and community transportation objectives. Intelligent Transportation Society of America, 1995.
[4]杨佩昆.智能交通.上海:同济大学出版社,2002.
[5]谢振东,章威. ITS公用信息平台研究.网络技术与工程,2002,32(8):75-78
[6]黄卫,陈里德.智能运输系统概论.北京:人们交通出版社, 1999.
[7]陈超,吕植勇.国内外车路协同系统发展现状综述.交通信息与安全,2011,29(1):102-105.
[8] Shladover,S.E. PATH at 20-history and major milestone. IEEE Transaction on Intelligent Transportation Systems, 2007, 8(4): 584-592.
[9]杨明.无人自动驾驶车辆研究综述与展望.哈尔滨工业大学学报, 2006, 38: 1259-1262.
[10] Amanna A. Overview of IntelliDrive and Vehicle Infrastructure Integration (VII), 2009, Virginiatech Transportation Institute.
[11] Row S, Schagrin M, Briggs V. The Future of VII, US Department of Transportation. 2008.
[12] ITS Joint Program Office, Achieving the Vision: From VII to IntelliDrive POLICY WHITE PAPER, 2010.
[13] Research and Innovative Technology Administration ITS Joint Program Office, IntelliDriveSM Governance Needs Summary A Summarization of Research from 2004-2009,2009.
[14] Shladover,S.E. Cooperative (rather than autonomous) vehicle-highway automation systems. IEEE Intelligent Transportation Systems Magazine, 2009, 1(1): 10-19.
[15] Hiroshi MAKINO, Smartway Project. 12th ITS World Congress. San Francisco: Intelligent Transportation Society of America. 2005.
[16] Wani K. The Fourth Phase of Advanced Safety Vehicle Project, ITS World Congress, London, 2006.
[17] Vehicle Information and Communication System (VICS). http://www.vics.or.jp/English/index.html, 1990
[18]欧洲智能交通信息服务平台. http://www.ertico.com/about-ertico-mission, 2010.
[19] Smartway. http://www.smartway2007.jp/index.html, 2006
[20]张豫鹤,黄希,崔莉.面向交通信息采集的无线传感器网络节点.计算机研究与发展, 2008.45(1): 110-118.
[21]郇鹏,张仲义.基于射频技术的的高速公路不停车收费系统.交通运输系统工程与信息, 2004,4(2): 121-124.
[22] J.K.Hedrick, P.Varaiya, V.K.Narendren, Choi SB. Integrated maneuvering control design andexperiments: Phase I. California Path Report, UCB-ITS-PRR-95-15, 1995.
[23] http://torcs.sourceforge.net .
[24]王跃建,侯德藻,李克强.基于ITS的汽车主动避撞性关键技术研究(一).汽车技术, 2003(3): 3-8.
[25]于立萍.基于测距雷达的汽车安全辅助驾驶技术研究[硕士论文].北京:清华大学,2004.
[26] http://www.chinanews.com/auto/2011/10-21/3404647.shtml
[27] Vahidi A, Eskandarian A. Research advances in intelligent collision avoidance and adaptive cruise control. IEEE Transactions on Intelligent Transportation Systems, 2003, 4(3): 143-153.
[28]徐海贵,王春香,杨汝清,杨明.磁传感器系统在室外移动机器人导航中的研究.机器人, 2007, 29(1): 61-66.
[29]孙振平,安向京,贺汉根. CIVAVT-IV——视觉导航的自主车.机器人, 2002, 24(2): 115-120.
[30] HE Y, WANG H, ZHANG B. Color-Based Road Detection in Urban Traffic Scenes. IEEE Transactions on Intelligent Transportation Systems, 2004, 5(4).
[31]王荣本,张荣辉,金立生等.区域交通智能车辆导航控制技术.农业机械学报, 2007,38(7): 39-42.
[32] Hatipoglu C. Qzgüner u, Redmill K A. Automated lane change controller design. IEEE Transactions on Intelligent Transportation Systems, 2003, 4: 13-22.
[33] Guldner J, Utkin V I, Ackermann J. A sliding mode control approach to automatic car steering. Proceedings of American Control Conference, Baltimore, MD, June, 1994: 1969-1973.
[34] Peter H. Modelling lane changing and merging in microscopic traffic simulation. Transportation Research Part C, 2002, 10(5-6): 351–371.
[35]王荣本,张荣辉,游峰等.智能车辆弧线跟踪控制算法.吉林大学学报, 2006, 36(5):731-735.
[36]高振海.汽车方向预瞄式自适应PD控制算法.机械工程学报, 2004, 40(5): 101-105.
[37] S. Halle, J. Laumonier, B. Chaib. A decentralized approach to collaborative driving coordination. 7th International IEEE Conference on Intelligent Transportation Systems, 2004: 453-458.
[38]吴青,何智伟,初秀民,宗成强.智能车路系统中汽车列队行驶控制关键技术与研究进展.交通与计算机, 2008, 4(26): 154-157.
[39] P. Seiler, A. Pant, K. Hedrick. Disturbance propagation in vehicle strings. IEEE Transactions on Automatic Control, 2004, 49(10): 1835-1841.
[40] Fenghui Wang, M. Yang, Ruqing Yang. Conflict-probability-estimation-based overtaking for intelligent vehicles. IEEE Transactions on Intelligent Transportation Systems, 2009, 10(2): 366-370.
[41] DAVIS G A, SWENSON T. Field study of gap acceptance by left-turning drivers. Transportation Research Record, 2004(1899):71-75.
[42]孙一飞.多智能车辆系统的多车协调和协作算法仿真研究[硕士论文].上海:上海交通大学, 2007.
[43]曲昭伟,金勇,陈永恒,等.提前右转组织方式及其影响分析.交通运输工程学报,2008, 8 (2) :106-109.
[44]张昊,马旭,卓晴.基于电磁场检测的寻线智能车设计.电子产品世界, 2009(11): 48-50.
[45]李仕伯,马旭,卓晴.基于磁场检测的寻线小车传感器布局研究.电子产品世界. 2009(12):41-44
[46]周润景,张丽娜,丁莉.基于PROTEUS的电路及单片机设计与仿真(第2版).北京:北京航空航天大学出版社, 2009.
[47]鲁哨廷.多波形数字信号发生器的设计与实现.微处理机. 2008(2):149-151.
[48]于春锐,韩方景,欧阳志宏,李霖.基于DDS的调频信号发生器的设计与仿真.电子产品世界. 2010(6):37-39.
[49]马文杰.基于DSS技术的程控信号发生器的研究[硕士论文].南京:南京林业大学, 2009
[50]李海涛.多频段多波形信号发生器设计构想.潍坊高等职业教育. 2009, 5(1):60-61.
[51] Moshe A Pollatschek, Abishai Polus, Moshe Livneh. A decision model for gap acceptance and capacity at intersections. Transportation Research Part B:Methodological,2002,36(7):649-663.
[52]孙一飞,杨明,杨汝清.基于冲突表的多智能车路口协调算法及其仿真实现.计算机应用研究, 2007.
[53] Chin H C, Quek S T. Measurement of traffic conflicts. Safety Science, 1997, 26(3): 169-185.
[54]杨建国,王兆安,李庆丰.混杂交通微观仿真初探.系统仿真学报, 2004, 16(6): 1115-1117.
[55]罗珀.博弈论导论及其应用.北京:中国政法大学出版社, 2005.
[56]施锡铨.博弈论.上海:上海财经大学出版社, 2000.
[57]赵晓华,李振龙,于泉,等.基于Q学习算法的两交叉口信号灯博弈协调控制.系统仿真学报, 2007, 19(18): 4253-4256.
[58]郭鹏,杨晓琴.博弈论与纳什均衡.哈尔滨师范大学自然科学学报. 2006, 22(4):25-28.
[59]李斌,王荣本,施树明,王志中.高速公路智能超车系统设计. ITS通讯. 2000, 4(2):44-52.
[60] T. Shamir. How should an autonomous vehicle overtake a slower moving vehicle: design and analysis of an optimal trajectory. IEEE Transactions on Automatic Control. 2004, 49:607–610.
[61]游峰.智能车辆自动换道与自动超车控制方法的研究[博士论文].长春:吉林大学, 2005
[62] J.M. Contet, F. Gechter, P. Gruer, Abder Koukam. Evaluation of global system state thanks to local phenomenon. proceedings of the18th European Conference on Arti?cial Intelligence ECAI. 2008: 865-866 .
[2] National Intelligent Transportation Systems Program Plan. Intelligent Transportation Society of America, 1995.
[3] National Intelligent Transportation Systems deployment strategy: actions for achieving national and community transportation objectives. Intelligent Transportation Society of America, 1995.
[4]杨佩昆.智能交通.上海:同济大学出版社,2002.
[5]谢振东,章威. ITS公用信息平台研究.网络技术与工程,2002,32(8):75-78
[6]黄卫,陈里德.智能运输系统概论.北京:人们交通出版社, 1999.
[7]陈超,吕植勇.国内外车路协同系统发展现状综述.交通信息与安全,2011,29(1):102-105.
[8] Shladover,S.E. PATH at 20-history and major milestone. IEEE Transaction on Intelligent Transportation Systems, 2007, 8(4): 584-592.
[9]杨明.无人自动驾驶车辆研究综述与展望.哈尔滨工业大学学报, 2006, 38: 1259-1262.
[10] Amanna A. Overview of IntelliDrive and Vehicle Infrastructure Integration (VII), 2009, Virginiatech Transportation Institute.
[11] Row S, Schagrin M, Briggs V. The Future of VII, US Department of Transportation. 2008.
[12] ITS Joint Program Office, Achieving the Vision: From VII to IntelliDrive POLICY WHITE PAPER, 2010.
[13] Research and Innovative Technology Administration ITS Joint Program Office, IntelliDriveSM Governance Needs Summary A Summarization of Research from 2004-2009,2009.
[14] Shladover,S.E. Cooperative (rather than autonomous) vehicle-highway automation systems. IEEE Intelligent Transportation Systems Magazine, 2009, 1(1): 10-19.
[15] Hiroshi MAKINO, Smartway Project. 12th ITS World Congress. San Francisco: Intelligent Transportation Society of America. 2005.
[16] Wani K. The Fourth Phase of Advanced Safety Vehicle Project, ITS World Congress, London, 2006.
[17] Vehicle Information and Communication System (VICS). http://www.vics.or.jp/English/index.html, 1990
[18]欧洲智能交通信息服务平台. http://www.ertico.com/about-ertico-mission, 2010.
[19] Smartway. http://www.smartway2007.jp/index.html, 2006
[20]张豫鹤,黄希,崔莉.面向交通信息采集的无线传感器网络节点.计算机研究与发展, 2008.45(1): 110-118.
[21]郇鹏,张仲义.基于射频技术的的高速公路不停车收费系统.交通运输系统工程与信息, 2004,4(2): 121-124.
[22] J.K.Hedrick, P.Varaiya, V.K.Narendren, Choi SB. Integrated maneuvering control design andexperiments: Phase I. California Path Report, UCB-ITS-PRR-95-15, 1995.
[23] http://torcs.sourceforge.net .
[24]王跃建,侯德藻,李克强.基于ITS的汽车主动避撞性关键技术研究(一).汽车技术, 2003(3): 3-8.
[25]于立萍.基于测距雷达的汽车安全辅助驾驶技术研究[硕士论文].北京:清华大学,2004.
[26] http://www.chinanews.com/auto/2011/10-21/3404647.shtml
[27] Vahidi A, Eskandarian A. Research advances in intelligent collision avoidance and adaptive cruise control. IEEE Transactions on Intelligent Transportation Systems, 2003, 4(3): 143-153.
[28]徐海贵,王春香,杨汝清,杨明.磁传感器系统在室外移动机器人导航中的研究.机器人, 2007, 29(1): 61-66.
[29]孙振平,安向京,贺汉根. CIVAVT-IV——视觉导航的自主车.机器人, 2002, 24(2): 115-120.
[30] HE Y, WANG H, ZHANG B. Color-Based Road Detection in Urban Traffic Scenes. IEEE Transactions on Intelligent Transportation Systems, 2004, 5(4).
[31]王荣本,张荣辉,金立生等.区域交通智能车辆导航控制技术.农业机械学报, 2007,38(7): 39-42.
[32] Hatipoglu C. Qzgüner u, Redmill K A. Automated lane change controller design. IEEE Transactions on Intelligent Transportation Systems, 2003, 4: 13-22.
[33] Guldner J, Utkin V I, Ackermann J. A sliding mode control approach to automatic car steering. Proceedings of American Control Conference, Baltimore, MD, June, 1994: 1969-1973.
[34] Peter H. Modelling lane changing and merging in microscopic traffic simulation. Transportation Research Part C, 2002, 10(5-6): 351–371.
[35]王荣本,张荣辉,游峰等.智能车辆弧线跟踪控制算法.吉林大学学报, 2006, 36(5):731-735.
[36]高振海.汽车方向预瞄式自适应PD控制算法.机械工程学报, 2004, 40(5): 101-105.
[37] S. Halle, J. Laumonier, B. Chaib. A decentralized approach to collaborative driving coordination. 7th International IEEE Conference on Intelligent Transportation Systems, 2004: 453-458.
[38]吴青,何智伟,初秀民,宗成强.智能车路系统中汽车列队行驶控制关键技术与研究进展.交通与计算机, 2008, 4(26): 154-157.
[39] P. Seiler, A. Pant, K. Hedrick. Disturbance propagation in vehicle strings. IEEE Transactions on Automatic Control, 2004, 49(10): 1835-1841.
[40] Fenghui Wang, M. Yang, Ruqing Yang. Conflict-probability-estimation-based overtaking for intelligent vehicles. IEEE Transactions on Intelligent Transportation Systems, 2009, 10(2): 366-370.
[41] DAVIS G A, SWENSON T. Field study of gap acceptance by left-turning drivers. Transportation Research Record, 2004(1899):71-75.
[42]孙一飞.多智能车辆系统的多车协调和协作算法仿真研究[硕士论文].上海:上海交通大学, 2007.
[43]曲昭伟,金勇,陈永恒,等.提前右转组织方式及其影响分析.交通运输工程学报,2008, 8 (2) :106-109.
[44]张昊,马旭,卓晴.基于电磁场检测的寻线智能车设计.电子产品世界, 2009(11): 48-50.
[45]李仕伯,马旭,卓晴.基于磁场检测的寻线小车传感器布局研究.电子产品世界. 2009(12):41-44
[46]周润景,张丽娜,丁莉.基于PROTEUS的电路及单片机设计与仿真(第2版).北京:北京航空航天大学出版社, 2009.
[47]鲁哨廷.多波形数字信号发生器的设计与实现.微处理机. 2008(2):149-151.
[48]于春锐,韩方景,欧阳志宏,李霖.基于DDS的调频信号发生器的设计与仿真.电子产品世界. 2010(6):37-39.
[49]马文杰.基于DSS技术的程控信号发生器的研究[硕士论文].南京:南京林业大学, 2009
[50]李海涛.多频段多波形信号发生器设计构想.潍坊高等职业教育. 2009, 5(1):60-61.
[51] Moshe A Pollatschek, Abishai Polus, Moshe Livneh. A decision model for gap acceptance and capacity at intersections. Transportation Research Part B:Methodological,2002,36(7):649-663.
[52]孙一飞,杨明,杨汝清.基于冲突表的多智能车路口协调算法及其仿真实现.计算机应用研究, 2007.
[53] Chin H C, Quek S T. Measurement of traffic conflicts. Safety Science, 1997, 26(3): 169-185.
[54]杨建国,王兆安,李庆丰.混杂交通微观仿真初探.系统仿真学报, 2004, 16(6): 1115-1117.
[55]罗珀.博弈论导论及其应用.北京:中国政法大学出版社, 2005.
[56]施锡铨.博弈论.上海:上海财经大学出版社, 2000.
[57]赵晓华,李振龙,于泉,等.基于Q学习算法的两交叉口信号灯博弈协调控制.系统仿真学报, 2007, 19(18): 4253-4256.
[58]郭鹏,杨晓琴.博弈论与纳什均衡.哈尔滨师范大学自然科学学报. 2006, 22(4):25-28.
[59]李斌,王荣本,施树明,王志中.高速公路智能超车系统设计. ITS通讯. 2000, 4(2):44-52.
[60] T. Shamir. How should an autonomous vehicle overtake a slower moving vehicle: design and analysis of an optimal trajectory. IEEE Transactions on Automatic Control. 2004, 49:607–610.
[61]游峰.智能车辆自动换道与自动超车控制方法的研究[博士论文].长春:吉林大学, 2005
[62] J.M. Contet, F. Gechter, P. Gruer, Abder Koukam. Evaluation of global system state thanks to local phenomenon. proceedings of the18th European Conference on Arti?cial Intelligence ECAI. 2008: 865-866 .