智能车自主驾驶控制系统研制与试验
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摘要
随着世界范围内汽车普及率的提高,汽车在极大地方便人们生活的同时也带来了大量问题,如交通安全问题、城市交通拥挤和环境污染等。运用高新技术,将现有的道路和车辆综合起来考虑,构建智能交通系统来解决交通问题是真正切实可行的办法。依靠车辆智能控制,提高道路车流密度,同时,减少控制对象,增加交通可控性,能有效减缓交通拥堵,增强交通安全。智能车辆作为智能交通系统的关键技术,是一个集环境感知、规划决策、多等级辅助驾驶等功能于一体的复杂系统,如何利用其相关技术实现智能交通系统的效用,正处于不断发展与完善中。因此,利用各种先进实验交通技术构建研究平台是非常必要的。
文中在建立1：10具有各种高速公路设施的模拟道路沙盘的基础上,以智能模型车(以下简称智能车)为研究对象,围绕着智能车自主驾驶控制系统的完成展开研究。搭建了一个基于TMS320F2812主控器的智能车控制系统的实验平台。
概括介绍了智能车辆的发展现状；对智能车控制系统总体设计进行了讨论,确定了智能车控制系统的硬件组成,设计了智能车控制系统的硬件结构,包括转向舵机的改装和传感器的安装两个部分,完成了对智能车控制系统硬件的功能分析,从而确定了智能车控制系统的硬件设计和软件设计方案。智能车控制系统的硬件设计从电源转换模块设计开始,完成DSP最小系统,电平转换模块,舵机和电机驱动控制模块以及串口模块等的设计；同时智能车控制系统软件设计从DSP的片上功能入手,完成智能车控制系统软件主程序的初始化设置,接着对智能车自主驾驶所需的功能函数进行了设计,包括标识线识别,转向舵机控制和智能车速度控制算法三个方面；设计了智能车监控软件,可以显示和储存智能车在模拟道路沙盘上的运动信息。开展智能车自主驾驶试验,通过试验,验证了控制系统的有效性。
With its increased penetration worldwide, automotive brings a lot of problems, such as traffic safety, urban congestion and environmental pollution, while it greatly facilitates human life. It is the very practical way to solve the traffic problem that constructing intelligent transportation system with an overall consideration of the existing road integrated with vehicles and by means of high technology. The intelligent transportation system can improve vehicle density rely on the intelligent control for vehicles, meanwhile, it can reduce the control object, and increase traffic controllability, thus effectively relieve the traffic congestion and enhance traffic safety. Intelligent vehicle, as the key technology in the intelligent transportation system, is a complex system with environment perception, planning decision, and multi-level driver-assistance rolled into one, and how to use the relevant technology to realize the effectiveness of the intelligent transportation system is right in continuous development. Therefore, it is necessary to build experimental platform by using a variety of advanced transportation technology.
Based on the established simulated road sand table that consists of one tenth closed road that simulates various freeway infrastructures, the thesis takes intelligent model car (hereinafter referred to as intelligent vehicles) as the research object, conducts research around the intelligent control system for autonomous vehicle. A hardware circuit system based on TMS320F2812 processor is designed. The main comments and contributions of this thesis are as follows:
First, an overview of the development of intelligent vehicles is introduced. Second, the thesis discusses an overall design of the intelligent control system, defines the hardware of its system, designs the hardware structure mainly including the installation of steer engine and sensors, then completes the functional analysis of its system, which determines the hardware circuit design and software design of the intelligent control system. The hardware design starts with the power conversion module, designs DSP minimum system, electrical level conversion module, steer engine and motor drive module, and serial communication interface module. Meanwhile, the software design starts with the DSP chip function, completes the initialization of main program of software, the performance function required by the intelligent control system for autonomous vehicle, including the algorithm about road lane markings identification, steer engine control, and speed control, and then designs a monitoring software that can display and store the motion information about autonomous vehicle driving along the simulated road sand table. Finally, autonomous vehicle driving test has been carried out, and the availability of the control system has been illustrated by test results.
文中在建立1：10具有各种高速公路设施的模拟道路沙盘的基础上,以智能模型车(以下简称智能车)为研究对象,围绕着智能车自主驾驶控制系统的完成展开研究。搭建了一个基于TMS320F2812主控器的智能车控制系统的实验平台。
概括介绍了智能车辆的发展现状；对智能车控制系统总体设计进行了讨论,确定了智能车控制系统的硬件组成,设计了智能车控制系统的硬件结构,包括转向舵机的改装和传感器的安装两个部分,完成了对智能车控制系统硬件的功能分析,从而确定了智能车控制系统的硬件设计和软件设计方案。智能车控制系统的硬件设计从电源转换模块设计开始,完成DSP最小系统,电平转换模块,舵机和电机驱动控制模块以及串口模块等的设计；同时智能车控制系统软件设计从DSP的片上功能入手,完成智能车控制系统软件主程序的初始化设置,接着对智能车自主驾驶所需的功能函数进行了设计,包括标识线识别,转向舵机控制和智能车速度控制算法三个方面；设计了智能车监控软件,可以显示和储存智能车在模拟道路沙盘上的运动信息。开展智能车自主驾驶试验,通过试验,验证了控制系统的有效性。
With its increased penetration worldwide, automotive brings a lot of problems, such as traffic safety, urban congestion and environmental pollution, while it greatly facilitates human life. It is the very practical way to solve the traffic problem that constructing intelligent transportation system with an overall consideration of the existing road integrated with vehicles and by means of high technology. The intelligent transportation system can improve vehicle density rely on the intelligent control for vehicles, meanwhile, it can reduce the control object, and increase traffic controllability, thus effectively relieve the traffic congestion and enhance traffic safety. Intelligent vehicle, as the key technology in the intelligent transportation system, is a complex system with environment perception, planning decision, and multi-level driver-assistance rolled into one, and how to use the relevant technology to realize the effectiveness of the intelligent transportation system is right in continuous development. Therefore, it is necessary to build experimental platform by using a variety of advanced transportation technology.
Based on the established simulated road sand table that consists of one tenth closed road that simulates various freeway infrastructures, the thesis takes intelligent model car (hereinafter referred to as intelligent vehicles) as the research object, conducts research around the intelligent control system for autonomous vehicle. A hardware circuit system based on TMS320F2812 processor is designed. The main comments and contributions of this thesis are as follows:
First, an overview of the development of intelligent vehicles is introduced. Second, the thesis discusses an overall design of the intelligent control system, defines the hardware of its system, designs the hardware structure mainly including the installation of steer engine and sensors, then completes the functional analysis of its system, which determines the hardware circuit design and software design of the intelligent control system. The hardware design starts with the power conversion module, designs DSP minimum system, electrical level conversion module, steer engine and motor drive module, and serial communication interface module. Meanwhile, the software design starts with the DSP chip function, completes the initialization of main program of software, the performance function required by the intelligent control system for autonomous vehicle, including the algorithm about road lane markings identification, steer engine control, and speed control, and then designs a monitoring software that can display and store the motion information about autonomous vehicle driving along the simulated road sand table. Finally, autonomous vehicle driving test has been carried out, and the availability of the control system has been illustrated by test results.
引文
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[2]任殿波.自动化公路系统车辆纵横向控制[D].成都：西南交通大学,2008.
[3]郝宇赟.自主汽车的智能纵向控制与实现研究[D].天津：天津大学,2006.
[4]徐友春,王荣本,李兵,等.世界智能车辆近况综述[J].汽车工程,2001,23(5)：289-295.
[5]尹念东.智能车辆的研究及前景[J].上海汽车,2002(4)：40-42
[6]李贻斌.ITS智能车辆关键技术研究[D].天津：天津大学,2008
[7]于少伟.智能车辆控制的关键技术研究[D].淄博：山东理工大学,2008
[8]周勇.智能车辆中的几个关键技术研究[D].上海：上海交通大学,2007
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[11]Dickmanns, E.D., Behringer, R., Dickmanns, D., et al. The seeing passenger car 'VaMoRs-P'[C]//. Proceedings of the Intelligent Vehicles Symposium, Neubiberg, Oct.24-26,1994.
[12]Behringer, R.. Road recognition from multifocal vision[C]//. Proceedings of the Intelligent Vehicles Symposium, Neubiberg, Oct.24-26,1994.
[13]Broggi, A., Bertozzi, M., Fascioli, A.. ARGO and the MilleMiglia in automatico tour[J]. IEEE Intelligent Systems and their Applications,1999,14(1):55-64.
[14]Bertozzi, M., Broggi, A., Conte, G., et al. Obstacle and lane detection on ARGO[C]//. IEEE Conference on Intelligent Transportation System, Boston, MA, Nov.9-12,1997.
[15]Chapuis, R., Potelle, A., Brame, J. L., et al. Real-time Vehicle Trajectory Supervision on the Highway[J]. International Journal of Robotics Research,1995,14(6):531-542
[16]邵春福,王颖.日本智能交通系统的现状及其发展战略[C]//.中国系统工程学会城市智能交通系统学术会议论文集,北京,Nov.1,2000.
[17]Kurtz, J.. Demo Ⅲ experimental unmanned vehicle autonomous mobility system overview[C]//. Proceedings of the IEEE International Symposium on Intelligent Control, Gaithersburg, MD, Sep.14-17,1998.
[18]Albus, J., Murphy, K., Lacaze, A., et al.4D / RCS sensory processing and world modeling on the Demo Ⅲ Experimental unmanned ground vehicles[C]//. Proceedings of the IEEE International Symposium on Intelligent Control,2002.
[19]欧青立,何克忠.室外智能移动机器人的发展及其关键技术研究[J].机器人,2000,22(6)：519-526.
[20]杨欣欣,何克忠,郭木河,等.基于神经网络的室外移动机器人前轮转向模型[J].自动化学报,2000,26(2)：154-161.
[21]郭木河,杨磊,陶西平,等.视觉导航中基于模糊神经网的消阴影算法研究[J].软件学报,1999,10(2)：155-159.
[22]王荣本,马雷.新型视觉自动引导车辆导航控制器设计[J].公路交通科技,2003,20(4)：84-87.
[23]王荣本,储江伟,冯炎,等.一种视觉导航的实用型AGV设计[J].机械工程学报,2002,38(11)：135-138.
[24]孙振平,安向京,贺汉根CITAVT-Ⅳ——视觉导航的自主车[J].机器人,2002,24(2)：115-121.
[25]刘铁,郑南宁.基于变形模板和遗传算法的道路检测方法[J].模式识别与人工智能,2004,17(2)：32-34.
[26]李青,郑南宁,马琳等.基于主元神经网络的非结构化道路跟踪[J].机器人,2005,27(3)：35-39.
[27]宋养鸼.竞赛用智能汽车控制系统的研究[D].兰州：兰州理工大学,2009.
[28]胡杰.基于16位单片机MC9S12DG128智能模型车系统开发研究[D].武汉：武汉理工大学,2008.
[29]孙振平.自主驾驶汽车智能控制系统[D].长沙：国防科学技术大学,2004.
[30]李旭.自主车辆多传感器导航与横向鲁棒控制的研究[D].南京：东南大学,2005.
[31]徐友春,李克强.智能车辆机器视觉发展近况[J].汽车工程,2003,25(5)：438-443.
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