高速公路环境中基于预测控制的自主车辆避障控制
|
摘要
随着我国经济的迅速发展,人们生活水平的提高,汽车已经成为当今社会人们日常生活中的重要组成部分。非职业化驾驶员的队伍不断扩大和汽车数量不断增加等因素导致交通事故发生率不断上升,给人民生命财产带来了巨大的损失。高速公路中车辆行驶速度快的特点提高了社会效率,增加了车辆行驶安全性,同时也使高速公路中交通事故的后果更加严重,车辆安全问题已经受到社会各界的广泛关注。保险杠、安全带和安全气囊等被动安全技术能够在发生交通事故后尽可能保护乘客安全,减小人们在交通事故中的受伤程度,但是不能有效防止交通事故的发生。随着汽车安全理念在人们头脑中不断改变和完善,被动安全技术已经无法满足人们对车辆安全性能的要求,研究车辆的主动安全技术已经成为国内外研究的热点。研究高速公路环境中自主车辆避障问题,对提高车辆的安全性能、发展车辆主动安全技术具有十分重要的意义,也是本文的主要研究内容。
本文首先对车辆“自行车”模型进行合理假设和简化得到车辆二自由度模型的状态空间形式,并以此为基础设计了车辆巡航和并线操作的预测控制算法。为满足车辆行驶过程中的侧向稳定性要求,将车辆质心侧向加速度作为控制算法中的约束。由于车辆二自由度模型是在纵向速度不变的假设下得到的,因而不能用车辆二自由度模型设计减速操作的控制算法。本文在对车辆“自行车”模型进行研究的基础上,采用微分平坦的方法将车辆非线性系统的控制问题转化为非线性规划问题进行求解,设计了车辆减速操作的基于微分平坦预测控制算法。
车辆在高速公路中行驶,周围的环境极其复杂并且动态变化,单一的控制算法无法使车辆在高速公路上安全行驶。因此,本为对高速公路环境进行分析,采用数学语言对高速公路车道、车道安全性和可用性、车辆与障碍物之间的距离等高速公路结构化环境进行描述。在对车辆行驶过程中制动过程进行分析的基础上,定义了车辆的制动距离、临界安全距离和安全距离。结合高速公路结构化环境描述与安全距离的定义,根据车辆在高速公路中的行驶规则制定了高速公路环境中车辆安全行驶策略。
传统的基于数值计算的车辆动力学仿真将结果以数据、图或表格的方法展现出来。这种仿真方法运算速度快、对机器要求不高,但是结果刻板、信息串行、不够主观形象。本文采用文本编辑器VrmlPad搭建高速公路虚拟现实模型,采用三维画图软件辅助设计的方法搭建车辆虚拟现实模型,结合本文设计的GUI用户界面和实验室已有的14自由度车辆模型,完成虚拟现实环境下车辆动力学仿真平台的搭建。在仿真平台中的仿真结果充分展示了该平台能够将仿真结果生动、形象、人们易于理解的方式显示出来。
本文的工作有很多地方还需要进一步的深入研究。例如车辆安全行驶策略的仿真是在直线道路工况下进行的,在曲线道路工况下的仿真还有很多工作要做,进一步对本文提出的控制策略和控制算法的有效性进行验证；本文搭建的虚拟现实仿真平台能够生动形象地显示车辆的运动姿态和周围环境动态信息,但是对车辆侧向加速度等变量缺乏量的刻画,因此虚拟现实仿真平台还需要进一步完善。
With the rapid development of China's economy and the improvement of people'slive, the car has become an important part in modern people's daily lives. The increasingnumber of non-professional drivers and trafc density has lead to rising accident rates,and brought great losses to people's lives and property. The characteristics of fast trafcspeed in highway improve social efciency, and increase vehicle security, but also takemore seriously consequences of highway trafc accidents. More and more concern hasbeen focused on trafc safety in modern society. Bumpers, seat belts, airbags and otherpassive safety technology protect the safety of passengers in a trafc accident as far aspossible, reduce the degree of injury in a road accident, but can't prevent trafc accidentsefectively.As the vehicle safety concept in people's minds has been changing and improv-ing, the passive safety technology has been unable to meet the requirements of vehiclesafety performance, and the research of vehicle active safety technology has become a hottopic at home and abroad. The study of autonomous vehicles obstacle avoidance prob-lem in highway has great significance to improve the safety performance of vehicles anddevelop the active safety technology, and is also the main contents of this article.
Firstly, through a reasonable assumption and simplification of vehicle”bicycle”model, we get a state space form of the vehicle two degrees model, and design predictivecontrol algorithms for vehicle cruise and overtake operations. To meet the lateral stabilityrequirements of vehicles travelings on the road, the lateral acceleration of vehicle masswas chosen as a constraint in the control algorithms.
When vehicles traveling on the highway, the surrounding environment are extremelycomplex and are changing dynamically. And single control algorithm can't make thevehicle driving safely on the highway. Therefore, after the highway environment wasanalyzed, the highway structured environments is described with mathematical language,such as the highway lane, lane security, the lane availability, the distance between vehiclesand obstacles. Based on the analysis of the vehicle braking process, this contributiondefines the vehicle's braking distance, critical safe distance and a safe distance. According to the trafc rules, the paper develops a safe driving strategy for vehicles driving on thehighway with the combination of the description of highway structure environmental andthe definition of the safe distance.
The traditional vehicle dynamics simulation based on numerical calculation showthe results with data, figures, or table. This simulation method runs fast and has nospecial requirement for computers. But the results are inflexible and not subjective image,the information is stereotypical serial. This paper builds highway virtual reality modelwith text editor VrmlPad, and builds vehicle with three-dimensional drawing software.Combing the virtual reality models with the graphic user interface and our laboratory's14degrees of freedom vehicle model, a vehicle dynamics virtual reality simulation platformis built. The simulation results show that the platform displays simulation results with avivid and easy-to-understand way.
There are still some topics that deserve further study. For example, the simulationenvironment of the vehicle safe driving strategy is straight road. Much work needs to bedone for further validating the efectiveness of the proposed control strategy and controlalgorithm on curved roads; although the virtual reality simulation platform in the paperis able to vividly display the vehicle's athletic stance and dynamic information of thesurrounding environment, it shows a lack of characterization of the amount of vehiclelateral acceleration, and other variables. So the virtual reality simulation platform stillneeds further improvement.
本文首先对车辆“自行车”模型进行合理假设和简化得到车辆二自由度模型的状态空间形式,并以此为基础设计了车辆巡航和并线操作的预测控制算法。为满足车辆行驶过程中的侧向稳定性要求,将车辆质心侧向加速度作为控制算法中的约束。由于车辆二自由度模型是在纵向速度不变的假设下得到的,因而不能用车辆二自由度模型设计减速操作的控制算法。本文在对车辆“自行车”模型进行研究的基础上,采用微分平坦的方法将车辆非线性系统的控制问题转化为非线性规划问题进行求解,设计了车辆减速操作的基于微分平坦预测控制算法。
车辆在高速公路中行驶,周围的环境极其复杂并且动态变化,单一的控制算法无法使车辆在高速公路上安全行驶。因此,本为对高速公路环境进行分析,采用数学语言对高速公路车道、车道安全性和可用性、车辆与障碍物之间的距离等高速公路结构化环境进行描述。在对车辆行驶过程中制动过程进行分析的基础上,定义了车辆的制动距离、临界安全距离和安全距离。结合高速公路结构化环境描述与安全距离的定义,根据车辆在高速公路中的行驶规则制定了高速公路环境中车辆安全行驶策略。
传统的基于数值计算的车辆动力学仿真将结果以数据、图或表格的方法展现出来。这种仿真方法运算速度快、对机器要求不高,但是结果刻板、信息串行、不够主观形象。本文采用文本编辑器VrmlPad搭建高速公路虚拟现实模型,采用三维画图软件辅助设计的方法搭建车辆虚拟现实模型,结合本文设计的GUI用户界面和实验室已有的14自由度车辆模型,完成虚拟现实环境下车辆动力学仿真平台的搭建。在仿真平台中的仿真结果充分展示了该平台能够将仿真结果生动、形象、人们易于理解的方式显示出来。
本文的工作有很多地方还需要进一步的深入研究。例如车辆安全行驶策略的仿真是在直线道路工况下进行的,在曲线道路工况下的仿真还有很多工作要做,进一步对本文提出的控制策略和控制算法的有效性进行验证；本文搭建的虚拟现实仿真平台能够生动形象地显示车辆的运动姿态和周围环境动态信息,但是对车辆侧向加速度等变量缺乏量的刻画,因此虚拟现实仿真平台还需要进一步完善。
With the rapid development of China's economy and the improvement of people'slive, the car has become an important part in modern people's daily lives. The increasingnumber of non-professional drivers and trafc density has lead to rising accident rates,and brought great losses to people's lives and property. The characteristics of fast trafcspeed in highway improve social efciency, and increase vehicle security, but also takemore seriously consequences of highway trafc accidents. More and more concern hasbeen focused on trafc safety in modern society. Bumpers, seat belts, airbags and otherpassive safety technology protect the safety of passengers in a trafc accident as far aspossible, reduce the degree of injury in a road accident, but can't prevent trafc accidentsefectively.As the vehicle safety concept in people's minds has been changing and improv-ing, the passive safety technology has been unable to meet the requirements of vehiclesafety performance, and the research of vehicle active safety technology has become a hottopic at home and abroad. The study of autonomous vehicles obstacle avoidance prob-lem in highway has great significance to improve the safety performance of vehicles anddevelop the active safety technology, and is also the main contents of this article.
Firstly, through a reasonable assumption and simplification of vehicle”bicycle”model, we get a state space form of the vehicle two degrees model, and design predictivecontrol algorithms for vehicle cruise and overtake operations. To meet the lateral stabilityrequirements of vehicles travelings on the road, the lateral acceleration of vehicle masswas chosen as a constraint in the control algorithms.
When vehicles traveling on the highway, the surrounding environment are extremelycomplex and are changing dynamically. And single control algorithm can't make thevehicle driving safely on the highway. Therefore, after the highway environment wasanalyzed, the highway structured environments is described with mathematical language,such as the highway lane, lane security, the lane availability, the distance between vehiclesand obstacles. Based on the analysis of the vehicle braking process, this contributiondefines the vehicle's braking distance, critical safe distance and a safe distance. According to the trafc rules, the paper develops a safe driving strategy for vehicles driving on thehighway with the combination of the description of highway structure environmental andthe definition of the safe distance.
The traditional vehicle dynamics simulation based on numerical calculation showthe results with data, figures, or table. This simulation method runs fast and has nospecial requirement for computers. But the results are inflexible and not subjective image,the information is stereotypical serial. This paper builds highway virtual reality modelwith text editor VrmlPad, and builds vehicle with three-dimensional drawing software.Combing the virtual reality models with the graphic user interface and our laboratory's14degrees of freedom vehicle model, a vehicle dynamics virtual reality simulation platformis built. The simulation results show that the platform displays simulation results with avivid and easy-to-understand way.
There are still some topics that deserve further study. For example, the simulationenvironment of the vehicle safe driving strategy is straight road. Much work needs to bedone for further validating the efectiveness of the proposed control strategy and controlalgorithm on curved roads; although the virtual reality simulation platform in the paperis able to vividly display the vehicle's athletic stance and dynamic information of thesurrounding environment, it shows a lack of characterization of the amount of vehiclelateral acceleration, and other variables. So the virtual reality simulation platform stillneeds further improvement.
引文
[1]赵志刚.高速公路发展现状及前景分析[J].交通运输标准化,2009(8)：7173.[2]范振宇,王宇鹏.基于现代综合运输体系的高速公路发展阶段特征分析与展望[J].公路交通科技,2006,23(7)：150153.[3]蔡石渠.高速公路发展与两型社会建设[J].山西建筑,2009，35(11)：276277.[4]于萌.高速公路发展与经济增长的关系研究[D].河北大学：硕士论文,2006.[5]李金龙,孙晚华.高速公路交通事故成因分析及对策研究[J].中国安全科学学报,2005,15(1)：5963.[6]李家龙,邵毅明,付立家.高速公路交通事故成因分析及对策研究[J].公路交通技术,2007,9：120122.[7]胡光辉,仇雅丽.高速公路交通事故成因分析及对策研究[J].交通标准化,2008,8：5355.[8]HUANG Jl HUA M T. LTV controller design for vehicle lateral control under fault in rear sensors[J]. IEEE/ASME Trans Mechatronicsl,2005,10(1):1-7.[9]E ROBERT D S J BENTON. A static-output-feedback design procedure for robust emergency lateral control of a highway vehicle[J]. Control Systems Technology,2005,13(4):618-623.[10]邹小兵,蔡自兴.非完整移动机器人道路跟踪控制器设计及应用[J].控制与决策,2004,19(3)：319322.[11]韩献光,席裕庚,张钟俊.自主车技术[J].自动化学报,1992,18(5)：513561.[12]R SUKTHANKAR S B J HANCOCK. Adaptive Intelligent Vehicle Modules for Tactical Driving[J]. AAAI Report WS-96-04,1996:13-22.[13]孙振平.自主驾驶汽车智能控制系统[D].长沙国防科技大学：博士论文,2004.[14]刘汝卫,张钢,殷庆振,等.防抱死制动系统(ABS)发展现状及趋势[J].机械制造,2009，47(544)：5154.[15]皮大伟,陈南,王金湘.模糊逻辑在车辆稳定性控制系统中的应用[J].东南大学学报(自然科学版),2008,38(1)：4348.[16]董因平.高速汽车车道偏离预警系统研究[J].长春理工大学学报,2004,27(1)：4850.[17]王春磊.基于ZigBee的高速公路车辆防碰撞预警系统研究[D].哈尔滨工业大学学：博士论文,2010.[18]Y YAMAMURA H N Y SETO. An ACC Design Method for Achieving Both String Sta-bility and Ride Comfort [J]. Journal of System Design and Dynamics,2008,2(4):979-990.[19]B MULLER S G J DEUTSCHER. Trajectory Generation and Feedforward Control for Parking a Car[J]. IEEE International Conference on Control Applications,2006:163-168.[20]J JANSSON J J. Decision Making for Collision Avoidance Systems [J]. Society of Automotive Engineers,2002.[21]邓金城,黄席樾,邓小丽.汽车防撞系统中的危险估计与超车决策[J].计算机仿真,2004,21(11)：207210.[22]H JULA PIE KOSMATOPOULOS. Collision Avoidance Analysis for Lane Changing and Merging[J]. IEEE Transactions on Vehicular Technology,2000,49(6):2295-2308.[23]王晓原,杨新月.基于决策树的驾驶行为决策机制研究[J].系统仿真学报,2008,20(2)：415420.[24]闻育,吴铁军,周春芳,等.基于决策优化模型的驾驶行为建模方法[J].浙江大学学报,2006,40(4)：704708.[25]王韦钰,曲仕茹.基于模糊神经网络的自动驾驶决策系统研究[J].计算机测量与控制,2009,17(9)：17111713.[26]彭金栓,付锐,石磊磊,等.驾驶人车道变换决策分析[J].武汉理工大学学报,2011,33(12)：4650.[27]BELKHOUCHE F. Reactive Path Planning in a Dynamic Environment [J]. IEEE Transactions on Robotics,2009,25(4):902-911.[28]S GE A M X LAI. Sensor-based Path Planning for Nonholonomic Mobile Robots Subject to Dynamic Constraints [J]. Robotics and Autonomous Systems,2007,55:513-526.[29]C BOTTASSO B S D LEONELLO. Path Planning for Autonomous Vehicles by Trajec-tory Smoothing Using Motion Primitives [J]. IEEE Transactions on Control Systems Technology,2008,16(6):1152-1168.[30]J CARSTEN D F A RANKIN. Global Path Planning on Board the Mars Exploration Rovers [J]. IEEE Aerospace Conference,2007:1-11.[31]ZHANG Q. A Hierarchical Global Path Planning Approach for AUV Based on Ge-netic Algorithm [J]. IEEE International Conference on Mechatronics and Automation,2006:1745-1750.[32]O PINCHARD F P A LIEGEOIS. Generalized Polar Polynomials for Vehicle Path Generation with Dynamic Constraints[C].Proceedings of IEEE International Confer-ence on Robotics and Automation,IEEE Press,1996:915-920.[33]T SCHOUWENAARS E F J How. Receding Horizon Path Planning with Implicit Safety Guarantees[C].Proceedings of the American Control Conference. Boston: IEEE Press,2004:5576-5581.[34]J HILGERT T B K HIRSCH. Emergency Path Planning for Autonomous Vehicles Using Elastic Band Theory[C].Proceedings of IEEE/ASME International Conference on Advanced Intelligent Mechatronics. Germany:IEEE Press,2003:1390-1395.[35]E ARNOLD O S J NEUPERT. Trajectory Tracking for Boom Cranes Based on Nonlinear Control and Optimal Trajectory Generation[C].IEEE Conference on Con-trol Applications Part of Multi-conference on Systems and Control.[]:IEEE Press,2007:1444-1449.[36]C HARGRAVES S P. Direct Trajectory Optimization Using Nonlinear Programming and Collocation [J]. Control and Dynamics,1987,10(4):338-342.[37]A HERMAN B C. Direct Optimization Using Collocation Based on Highorder Gauss-Lobatto Quadrature Rules[J]. Control and Dynamics,1996,19(3):592-599.[38]R BHATTACHARYA P S. Nonlinear Trajectory Generation Using Global Local Approximations[C].Proceedings of IEEE Conference on Decision and Control,IEEE Press,2006:6802-6807.[39]M VAN NIEUWSTADT R M. Approximate Trajectory Generation for Differentially Flat Systems with Zero Dynamics[C].Proceedings of the34th IEEE Conference on Decision and Contro,IEEE Press,1995:4224-4230.[40]M VAN NIEUWSTADT R M. Real Time Trajectory Generation For Differentially Flat Systems[J]. International Journal of Robust and Nonlinear Control,1998,8(11):995-1020.[41]丛岩峰,喻再涛,宋金泽.车辆变动力学约束下基于微分平坦的滚动运动规划[C].“视听觉信息的认知计算”学术交流会.西安,2010：236241.[42]CONG YANFENG CIIOS Yu ZAITAO. Flatness-Based Vehicle Online Path Follow-ing with Time-varying Constraints of Dynamics[C].Proceedings of the2011Chinese Control and Decision Conference IEEE Press,2011:3385-3390.[43]丛岩峰,陈虹,OLIVER S,等.车辆高速公路环境下基于微分平坦的紧急避障预测控制[C].第30界中国控制会议.烟台,2011：35433548.[44]RIEKERT P, SCHUNK T. Zur Fahrmechanik des gummibereiften Kraftfahrzeugs[J]. Ingenieur-Archivs,1940,11:210-224.[45]SAYERS M W, HAN D. A Generic Multibody Vehicle Model for Simulating Han-dling and Braking[J]. Vehicle Systems Dynamics:International of Vehicle Mechanics Mobility,2001,25(1):599-613.[46]崔胜民,肖利寿,宋宝玉,等.汽车操纵动力学十八自由度模型仿真研究[J].汽车工程),1998,20(4)：212219.[47]杨得军,林柏忠,管欣,等.用于开发型驾驶模拟器的17自由度汽车动力学仿真的数学模型及算法[J].汽车技术,2002,12：610.[48]丛岩峰.高速公路环境中自主驾驶车辆运动规划与控制[D].吉林大学：博士毕业论文,2011.M. FLIESS P M J. LEVINE, ROUCHON P. Sur les systemes non lineaires differen-tiellement plats[J]. C.R. Acad,1992:619-624.[50]M. FLIESS P M P R J. LEVINE. Flatness and defect of nonlinear systems:intro-ductory theory and examples[J]. Int. J. Control,1995,61(6):1327-1361.[51]MARTIN P. Contribution al'etude des systemes differentiellements plats[M]. Ecole des Mines de Paris:PhD Thesis,1992.[52]M. FLIESS P M F O J. LEVINE, ROUCHON P. Systems and control in the Twenty-First Century [J]. Progress in Systems and Control Theory,1997.[53]PII. MARTIN P R R. M. MURRAY. Flat systems[J].1997:211-264.[54]PII. MARTIN P R R. M. MURRAY. Flat systems:equivalence and trajectory gen-eration[J]. Technical report,2003:1-81.[55]赵海艳,陈虹,李姝,等.基于微分平坦的双电机雨刮系统控制器设计[C].第29界中国控制会议.北京,2010：35613565.[56]BINGZHAO GAO Y H HONG CIIEN, SANADA K. Nonlinear feedforward-feedback control of clutch-to-clutch shift technique [J]. Vehicle System Dynamics,2011:1-17.[57]FLORES M E, MILAM M B. Trajectory Generation for Differentially Flat Systems via NURBS Basis functions with Obstacle Avoidance[C].Proceedings of the2006American Control Conference Minneapoli. Minnesota,2011:1-17.[58]丛岩峰,安向京,陈虹,等.基于滚动优化原理的类车机器人路劲跟踪控制[J].吉林大学学报(工学版),2012,42(1)：1822187.[59]STEFAN FUCHSHUMER K S, RITTERSCHOBER T. Nonlinear Vehicle Dynamics Control-A Flatness Based Approach[C].Proceeding of the44th IEEE Conference on Decision and Control, and the European Control Conference2005Seville. Spain,2005:12-15.[60]余志生.汽车理论[M].北京：机械工业出版社,2000.[61]郑茂才.考虑牵扯减速状况的跟随车安全距离分析[J].湖南交通科技,2011,6(37)：190193.[62]钟勇,姚剑峰.行进中车辆临界安全车距的探讨[J].湖南大学学报,2011,28(6)：5459.[63]徐龙文,邵子法.机助绘图时画平行曲线的一种算法[J].地图,1989,4：5155.