汽车防撞预警相关路面状态识别的研究
|
摘要
本文研究了一种新型的基于路面状态识别的车辆防撞预警系统,在实时识别路面特征基础之上,判别路面是水泥还是沥青,是干燥、湿滑还是冰层路面,再此基础上推算出路面附着力,为车辆制动时最大减速度的判别提供理论和数据支持.并在此基础上建立起安全距离模型,通过matlab仿真,构建起基于模糊理论的防撞预警系统.
本文完成路面特征实时识别,分析了路面特征差异及车轮振动激励源,通过建立车轮振动模型,将车轮振动频谱作为路面特征分类的特征空间,以车轮高频振动频谱特征向量作为输入,构造神经网络分类器,并利用分类器识别水泥混凝土路面特征和沥青SMA路面特征.
本文还完成路面状态湿滑、干燥、冰层的识别。研究得知路面温度与路面湿滑状态以及太阳辐射强度之间存在非线性关系,本文以路面温度和太阳辐射强度为输入构造BP神经网络分类器,实现路面湿滑状态的识别。
建立安全距离模型,研究了基于路面识别的防撞预警系统设计,分析了制动过程,探讨了模型中几个重要参数并在此基础上建立起安全距离模型,研究了基于模糊逻辑算法的防撞系统参数设定。在车辆防撞预警系统中,充分考虑到各种变量具有较大的随机性和模糊性,将路面特征、路面湿滑、天气等状况、驾驶员反应速度等量定义模糊子集,编辑模糊规则,对其进行仿真,确立最大减速度,可以实现安全距离准确预测及危险状态的预警。
本文完成防撞预警系统的现场试验及数据采集,进行了仿真测试比较,并建立起远程监控平台,实现基于路面识别的防撞预警系统的设计。通过现场试验,采集车轮振动加速度的数据,通过单子带重构改进算法,利用RBF神经网络识别水泥和沥青路面,识别准确率达到90%以上;然后进行了路面温度和空气温度湿度监测,采集实时路面温度和空气温度湿度,用有线和无线两种方式实现温度数据的采集,并建立采集监控子系统,将采集的数据,在matlab中作为输入搭建BP网络识别路面湿滑、干燥和冰层的判决。最后,利用识别的路面类型和湿滑状况,建立防撞预警系统,并通过模糊算法仿真,相对于不同的路面状态和车速,计算出车辆间安全距离,并及时向行驶中的车辆发出预警,实现主动防撞,保障行车安全。
In summary, we carry out a research on a vehicle anti-collision warning system based on road condition detection. This system colletcts real time features of the road to determine the road types, cement of SMA, and the surface condition, dry, wet or icy.Then,it calculates road adhesion coefficient related to the size of braking distance based on the collected data.Besides,we establish a model to measure braking distances. Finally, through the Matlab simulation, we construct a collision warning system based on the Fuzzy theory.
The method to detect road types is by following subsequent steps:a) Analyzes different road surface characteristics and the wheel vibration excitation source b) Establishes a wheel vibration model, the wheel vibration spectrum is considered as the feature space of the feature classification c) Constructs a neural network classifier with the wheel frequency vibration spectrum eigenvectors as the input to identify the features of cement and the SMA features of bitumen.
The method to detect road conditions is also described in this paper. Road temperature depends on road condition (dry, wet and icy) and solar radiation, and there is the nonlinear causality among them, thus, road condition can be identified indirectly by road temperature and solar radiation with BP neural network.
Furthermore, with the establishment of braking distance model, we study the design of anti-collision warning system based on road detection, analyze the braking process, discuss the important parameters of the model, and investigate into the parameter settings of the anti-collision system based on the Fuzzy theory. Due to a variety of complex variables, considering the great randomness and fuzziness, road type, road condition, weather, reaction speed of the driver are considered as the fuzzy subset. The maximum velocity is determined by running a simulation of the subset, then, braking distance prediction and risk early warning is realized.
At the end, we bring out the design of a vehicle anti-collision warning system based on road condition detection by comparison between the simulated results and the on-site test. We use RBF neural network and Single-band reconstruction algorithm to analyze the collected wheel vibration acceleration to identify road type with90%accuracy. We establish a temperature monitoring system to collect road surface temperature, air temperature and humidity and transmit them through wired or wireless channels to the BP network to determine the road condition. Finally, we use the road type and the road condition to build up an anti-collision warning system. It uses the Fuzzy theory to calculate the safe distance and sets out precautions to avoid collisions.
本文完成路面特征实时识别,分析了路面特征差异及车轮振动激励源,通过建立车轮振动模型,将车轮振动频谱作为路面特征分类的特征空间,以车轮高频振动频谱特征向量作为输入,构造神经网络分类器,并利用分类器识别水泥混凝土路面特征和沥青SMA路面特征.
本文还完成路面状态湿滑、干燥、冰层的识别。研究得知路面温度与路面湿滑状态以及太阳辐射强度之间存在非线性关系,本文以路面温度和太阳辐射强度为输入构造BP神经网络分类器,实现路面湿滑状态的识别。
建立安全距离模型,研究了基于路面识别的防撞预警系统设计,分析了制动过程,探讨了模型中几个重要参数并在此基础上建立起安全距离模型,研究了基于模糊逻辑算法的防撞系统参数设定。在车辆防撞预警系统中,充分考虑到各种变量具有较大的随机性和模糊性,将路面特征、路面湿滑、天气等状况、驾驶员反应速度等量定义模糊子集,编辑模糊规则,对其进行仿真,确立最大减速度,可以实现安全距离准确预测及危险状态的预警。
本文完成防撞预警系统的现场试验及数据采集,进行了仿真测试比较,并建立起远程监控平台,实现基于路面识别的防撞预警系统的设计。通过现场试验,采集车轮振动加速度的数据,通过单子带重构改进算法,利用RBF神经网络识别水泥和沥青路面,识别准确率达到90%以上;然后进行了路面温度和空气温度湿度监测,采集实时路面温度和空气温度湿度,用有线和无线两种方式实现温度数据的采集,并建立采集监控子系统,将采集的数据,在matlab中作为输入搭建BP网络识别路面湿滑、干燥和冰层的判决。最后,利用识别的路面类型和湿滑状况,建立防撞预警系统,并通过模糊算法仿真,相对于不同的路面状态和车速,计算出车辆间安全距离,并及时向行驶中的车辆发出预警,实现主动防撞,保障行车安全。
In summary, we carry out a research on a vehicle anti-collision warning system based on road condition detection. This system colletcts real time features of the road to determine the road types, cement of SMA, and the surface condition, dry, wet or icy.Then,it calculates road adhesion coefficient related to the size of braking distance based on the collected data.Besides,we establish a model to measure braking distances. Finally, through the Matlab simulation, we construct a collision warning system based on the Fuzzy theory.
The method to detect road types is by following subsequent steps:a) Analyzes different road surface characteristics and the wheel vibration excitation source b) Establishes a wheel vibration model, the wheel vibration spectrum is considered as the feature space of the feature classification c) Constructs a neural network classifier with the wheel frequency vibration spectrum eigenvectors as the input to identify the features of cement and the SMA features of bitumen.
The method to detect road conditions is also described in this paper. Road temperature depends on road condition (dry, wet and icy) and solar radiation, and there is the nonlinear causality among them, thus, road condition can be identified indirectly by road temperature and solar radiation with BP neural network.
Furthermore, with the establishment of braking distance model, we study the design of anti-collision warning system based on road detection, analyze the braking process, discuss the important parameters of the model, and investigate into the parameter settings of the anti-collision system based on the Fuzzy theory. Due to a variety of complex variables, considering the great randomness and fuzziness, road type, road condition, weather, reaction speed of the driver are considered as the fuzzy subset. The maximum velocity is determined by running a simulation of the subset, then, braking distance prediction and risk early warning is realized.
At the end, we bring out the design of a vehicle anti-collision warning system based on road condition detection by comparison between the simulated results and the on-site test. We use RBF neural network and Single-band reconstruction algorithm to analyze the collected wheel vibration acceleration to identify road type with90%accuracy. We establish a temperature monitoring system to collect road surface temperature, air temperature and humidity and transmit them through wired or wireless channels to the BP network to determine the road condition. Finally, we use the road type and the road condition to build up an anti-collision warning system. It uses the Fuzzy theory to calculate the safe distance and sets out precautions to avoid collisions.
引文
[1]陈明,汽车主动防撞预警系统的路面识别研究,《吉林大学硕士论文》,2011,
[2]马骏.高速公路行车安全距离的分析与研究[J].西安公路交通大学学报,1998,18(4)：90-94.
[3]郑安文.高速公路行车间距分析与防追尾装置开发[J].武汉理工大学学报,2002,24(9)：62-65.
[4]肖梅.高速公路追尾碰撞预防报警系统再研究[D].西安：长安大学硕士论文,2003.
[5]刘刚,侯德藻等.汽车主动避撞系统安全报警算法[J]清华大学学报(自然科学版),2004,44(5)：697-700.
[6]侯德藻,刘刚.新型汽车主动避撞安全距离模型[J].汽车工程,2005,27(12)186-191.
[7]卢俊辉,巫世晶,基于车轮振动的路面实时研究[J],振动与冲击,2008,27(4),19-23
[8]John Laurent,Mario Talbot,Michel Doucet,Road surface inspection using laser scanners adapted for thehigh precision 3D measurements of large flat surfaces[C]. 3-D Digital Imaging and Modeling,International Conference on RecentAdvances, May 12-15,1997:303-310
[9]徐豪,汽车主动防撞预警系统避规控制研究,《吉林大学硕士论文》,2012
[10]边明远.汽车主动安全性控制系统路况识别技术纵览[J].汽车研究与开发,2002,(01)：31-33
[11]卢俊辉,巫世晶等,基于车轮振动的路面类型识别方法,江汉大学
[12]赵祥模等.基于PSD的路面粗糙度快速检测方法研究[J].光电子技术与信息,2004,17(2)：58-60
[13]余卓平,左建令,张立军.路面附着系数估算技术发展现状综述[J].汽车工程,2006,(06)：546-549.
[14]江文锋.行驶过程中轮胎与路面间附着性能的评价[D].长安大学,2008
[15]冯广刚.基于主被动集成的汽车安全控制系统建模与仿真[D].湖南大学,2008
[16]卢俊辉,基于路面温度和太阳辐射强度的路面状态识别方法,农业机械学报,2010,41(5),21-23
[17]FredriCkGustafsson.MonitoringTire—Road Frietion Using the Wheel slip.IEEEControlSystems,1998,(8):42-49.
[18]李智,张肖宁,雷尊贵,刘砥石,激光纹理仪在广惠高速公路沥青路面施工中的应用,[J],湖南交通科技,2006,(9)
[19]庄继德,汽车轮胎学[M]..北京：北京理工大学出版社,1996
[20]张克健,汽车地面力学[M]..北京：国防工业出版社,2002
[21]胡小弟,孙立军.轻型货车轮胎接地压力分布实测.公路交通科技.2005,22(8)：1-7
[22]Pieter L.Swart,Beatrys M.Lacquet.An Acoustic Sensor System for Determination of MacroscopicSurface Roughness[C].IEEE Transactions on Instrumentation and Measurement,vol.45,No.5,October1996
[23]A.Pohl,F.Seifert.Wirelessly Interrogable SAW-Sensors for Vehicular Aplications[C].IEEEInstrumentation and Measurement Technology Conference Brussels,Belgium,June 4-6,1996:1465-1468
[24]Alfred Pohl,Reinhard Steindl,Leonhard Reindl.The "Intelligent Tire"Utilizing Passive SAW Sensors Measurement of Tire Friction[C]. IEEE Transactions on Instrumentation Measurement, vol.48, No.6,December 1999:1041-1046
[25]韩建保,张鲁滨等.轮胎路面附着系数实时感应识别系统[J].汽车与动力技术,2005,(2)：62-64
[26]Alfred Pohl, Reinhard Steindl, Leonhard Reindl. IEEE The "Intelligent Tire"Utilizing Passive SAWSensors Measurement of Tire Friction[C]. IEEE Transactions on Instrumentation and Mesurement,vol.48, No.6, December 1999:1041-1046
[27]Jin-Oh Hahn,Rajesh Rajamani.GPS-Based Real-Time Identification of Tire-Road Friction Coefficient[C].IEEE Transactions on Control Systems Technology,vol.l0,No.3,May 2002:331-343
[28]Carloscanud Canuda-dei-Wit, Roberto Horowitz, Observers for Tire/road Contact Friction using onlywheel angular velocity information[C]. Proceedings of the 38th Conference on Decision & ControlPhoenix,Arizona USA Decembe1999:3932-3937
[29]Li Li, Fei-Yue Wang, Qunzhi Zhou.Integrated Longitudinal and Lateral Tire/Road Friction Modelingand Monitoring for Vehicle Motion Control[C].IEEE Transactions on Intelligent TransportionSystems,Vol.7,No.1,March 2006:1-19
[30]Yonggon Lee,Stanislaw H. Zak2.Genetic Neural Fuzzy Control of Anti-Lock Brake Systems[J].Proceedings of the American Control Conference,Arlington,VA June 25-27,2001:671-676
[31]P.Khatun, C.M.Bingham, Schofield, P.H.Mellor. Application of Fuzzy Control Algorithms forElectricVehicle Antilock Braking/Traction Control Systems. IEEE ransactions on VehicularTechnology,vol.52,No.5,september 2003:1356-1364
[32]宋健,陈在峰.制动器耗散功率最大为目标的ABS控制方法[J].清华大学学报(自然科学版),1997,37(12)：95-98
[33]宋健,李永.汽车防抱死制动系统控制方法的研究进展[J].公路交通科技,2002,19(6)：140-145
[34]吴锆,赵克刚等.附着系数-滑移率曲线的测定[J].华南理工大学学报(自然科学版),2001,29(9)：20-22
[35]李朝晖主编.公路工程基础[M].北京：人民交通出版社,2001
[36]邓学钧.路基路面工程[M].北京：人民交通出版社,2000
[37]Katsuhiro Asano, Shigenobu Okada, Norio Iwama. Vibration Suppression of Induction Motor DrivenHybrid Vehicle Using Wheel Torque Observer[C]. IEEE Transactions on IndustryAppaications,vol.28,No.2, March/april 1992:441-447
[38]左曙光,靳晓雄.轿车发动机振动传递系统建模与分析[C].2002年全国振动(诊断、模态、噪声与结构动力学)工程及应用学术会议论文集,北京,2002：502-506
[39]严世榕.影响汽车振动特性的几个参数研究[J].机械强度,2006,28(增刊)：22-25
[40]陈南主编,汽车振动与噪声控制[M].北京：人民交通出版社,2005
[41]Song Jian, Jin Ruichen. Generation of Virtual Road Surfaces and Simulation of Nonlinear Vibration ofVehicles[C].Vehicle Electronics Conference,1999. (IVEC '99) Proceedings of the IEEEInternational:355-359
[42]李忠国,张为公等.基于动载的路面不平度识别的小波特征提取[J].江苏大学学报(自然科学版),2007,28(4)：305-308
[43]Yue Jianhai,Qiu Zhengding. Application of Wavelet Transform to Defect Detection of Wheel flats ofRailway wheels[C].IEEE ICSP'02 Proceedings:29-32
[44]靳晓雄,张立军,江浩.汽车振动分析[M].上海：同济大学出版社,2002：5.
[45]杨建国等.小波分解与重建中产生频率混淆的原因与消除算法[J].振动与冲击,1994,31(2)：
[46]李艳彩.基于四轮模型的汽车ABS控制策略的研究[J].河北工业大学,2007.
[47]陈明,汽车主动防撞预警系统的路面识别研究,《吉林大学硕士论文》-2011-05-01
[48]许颖,基于模糊理论的车辆防碰撞预警系统研究,《湖南农业大学硕士论文》-2010-05-20
[49]董红召,陈炜烽,陈宁,郭明飞,车路集成环境下车辆防撞预警安全状态判别模型的研究[J],《汽车工程》,2011,33(9)：777-780
[50]连晋毅,华小洋.汽车防追尾碰撞数学模型研究[J].中国公路学报,2005,18(3)：123-126.
[51]李晓霞,李百川等.车辆追尾碰撞避免技术[J].西安公路交通大学学报,2001,21(2)：94-97
[52]马娟丽.汽车防撞系统的研究[D].西安：西北工业大学,2007.
[53]Zhiguo Zhao,Zhuoping Yu,Zechang Sun.Research On Fuzzy Road Surface Identification and LogicControl for Anti-lock Braking System[C].IEEE 2003:510-513
[54]杜雪松,解晓光,张小瑞,胡光胜,不同冰雪路面状态的抗滑特性研究[J],2012：127(10)：1-3
[55]吕江毅,宋建桐,刘敏杰,汽车制动时湿滑路面对运行状态的影响分析[J],13(2),372-377
[56]黄立葵,贾璐,万剑平,等.沥青路面温度状况的统计分析.中南公路工程,2005, 30(3)：8-9.
[57]娄伟平,吴利红,赵慧娟,等.积雪温度和深度变化特征分析.科技导报,2006,24(9)：32-35.
[58]卢俊辉,基于路面温度和空气温度的路面冰层识别[J],仪表技术与传感器,2010：11,74-76
[59]董长虹.Matlab神经网络与应用[M].北京：国防工业出版社,2005
[60]周开利,康耀红.神经网络模型及其MATLAB仿真程序设计[M].北京：清华大学出版社,2005
[61]王国栋,张建宇等.小波包神经网络在轴承故障模式识别中的应用[J].轴承,2007,(1)：31-34
[62]WuMingzan, Qidie, GuQun, ShaoHongwen. Wavelet Package-Neural network based on Rough Setdiesel Engine Vibration Signal Identification Model [C]. IEEE Int.Cnnf.Neural Networks 8 SignalProcessing, Nanjing. China,14-17 December,2003:185-190
[63]李国勇.智能控制及其MATLAB的实现[M].北京：电子工业出版社,2005
[64]鲁植雄.汽车防抱死系统故障诊断图解[M].南京：江苏科学技术出版社,2004
[65]K J.Emami,M.-R.Akbarzadeh-T.Adaptive Discrete-Time Fuzzy Sliding Mode Control for Anti LockBraking Systems[C].IEEE 2003:335-340
[66]Chih-Min Lin,chun-Fei Hsu.Self-Learning Fuzzy Sliding-Model Control for Antilock BrakingSystems[C].IEEE Transactions on Control Systems Technology,vol 11,No.2,2003:273-278
[67]毛艳娥等,汽车ABS滑模变结构控制方法的研究[J].系统仿真学报,2008,20(5)：1243-1245
[68]王纪森,杨旭东.汽车防抱制动系统的自寻最优控制[J].汽车工程,2004,26(3)：299-301
[69]P.Khatun, C.M.Bingham, Schofield, P.H.Mellor. Application of Fuzzy Control Algorithms forElectricVehicle Antilock Braking/Traction Control Systems. IEEE ransactions on VehicularTechnology,vol.52,No.5,september 2003:1356-1364
[70]Guofu Liu,Qi Zhang, Yueke Wang,Tingting Zhou. An Investigation of Digital Filter Technology on ABSWheel Speed Signal[C].IEEE Proceedings of 2004 International Conference on InformationAcquisition:151-154
[71]Zhang Jian,Ding Neng-gen,Yu Gui-zhen.Research on ABS Wheel Speed Processing Approaches Basedon 80C196 Singlechip[C].IEEE 2006:372-375陈炯,.基于滑移率和减速度的ABS模糊控制仿真研究[J].汽车工程,2006,28(2)：148-151
[72]胡小弟,孙立军.轻型货车轮胎接地压力分布实测.公路交通科技.2005,22(8)：1-7
[73]余卓平,左建令等.路面附着系数估算技术发展现状综述[J].汽车工程,2006,28(6)：546-549
[74]韩建保,张鲁滨等.轮胎路面附着系数实时感应识别系统[J].汽车与动力技术,2005,(2)：62-64
[75]Jin-Oh Hahn,Rajesh Rajamani.GPS-Based Real-Time Identification of Tire-Road Friction87Coefficient[C].IEEE Transactions on Control Systems Technology,vol.10,No.3,May 2002:331-343
[76]Li Li, Fei-Yue Wang, Qunzhi Zhou.Integrated Longitudinal and Lateral Tire/Road Friction Modelingand Monitoring for Vehicle Motion Control[C].IEEE Transactions on Intelligent TransportionSystems,Vol.7,No.1,March 2006:1-19
[77]Mattia Castelnovi,Ronald Arhin,Thomas R. Collins. Reactive Speed Control System Based on TerrainRoughness Detection[C].Robotics and Automation,ICRAApril,2005,891-896
[78]李智等.激光纹理仪在广惠高速公路沥青路面施工中的应用[J].湖南交通科,2006,32(3)：94-96
[79]赵祥模等.基于PSD的路面粗糙度快速检测方法研究[J].光电子技术与信息,2004,172)：58-60
[80]Bodo Heimann,Noamen Bouzid.Road-Wheel Interaction in Vehicles A Mechatronic View ofFriction[C]. IEEE 3rd International Conference on Mechatronics,ICM 2006:137-146
[81]徐延海.基于轮速的路面状态识别方法[J].农业机械学报,2007,38(3)：19-22
[82]李熙亚,吴诰,廖俊,周全.汽车ABS制动过程的道路识别[J].华南理工大学学报 (自然科学版),2006,34(4)：24-27
[83]高健,殷承良等.基于路面自动识别的ABS自适应神经网络模糊控制器方针研究[J].汽车技术,2006,(6)：4-7
[84]Roy McCann,Son Nguyen,System Identification for a Model-Based Observer of a Road RoughnessProfiler [J].2007 IEEE Region 5 Technical Conference,April 20-21,Fayetteville,AR:336-343
[85]Mattia Castelnovi,Ronald Arhin,Thomas R. Collins. Reactive Speed Control System Based on TerrainRoughness Detection[C].Robotics and Automation,ICRAApril,2005:891-896
[86]赵桂娟等.水泥混凝土路面抗滑性能研究[J].山东交通学院学报,2006,14(2)：33-37
[87]吴培关等.高等级道路水泥混凝土路面抗滑构造深度验算方法[J].湖南交通科技,2006,32(3)：4-5
[88]严世榕.影响汽车振动特性的几个参数研究[J].机械强度,2006,28(增刊)：22-25
[89]李忠国,张为公等.基于动载的路面不平度识别的小波特征提取[J].江苏大学学报(自然科学版),2007,28(4)：305-308
[90]董长虹主编.Matlab信号处理与应用[M].北京：国防工业出版社,2005
[91]彭余华,沙爱民沥青路面不均匀的影响因素分析[J].公路交通科技.2006,23(6)：9-13
[92]李士勇.工程模糊数学及应用[M].哈尔滨：哈尔滨工业大学出版社,2004
[93]刘法贵,赵娟.模糊贴近度及应用[J].华北水利水电学院学报,2006,27(3)：104-106
[94]吕燕,唐斌.基于模糊分类的调制信号自动识别方法[J].电子对抗技术,2005,20(4)：19-22
[95]董长虹.Matlab神经网络与应用[M].北京：国防工业出版社,2005
[96]周开利,康耀红.神经网络模型及其MATLAB仿真程序设计[M].北京：清华大学出版社,2005
[97]石辛民,郝整清模糊控制及其MATLABA仿真,[M].北京：清华大学出版社,2008
[2]马骏.高速公路行车安全距离的分析与研究[J].西安公路交通大学学报,1998,18(4)：90-94.
[3]郑安文.高速公路行车间距分析与防追尾装置开发[J].武汉理工大学学报,2002,24(9)：62-65.
[4]肖梅.高速公路追尾碰撞预防报警系统再研究[D].西安：长安大学硕士论文,2003.
[5]刘刚,侯德藻等.汽车主动避撞系统安全报警算法[J]清华大学学报(自然科学版),2004,44(5)：697-700.
[6]侯德藻,刘刚.新型汽车主动避撞安全距离模型[J].汽车工程,2005,27(12)186-191.
[7]卢俊辉,巫世晶,基于车轮振动的路面实时研究[J],振动与冲击,2008,27(4),19-23
[8]John Laurent,Mario Talbot,Michel Doucet,Road surface inspection using laser scanners adapted for thehigh precision 3D measurements of large flat surfaces[C]. 3-D Digital Imaging and Modeling,International Conference on RecentAdvances, May 12-15,1997:303-310
[9]徐豪,汽车主动防撞预警系统避规控制研究,《吉林大学硕士论文》,2012
[10]边明远.汽车主动安全性控制系统路况识别技术纵览[J].汽车研究与开发,2002,(01)：31-33
[11]卢俊辉,巫世晶等,基于车轮振动的路面类型识别方法,江汉大学
[12]赵祥模等.基于PSD的路面粗糙度快速检测方法研究[J].光电子技术与信息,2004,17(2)：58-60
[13]余卓平,左建令,张立军.路面附着系数估算技术发展现状综述[J].汽车工程,2006,(06)：546-549.
[14]江文锋.行驶过程中轮胎与路面间附着性能的评价[D].长安大学,2008
[15]冯广刚.基于主被动集成的汽车安全控制系统建模与仿真[D].湖南大学,2008
[16]卢俊辉,基于路面温度和太阳辐射强度的路面状态识别方法,农业机械学报,2010,41(5),21-23
[17]FredriCkGustafsson.MonitoringTire—Road Frietion Using the Wheel slip.IEEEControlSystems,1998,(8):42-49.
[18]李智,张肖宁,雷尊贵,刘砥石,激光纹理仪在广惠高速公路沥青路面施工中的应用,[J],湖南交通科技,2006,(9)
[19]庄继德,汽车轮胎学[M]..北京：北京理工大学出版社,1996
[20]张克健,汽车地面力学[M]..北京：国防工业出版社,2002
[21]胡小弟,孙立军.轻型货车轮胎接地压力分布实测.公路交通科技.2005,22(8)：1-7
[22]Pieter L.Swart,Beatrys M.Lacquet.An Acoustic Sensor System for Determination of MacroscopicSurface Roughness[C].IEEE Transactions on Instrumentation and Measurement,vol.45,No.5,October1996
[23]A.Pohl,F.Seifert.Wirelessly Interrogable SAW-Sensors for Vehicular Aplications[C].IEEEInstrumentation and Measurement Technology Conference Brussels,Belgium,June 4-6,1996:1465-1468
[24]Alfred Pohl,Reinhard Steindl,Leonhard Reindl.The "Intelligent Tire"Utilizing Passive SAW Sensors Measurement of Tire Friction[C]. IEEE Transactions on Instrumentation Measurement, vol.48, No.6,December 1999:1041-1046
[25]韩建保,张鲁滨等.轮胎路面附着系数实时感应识别系统[J].汽车与动力技术,2005,(2)：62-64
[26]Alfred Pohl, Reinhard Steindl, Leonhard Reindl. IEEE The "Intelligent Tire"Utilizing Passive SAWSensors Measurement of Tire Friction[C]. IEEE Transactions on Instrumentation and Mesurement,vol.48, No.6, December 1999:1041-1046
[27]Jin-Oh Hahn,Rajesh Rajamani.GPS-Based Real-Time Identification of Tire-Road Friction Coefficient[C].IEEE Transactions on Control Systems Technology,vol.l0,No.3,May 2002:331-343
[28]Carloscanud Canuda-dei-Wit, Roberto Horowitz, Observers for Tire/road Contact Friction using onlywheel angular velocity information[C]. Proceedings of the 38th Conference on Decision & ControlPhoenix,Arizona USA Decembe1999:3932-3937
[29]Li Li, Fei-Yue Wang, Qunzhi Zhou.Integrated Longitudinal and Lateral Tire/Road Friction Modelingand Monitoring for Vehicle Motion Control[C].IEEE Transactions on Intelligent TransportionSystems,Vol.7,No.1,March 2006:1-19
[30]Yonggon Lee,Stanislaw H. Zak2.Genetic Neural Fuzzy Control of Anti-Lock Brake Systems[J].Proceedings of the American Control Conference,Arlington,VA June 25-27,2001:671-676
[31]P.Khatun, C.M.Bingham, Schofield, P.H.Mellor. Application of Fuzzy Control Algorithms forElectricVehicle Antilock Braking/Traction Control Systems. IEEE ransactions on VehicularTechnology,vol.52,No.5,september 2003:1356-1364
[32]宋健,陈在峰.制动器耗散功率最大为目标的ABS控制方法[J].清华大学学报(自然科学版),1997,37(12)：95-98
[33]宋健,李永.汽车防抱死制动系统控制方法的研究进展[J].公路交通科技,2002,19(6)：140-145
[34]吴锆,赵克刚等.附着系数-滑移率曲线的测定[J].华南理工大学学报(自然科学版),2001,29(9)：20-22
[35]李朝晖主编.公路工程基础[M].北京：人民交通出版社,2001
[36]邓学钧.路基路面工程[M].北京：人民交通出版社,2000
[37]Katsuhiro Asano, Shigenobu Okada, Norio Iwama. Vibration Suppression of Induction Motor DrivenHybrid Vehicle Using Wheel Torque Observer[C]. IEEE Transactions on IndustryAppaications,vol.28,No.2, March/april 1992:441-447
[38]左曙光,靳晓雄.轿车发动机振动传递系统建模与分析[C].2002年全国振动(诊断、模态、噪声与结构动力学)工程及应用学术会议论文集,北京,2002：502-506
[39]严世榕.影响汽车振动特性的几个参数研究[J].机械强度,2006,28(增刊)：22-25
[40]陈南主编,汽车振动与噪声控制[M].北京：人民交通出版社,2005
[41]Song Jian, Jin Ruichen. Generation of Virtual Road Surfaces and Simulation of Nonlinear Vibration ofVehicles[C].Vehicle Electronics Conference,1999. (IVEC '99) Proceedings of the IEEEInternational:355-359
[42]李忠国,张为公等.基于动载的路面不平度识别的小波特征提取[J].江苏大学学报(自然科学版),2007,28(4)：305-308
[43]Yue Jianhai,Qiu Zhengding. Application of Wavelet Transform to Defect Detection of Wheel flats ofRailway wheels[C].IEEE ICSP'02 Proceedings:29-32
[44]靳晓雄,张立军,江浩.汽车振动分析[M].上海：同济大学出版社,2002：5.
[45]杨建国等.小波分解与重建中产生频率混淆的原因与消除算法[J].振动与冲击,1994,31(2)：
[46]李艳彩.基于四轮模型的汽车ABS控制策略的研究[J].河北工业大学,2007.
[47]陈明,汽车主动防撞预警系统的路面识别研究,《吉林大学硕士论文》-2011-05-01
[48]许颖,基于模糊理论的车辆防碰撞预警系统研究,《湖南农业大学硕士论文》-2010-05-20
[49]董红召,陈炜烽,陈宁,郭明飞,车路集成环境下车辆防撞预警安全状态判别模型的研究[J],《汽车工程》,2011,33(9)：777-780
[50]连晋毅,华小洋.汽车防追尾碰撞数学模型研究[J].中国公路学报,2005,18(3)：123-126.
[51]李晓霞,李百川等.车辆追尾碰撞避免技术[J].西安公路交通大学学报,2001,21(2)：94-97
[52]马娟丽.汽车防撞系统的研究[D].西安：西北工业大学,2007.
[53]Zhiguo Zhao,Zhuoping Yu,Zechang Sun.Research On Fuzzy Road Surface Identification and LogicControl for Anti-lock Braking System[C].IEEE 2003:510-513
[54]杜雪松,解晓光,张小瑞,胡光胜,不同冰雪路面状态的抗滑特性研究[J],2012：127(10)：1-3
[55]吕江毅,宋建桐,刘敏杰,汽车制动时湿滑路面对运行状态的影响分析[J],13(2),372-377
[56]黄立葵,贾璐,万剑平,等.沥青路面温度状况的统计分析.中南公路工程,2005, 30(3)：8-9.
[57]娄伟平,吴利红,赵慧娟,等.积雪温度和深度变化特征分析.科技导报,2006,24(9)：32-35.
[58]卢俊辉,基于路面温度和空气温度的路面冰层识别[J],仪表技术与传感器,2010：11,74-76
[59]董长虹.Matlab神经网络与应用[M].北京：国防工业出版社,2005
[60]周开利,康耀红.神经网络模型及其MATLAB仿真程序设计[M].北京：清华大学出版社,2005
[61]王国栋,张建宇等.小波包神经网络在轴承故障模式识别中的应用[J].轴承,2007,(1)：31-34
[62]WuMingzan, Qidie, GuQun, ShaoHongwen. Wavelet Package-Neural network based on Rough Setdiesel Engine Vibration Signal Identification Model [C]. IEEE Int.Cnnf.Neural Networks 8 SignalProcessing, Nanjing. China,14-17 December,2003:185-190
[63]李国勇.智能控制及其MATLAB的实现[M].北京：电子工业出版社,2005
[64]鲁植雄.汽车防抱死系统故障诊断图解[M].南京：江苏科学技术出版社,2004
[65]K J.Emami,M.-R.Akbarzadeh-T.Adaptive Discrete-Time Fuzzy Sliding Mode Control for Anti LockBraking Systems[C].IEEE 2003:335-340
[66]Chih-Min Lin,chun-Fei Hsu.Self-Learning Fuzzy Sliding-Model Control for Antilock BrakingSystems[C].IEEE Transactions on Control Systems Technology,vol 11,No.2,2003:273-278
[67]毛艳娥等,汽车ABS滑模变结构控制方法的研究[J].系统仿真学报,2008,20(5)：1243-1245
[68]王纪森,杨旭东.汽车防抱制动系统的自寻最优控制[J].汽车工程,2004,26(3)：299-301
[69]P.Khatun, C.M.Bingham, Schofield, P.H.Mellor. Application of Fuzzy Control Algorithms forElectricVehicle Antilock Braking/Traction Control Systems. IEEE ransactions on VehicularTechnology,vol.52,No.5,september 2003:1356-1364
[70]Guofu Liu,Qi Zhang, Yueke Wang,Tingting Zhou. An Investigation of Digital Filter Technology on ABSWheel Speed Signal[C].IEEE Proceedings of 2004 International Conference on InformationAcquisition:151-154
[71]Zhang Jian,Ding Neng-gen,Yu Gui-zhen.Research on ABS Wheel Speed Processing Approaches Basedon 80C196 Singlechip[C].IEEE 2006:372-375陈炯,.基于滑移率和减速度的ABS模糊控制仿真研究[J].汽车工程,2006,28(2)：148-151
[72]胡小弟,孙立军.轻型货车轮胎接地压力分布实测.公路交通科技.2005,22(8)：1-7
[73]余卓平,左建令等.路面附着系数估算技术发展现状综述[J].汽车工程,2006,28(6)：546-549
[74]韩建保,张鲁滨等.轮胎路面附着系数实时感应识别系统[J].汽车与动力技术,2005,(2)：62-64
[75]Jin-Oh Hahn,Rajesh Rajamani.GPS-Based Real-Time Identification of Tire-Road Friction87Coefficient[C].IEEE Transactions on Control Systems Technology,vol.10,No.3,May 2002:331-343
[76]Li Li, Fei-Yue Wang, Qunzhi Zhou.Integrated Longitudinal and Lateral Tire/Road Friction Modelingand Monitoring for Vehicle Motion Control[C].IEEE Transactions on Intelligent TransportionSystems,Vol.7,No.1,March 2006:1-19
[77]Mattia Castelnovi,Ronald Arhin,Thomas R. Collins. Reactive Speed Control System Based on TerrainRoughness Detection[C].Robotics and Automation,ICRAApril,2005,891-896
[78]李智等.激光纹理仪在广惠高速公路沥青路面施工中的应用[J].湖南交通科,2006,32(3)：94-96
[79]赵祥模等.基于PSD的路面粗糙度快速检测方法研究[J].光电子技术与信息,2004,172)：58-60
[80]Bodo Heimann,Noamen Bouzid.Road-Wheel Interaction in Vehicles A Mechatronic View ofFriction[C]. IEEE 3rd International Conference on Mechatronics,ICM 2006:137-146
[81]徐延海.基于轮速的路面状态识别方法[J].农业机械学报,2007,38(3)：19-22
[82]李熙亚,吴诰,廖俊,周全.汽车ABS制动过程的道路识别[J].华南理工大学学报 (自然科学版),2006,34(4)：24-27
[83]高健,殷承良等.基于路面自动识别的ABS自适应神经网络模糊控制器方针研究[J].汽车技术,2006,(6)：4-7
[84]Roy McCann,Son Nguyen,System Identification for a Model-Based Observer of a Road RoughnessProfiler [J].2007 IEEE Region 5 Technical Conference,April 20-21,Fayetteville,AR:336-343
[85]Mattia Castelnovi,Ronald Arhin,Thomas R. Collins. Reactive Speed Control System Based on TerrainRoughness Detection[C].Robotics and Automation,ICRAApril,2005:891-896
[86]赵桂娟等.水泥混凝土路面抗滑性能研究[J].山东交通学院学报,2006,14(2)：33-37
[87]吴培关等.高等级道路水泥混凝土路面抗滑构造深度验算方法[J].湖南交通科技,2006,32(3)：4-5
[88]严世榕.影响汽车振动特性的几个参数研究[J].机械强度,2006,28(增刊)：22-25
[89]李忠国,张为公等.基于动载的路面不平度识别的小波特征提取[J].江苏大学学报(自然科学版),2007,28(4)：305-308
[90]董长虹主编.Matlab信号处理与应用[M].北京：国防工业出版社,2005
[91]彭余华,沙爱民沥青路面不均匀的影响因素分析[J].公路交通科技.2006,23(6)：9-13
[92]李士勇.工程模糊数学及应用[M].哈尔滨：哈尔滨工业大学出版社,2004
[93]刘法贵,赵娟.模糊贴近度及应用[J].华北水利水电学院学报,2006,27(3)：104-106
[94]吕燕,唐斌.基于模糊分类的调制信号自动识别方法[J].电子对抗技术,2005,20(4)：19-22
[95]董长虹.Matlab神经网络与应用[M].北京：国防工业出版社,2005
[96]周开利,康耀红.神经网络模型及其MATLAB仿真程序设计[M].北京：清华大学出版社,2005
[97]石辛民,郝整清模糊控制及其MATLABA仿真,[M].北京：清华大学出版社,2008