一种基于感应线圈的车型识别系统
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摘要
模式识别是人工智能中一个重要的领域，它是通过计算机用数学分析的方法来研究模式的自动处理和判读，使得人类有可能研究复杂的信息处理过程。随着计算机技术的发展，模式识别技术被广泛地应用到人工智能、计算机工程、机器人学、神经生物学等重要领域，其基本理论和方法也正日益丰富。本论文以模式识别的基本理论为依据，对车型自动识别系统做了较为深入的研究和探讨。
车型自动识别是当前智能交通运输系统热点研究方向之一，是高速公路实现不停车收费系统的核心技术，具有广阔的应用前景。本文根据优创集团泛安科技开发(石家庄)有限公司关于保定至天津高速公路机电设备更新项目的要求，设计了一种基于感应线圈的车型识别系统，该系统主要由数据采样、采样波形特征提取及车型模式匹配三大部分组成。
本文详细介绍了数据采样部分的组成、工作原理及硬件结构，并列举了几种常见车型的实际采样波形。通过分析采样数据和比较各车型波形后，采用实际采样波形的幅值作为车型分类判据标准，整条波形的采样值作为模式匹配的特征参数。
因为车辆每次经过感应线圈时的速度不同，所以采样波形存在伸缩变化。在进行车型模式匹配时，为了能使采样波形中的相似特征对齐，本文提出了对称式DTW算法和非对称式DTW算法配合使用的方案。并通过实例仿真，验证了该方案的可行性，并获得了很高的车型识别率。
Pattern recognition is one of the most important regions of Artificial Intelligence (A.I). It is in order to research complicated process of dealing with information. With the development of computer technology, pattern recognitionisusedtoA.I, computer engineering, robot, nerve-biology e tc widely, which basic theory and method are more richer. The paper is based on the basic theory of pattern recognition, and doing deeply research and discussion about the automatic recognition of automobile type.
At present, the automatic recognition of automobile type is one of Intelligent Transportation System (ITS) hot topics, which is the core of the charge system that does not need stop vehicle, and has practice meaning in future. The thesis content came from VATA Ltd. request, which is a vehicle classification system based on inductive loop detectors, made up with data collection sample wave character extracting and automobile type pattern matching.
This paper introduces principle of data collection and hardware frame, and examples some common automobile type of data ware at the same time. After analyzing data and comparing automobile type of data ware, the max-data as criterion of vehicle classification, whole sample's data as character parameter of pattern matching.
Because of different velocity through inductive loop detector, sample ware has flexibility. When doing automobile type pattern matching, in order to keep similar character consistent, the paper put forward the project that symmetry DTW and non- symmetry DTW use together. By using MATLAB software, I validate feasibility of this arithmetic, and obtain anticipate effect.
车型自动识别是当前智能交通运输系统热点研究方向之一，是高速公路实现不停车收费系统的核心技术，具有广阔的应用前景。本文根据优创集团泛安科技开发(石家庄)有限公司关于保定至天津高速公路机电设备更新项目的要求，设计了一种基于感应线圈的车型识别系统，该系统主要由数据采样、采样波形特征提取及车型模式匹配三大部分组成。
本文详细介绍了数据采样部分的组成、工作原理及硬件结构，并列举了几种常见车型的实际采样波形。通过分析采样数据和比较各车型波形后，采用实际采样波形的幅值作为车型分类判据标准，整条波形的采样值作为模式匹配的特征参数。
因为车辆每次经过感应线圈时的速度不同，所以采样波形存在伸缩变化。在进行车型模式匹配时，为了能使采样波形中的相似特征对齐，本文提出了对称式DTW算法和非对称式DTW算法配合使用的方案。并通过实例仿真，验证了该方案的可行性，并获得了很高的车型识别率。
Pattern recognition is one of the most important regions of Artificial Intelligence (A.I). It is in order to research complicated process of dealing with information. With the development of computer technology, pattern recognitionisusedtoA.I, computer engineering, robot, nerve-biology e tc widely, which basic theory and method are more richer. The paper is based on the basic theory of pattern recognition, and doing deeply research and discussion about the automatic recognition of automobile type.
At present, the automatic recognition of automobile type is one of Intelligent Transportation System (ITS) hot topics, which is the core of the charge system that does not need stop vehicle, and has practice meaning in future. The thesis content came from VATA Ltd. request, which is a vehicle classification system based on inductive loop detectors, made up with data collection sample wave character extracting and automobile type pattern matching.
This paper introduces principle of data collection and hardware frame, and examples some common automobile type of data ware at the same time. After analyzing data and comparing automobile type of data ware, the max-data as criterion of vehicle classification, whole sample's data as character parameter of pattern matching.
Because of different velocity through inductive loop detector, sample ware has flexibility. When doing automobile type pattern matching, in order to keep similar character consistent, the paper put forward the project that symmetry DTW and non- symmetry DTW use together. By using MATLAB software, I validate feasibility of this arithmetic, and obtain anticipate effect.
引文
[1] 杨冰．智能运输系统．中国铁路出版社，2000．9：pp．23
[2] Boch. E, Gee. P, A new passive traffic detector. Vehicular Technology Conference, 1997 IEEE 47th, Volume: 1, 4-7 May 1997 pp.112-115 vol.1
[3] Westerman.M, Aspects of mobile communication in dynamic road traffic management, Personal, Indoor and Mobile Radio Communications. 1994. Wireless Networks-Catching the Mobile Future. 5th IEEE International Symposium on, Volume:4, 18-23 Sep 1994, pp.1232-1236 vol. 4
[4] Holmes, R.F. Wynn, S.C.W. Recent developments in electronic systems for road tunnels and bridges, Road Traffic Control, 1990. Third International Conference on, 1-3 May 1990, pp.178-181
[5] 黄卫，陈里得．智能运输系统(ITS)概论．人民交通出版社，1999．9：pp．42-108
[6] 范锟．高速公路路政管理．人民交通出版社，1998．10：pp．21
[7] 刘伟铭，王哲人，郑白涛．高速公路收费系统理论与方法[M]．人民交通出版社．2000．5：pp．36-37
[8] 杨兆升，杨志宏，赵丹华．高速公路收费系统的车型自动分类吉林大学学报．2002．7：pp．16-19
[9] 宋燕铭．高速公路不停车收费系统的发展前景与解决方案．湖南交通科技．2000．12：pp．27-29
[10] 黄中祥，贺国光．不停车自动收费系统研究动态与发展趋势国外公路．1996．12：pp．28-20
[11] 吕任东．关于我国高速公路收费系统的若干探讨．交通与计算机．1995．10：pp．22-25
[12] 李金宗．模式识别导论．高等教育出版社．1991．5：pp．38-56
[13] 王碧泉，陈祖荫．模式识别理论、方法和应用．地震出版社．1989．11：pp．147-151
[14] 沈清，汤霖．模式识别导论．国防工业出版社．1991．11：pp．2-19
[15] 孙即祥．模式识别中的特征提取与计算机视觉不变量．国防工业出版社，2001．9：pp．132-145
[16] 傅亨孙．人工智能及其应用．清华大学出版社．1987．9
[17] 黄德双．神经网络模式识别系统理论．电子工业出版社．1996．5
[18] 数字信号处理技术的新发展．中国电子学会第七届年会论文 P555．
[19] Kan. W.Y., Krogmeier. J.V., Doerschuk. P.C., Detection Technology for IVHS-Task L Final Report, Federal Highway Administration Contract DTFH61-91 -C-00076,U.S.Department of Transportation, Wash., D.C., 1995,pp.278-286
[20] 姜紫峰，谭光莉．车辆检测器的进展．公路交通科技．1996．3：pp．31-32
[21] 阙大顺．车辆检测器及其发展研究．交通与计算机．1999．4：pp．24-27
[22] Klein, L.A, Traffic parameter measurement technology evaluation, Vehicle Navigation and Information Systems Conference, 1993. Proceedings of the IEEE-lEE, 12-15 Oct 1993, pp. 529-533
[23] L.A. Klein, M.R. Kelley, and M.K. Mills, Evaluation of Overhead and In-Ground Vehicle Detector Technologies for Traffic Flow Measurement, Journal of Testing and Evaluation,JTEVA, Vol. 25, No. 2, March 1997, pp. 215-224
[24] 王福瑞．单片机微机测控系统设计大全．北京航空航天大学出版社 1999．3
[25] 童诗白．模拟电子技术基础．高等教育出版社．2000．5
[26] 何立民．MCS-51系列单片机应用系统设计．北京航空航天大学出版社．1990
[27] 尤一鸣．单片机总线扩展技术．北京航空航天大学出版社．1993
[28] 胡广书．数字信号处理理论、算法与实现．清华大学出版社．2001．3：pp．68-70
[29] SRAM628128技术手册HITACHI公司
[30] FLASH EPROM技术手册Intel公司
[31] DS80C320/DS80C323.Dallas Semiconductor. 1997
[32] Dallas Semiconductor Corp: Dallas High Speed Microcomputer User's Guide
[33] Edwards, V. ,Evers, C.,Chartier, E., Inductive loop sensor subsystem (LSS) as a supplemental surface surveillance system-demonstration results, Digital Avionics Systems Conferences, 2000. Proceedings. DASC. The 19th, Volume: 2,2000,pp. 7D6/1 -7D6/8 vol.2
[34] Gajda, J. ,Sroka. R., Stencel, M., Wajda, A.; Zeglen, T.;A vehicle classification based on inductive loop detectors,Instrumentation and Measurement Technology Conference,2001 IMTC 2001. Proceedings of the 18th IEEE, Volume: 1,21-23 May 2001,pp.460-464 vol.1
[35] Holmes, R.F. Wynn, S.C.W. Recent developments in electronic systems for road tunnels and bridges, Road Traffic Control,1990. Third International Conference on, 1-3 May 1990, pp. 178-181
[36] Pursula, M.; Kosonen, I.; Microprocessor and PC-based vehicle classification equipments using induction loops. Road Traffic Monitoring, 1989. Second International Conference on,7-9 Feb 1989. Page(s): 24-28
[37] Mills, M.K., Inductive loop system equivalent circuit model. Vehicular Technology Conference, 1989 IEEE 39th, 1-3 May 1989. Page(s): 689-700 vol.2
[38] Viarani, E, Extraction of traffic information from images at DEIS. Image Analysis and Processing, 1999. Proceedings.International Conference on, 1999. Page(s): 1073-1076
[39] 孙德敏．工程最优化方法及应用．中国科学技术大学出版社．1991．1：pp．251-259
[40] 刘兴良，最优控制及应用．科学出版社．1990．1：p79-91
[41] 蔡宣三．最优化与最优控制．清华大学出版社．1982．12：pp．104-128
[42] 毛云英．动态系统与最优控制．高等教育出版社．1994．1：pp．98-112
[43] 王康宁．最优控制的数学理论．国防工业出版社．1995．10：pp．46-69
[44] 樊海泉 董德存．基于模式匹配算法的车型识别研究．微型电脑应用．2002．4：pp．29-31
[45] 万春．基于DTW的语音识别应用系统研究与实现．集美大学学报(自然科学版)．2002．6：pp．33-35
[46] 高翔等．多元轨迹同步化问题的改进DTW算法．新鲜与控制．2001．4：pp．26-31
[47] MyersC, etal. Performance Tradeoffs in Dynamic Time Warping Algorithms for Isolated Word Recognition. IEEE Trans.on Acoustics speech and Singal Procession, ASSP 1984, 32(2): 263
[48] Athanassios Kassidas, Synchronization of Batch Trajectorise Using Dynamic Time Warping. AICHE J. 1998.44.864
[49] 杨行峻 迟惠生．语音信号数字处理[M]．电子工业出版社．1995．
[50] Sakoc.H,S.Chiba Dynamic Programming Algorithm OptiMization for Spoken Word Recognition,IEEE Trans.on Acoustics, Speech and Singal Process.ASSP1987,26(1),43
[51] 杨克昌．动态规划最优化路径搜索设计．岳阳师范学院学报．2000．3：pp．20-23
[52] 黄文梅．系统分析与仿真：MATLAB语言及应用．国防科技大学出版社．1999
[53] 杨胜天 李轶．MATLAB仿真应用详解，人民邮电出版社．2001．3
[54] 张建任．基于MATLAB的模糊控制系统仿真．自动化与仪表仪器．2002．1：pp．27-30
[55] 苏金明阮沈勇．MATLAB6．1实用指南(上册)．电子工业出版社．2002．1
[2] Boch. E, Gee. P, A new passive traffic detector. Vehicular Technology Conference, 1997 IEEE 47th, Volume: 1, 4-7 May 1997 pp.112-115 vol.1
[3] Westerman.M, Aspects of mobile communication in dynamic road traffic management, Personal, Indoor and Mobile Radio Communications. 1994. Wireless Networks-Catching the Mobile Future. 5th IEEE International Symposium on, Volume:4, 18-23 Sep 1994, pp.1232-1236 vol. 4
[4] Holmes, R.F. Wynn, S.C.W. Recent developments in electronic systems for road tunnels and bridges, Road Traffic Control, 1990. Third International Conference on, 1-3 May 1990, pp.178-181
[5] 黄卫，陈里得．智能运输系统(ITS)概论．人民交通出版社，1999．9：pp．42-108
[6] 范锟．高速公路路政管理．人民交通出版社，1998．10：pp．21
[7] 刘伟铭，王哲人，郑白涛．高速公路收费系统理论与方法[M]．人民交通出版社．2000．5：pp．36-37
[8] 杨兆升，杨志宏，赵丹华．高速公路收费系统的车型自动分类吉林大学学报．2002．7：pp．16-19
[9] 宋燕铭．高速公路不停车收费系统的发展前景与解决方案．湖南交通科技．2000．12：pp．27-29
[10] 黄中祥，贺国光．不停车自动收费系统研究动态与发展趋势国外公路．1996．12：pp．28-20
[11] 吕任东．关于我国高速公路收费系统的若干探讨．交通与计算机．1995．10：pp．22-25
[12] 李金宗．模式识别导论．高等教育出版社．1991．5：pp．38-56
[13] 王碧泉，陈祖荫．模式识别理论、方法和应用．地震出版社．1989．11：pp．147-151
[14] 沈清，汤霖．模式识别导论．国防工业出版社．1991．11：pp．2-19
[15] 孙即祥．模式识别中的特征提取与计算机视觉不变量．国防工业出版社，2001．9：pp．132-145
[16] 傅亨孙．人工智能及其应用．清华大学出版社．1987．9
[17] 黄德双．神经网络模式识别系统理论．电子工业出版社．1996．5
[18] 数字信号处理技术的新发展．中国电子学会第七届年会论文 P555．
[19] Kan. W.Y., Krogmeier. J.V., Doerschuk. P.C., Detection Technology for IVHS-Task L Final Report, Federal Highway Administration Contract DTFH61-91 -C-00076,U.S.Department of Transportation, Wash., D.C., 1995,pp.278-286
[20] 姜紫峰，谭光莉．车辆检测器的进展．公路交通科技．1996．3：pp．31-32
[21] 阙大顺．车辆检测器及其发展研究．交通与计算机．1999．4：pp．24-27
[22] Klein, L.A, Traffic parameter measurement technology evaluation, Vehicle Navigation and Information Systems Conference, 1993. Proceedings of the IEEE-lEE, 12-15 Oct 1993, pp. 529-533
[23] L.A. Klein, M.R. Kelley, and M.K. Mills, Evaluation of Overhead and In-Ground Vehicle Detector Technologies for Traffic Flow Measurement, Journal of Testing and Evaluation,JTEVA, Vol. 25, No. 2, March 1997, pp. 215-224
[24] 王福瑞．单片机微机测控系统设计大全．北京航空航天大学出版社 1999．3
[25] 童诗白．模拟电子技术基础．高等教育出版社．2000．5
[26] 何立民．MCS-51系列单片机应用系统设计．北京航空航天大学出版社．1990
[27] 尤一鸣．单片机总线扩展技术．北京航空航天大学出版社．1993
[28] 胡广书．数字信号处理理论、算法与实现．清华大学出版社．2001．3：pp．68-70
[29] SRAM628128技术手册HITACHI公司
[30] FLASH EPROM技术手册Intel公司
[31] DS80C320/DS80C323.Dallas Semiconductor. 1997
[32] Dallas Semiconductor Corp: Dallas High Speed Microcomputer User's Guide
[33] Edwards, V. ,Evers, C.,Chartier, E., Inductive loop sensor subsystem (LSS) as a supplemental surface surveillance system-demonstration results, Digital Avionics Systems Conferences, 2000. Proceedings. DASC. The 19th, Volume: 2,2000,pp. 7D6/1 -7D6/8 vol.2
[34] Gajda, J. ,Sroka. R., Stencel, M., Wajda, A.; Zeglen, T.;A vehicle classification based on inductive loop detectors,Instrumentation and Measurement Technology Conference,2001 IMTC 2001. Proceedings of the 18th IEEE, Volume: 1,21-23 May 2001,pp.460-464 vol.1
[35] Holmes, R.F. Wynn, S.C.W. Recent developments in electronic systems for road tunnels and bridges, Road Traffic Control,1990. Third International Conference on, 1-3 May 1990, pp. 178-181
[36] Pursula, M.; Kosonen, I.; Microprocessor and PC-based vehicle classification equipments using induction loops. Road Traffic Monitoring, 1989. Second International Conference on,7-9 Feb 1989. Page(s): 24-28
[37] Mills, M.K., Inductive loop system equivalent circuit model. Vehicular Technology Conference, 1989 IEEE 39th, 1-3 May 1989. Page(s): 689-700 vol.2
[38] Viarani, E, Extraction of traffic information from images at DEIS. Image Analysis and Processing, 1999. Proceedings.International Conference on, 1999. Page(s): 1073-1076
[39] 孙德敏．工程最优化方法及应用．中国科学技术大学出版社．1991．1：pp．251-259
[40] 刘兴良，最优控制及应用．科学出版社．1990．1：p79-91
[41] 蔡宣三．最优化与最优控制．清华大学出版社．1982．12：pp．104-128
[42] 毛云英．动态系统与最优控制．高等教育出版社．1994．1：pp．98-112
[43] 王康宁．最优控制的数学理论．国防工业出版社．1995．10：pp．46-69
[44] 樊海泉 董德存．基于模式匹配算法的车型识别研究．微型电脑应用．2002．4：pp．29-31
[45] 万春．基于DTW的语音识别应用系统研究与实现．集美大学学报(自然科学版)．2002．6：pp．33-35
[46] 高翔等．多元轨迹同步化问题的改进DTW算法．新鲜与控制．2001．4：pp．26-31
[47] MyersC, etal. Performance Tradeoffs in Dynamic Time Warping Algorithms for Isolated Word Recognition. IEEE Trans.on Acoustics speech and Singal Procession, ASSP 1984, 32(2): 263
[48] Athanassios Kassidas, Synchronization of Batch Trajectorise Using Dynamic Time Warping. AICHE J. 1998.44.864
[49] 杨行峻 迟惠生．语音信号数字处理[M]．电子工业出版社．1995．
[50] Sakoc.H,S.Chiba Dynamic Programming Algorithm OptiMization for Spoken Word Recognition,IEEE Trans.on Acoustics, Speech and Singal Process.ASSP1987,26(1),43
[51] 杨克昌．动态规划最优化路径搜索设计．岳阳师范学院学报．2000．3：pp．20-23
[52] 黄文梅．系统分析与仿真：MATLAB语言及应用．国防科技大学出版社．1999
[53] 杨胜天 李轶．MATLAB仿真应用详解，人民邮电出版社．2001．3
[54] 张建任．基于MATLAB的模糊控制系统仿真．自动化与仪表仪器．2002．1：pp．27-30
[55] 苏金明阮沈勇．MATLAB6．1实用指南(上册)．电子工业出版社．2002．1
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