DSP及视觉检测技术在智能汽车辅助驾驶系统中的应用
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摘要
汽车智能辅助驾驶系统以其自主式车辆事故预警和行驶导航机制，在提高汽车的主动安全性能和减少交通事故方面有着广阔的应用前景。汽车行驶道路的复杂、多变量环境，对智能辅助驾驶装置的实时性、空间尺寸和稳定性要求极为苛刻。采用计算机视觉技术的辅助驾驶系统，由于其探测范围的完整性和宽广性，具有优越的性价比，是辅助驾驶系统的重点发展方向之一。
本文主要工作围绕着智能汽车辅助驾驶系统中视觉检测、导航部分的硬件实现展开。产品化的智能汽车辅助驾驶装置应具有良好的实时性及便携性，传统的基于"图像采集卡－PC－终端控制设备"的硬件实现方案无法满足以上需要。分析比较国内外相关领域的研究状况后，提出了基于DSP的"图像采集－处理"一体化结构实现方案。
论文介绍了数字信号处理及数字信号处理芯片技术，比较了基于通用CPU和DSP芯片的硬件实现方案的性能。在总结各种图像处理算法对运算器、存储器的要求及相应的实现方案后，建立了DSP实时图像处理系统仿真开发装置。采用MCU控制器，控制数字图像采集单元。通过中断机制，实现数据的可靠传输，在DSP EVM板环境下，对算法程序进行优化和比较，完成算法仿真测试，实现软件无缝移植和硬件的结构化设计。
根据算法实时仿真结果，本文给出DSP小系统实现方案。以TMS320C6711为核心，通过其EMIF接口，扩充外部ROM、SDRAM及SBSRAM存储器，采用中断及DMA方式实现外部数据采集及传输。根据系统要求，设计两路电源及复位监控电路，并进行了系统级优化和抗干扰设计。
视频采集单元采用Philips SAA 7111及FPGA芯片，以标准视频信号(PAL或NTSC)为输入，通过FPGA及I2C总线，对图像数据进行剪裁及采集；采用两帧存储体轮换工作机制，省去FIFO器件，降低成本；采用"交叉－连续"地址存储空间，便于DSP进行DMA传输。根据"存储-处理"并行设计思想，提出了一种改进的Sobel算子，利用FPGA芯片内部RAM资源，采用并行流水工作机制，与Sobel算子模板卷积，实现硬件滤波和图像数据的边缘提取，大幅度提高了系统工作效率。
以上实时图像处理系统方案能够满足系统算法要求，配合FPGA液晶显示控制器，能够迅速建立低成本的产品原型，并实现算法软件的固化和产品加密。
Owing to its intrinsic Pre-Accident Warning mechanism, Intelligence Automobile Driver-Assistance System has bright prospects, especially in high quality active automobile safety and accident avoidance measurement. The road driving condition which is Multi-Variables and complex environment requires high real-time quality, stability and limited space. The Driver-Assistance System that employs Computer Vision technology is one of the booming research fields, due to their extensive signal detection range, integrity and excellent "Quality-Cost" ratio.
In this paper, discussion is mainly focused on the Hardware Application Policy of Intelligence Automobile Driver-Assistance System. A qualified product of the Intelligence Driver-Assistance System must display good real-time and easy-carry quality. Traditional equipment based on " Image Acquisition Card-PC-Execution Device" policy cannot meet the requirments above. After systematically analyzed the related research fields, a new solution is proposed, which is based on "DSP Image Acquisition-Processing" integrity policy.
After summarized Digital Signal Processing and Digital Signal Processor technology, the device performances are compared, whose hardware application solutions are independently based on general CPU and DSP chips. According to the needs of different Image Processing Algorithms, a Real-time Image Processing Development Simulation Device is developed. In this equipment, a MCU controller is responsible for Digital Image Acquisition, realized stable data transmission between different running frequency units. The whole algorithm is simulated and optimized on DSP EVM board and CCS environment, which contribute to a seamless software transplant and hardware structure design.
A DSP minimum system solution is proposed according to the Real－Time simulation results. A TMS320C 6711 DSP chip is adopted as the operation unit. External ROM, SDRAM and SBSRAM is constructed through its EMIF interface. The image data are stored and exchanged under an "Interruption & DMA" parallel mechanism, which can run simultaneously with DSP unit. Two different voltage power resources are provided for the whole system, which are watched by one surveillance circuit. System Anti-jamming and system optimization measures are added into system for future circuit debug.
Video Acquisition Unit is constructed on Philips SAA7111 and FPGA chips. Input signal is standard video signal (PAL or NTSC). The brightness and color control can be adjusted through I2C Bus. With alternately storing and intercross address mechanism of two SRAM memory banks, the expensive FIFO memory is avoided and the image data can be stored in a consecutive address range, which can save lots of time in DMA transmission. At the same time, the image data format can be changed. Based on "Store-Processing Integrity" idea, a promoted Sobel operator is proposed. With full use of internal RAM resources and Pipeline mechanism, the image data can be convoluted with Sobel operator, and then the edge of the image data can be extracted entirely by hardware device. This method greatly promoted the efficiency.
The solution can meet the requirements of system algorithm. A fast prototype can be built if a FPGA display controller is added, as well as realize algorithm and products encryption.
本文主要工作围绕着智能汽车辅助驾驶系统中视觉检测、导航部分的硬件实现展开。产品化的智能汽车辅助驾驶装置应具有良好的实时性及便携性，传统的基于"图像采集卡－PC－终端控制设备"的硬件实现方案无法满足以上需要。分析比较国内外相关领域的研究状况后，提出了基于DSP的"图像采集－处理"一体化结构实现方案。
论文介绍了数字信号处理及数字信号处理芯片技术，比较了基于通用CPU和DSP芯片的硬件实现方案的性能。在总结各种图像处理算法对运算器、存储器的要求及相应的实现方案后，建立了DSP实时图像处理系统仿真开发装置。采用MCU控制器，控制数字图像采集单元。通过中断机制，实现数据的可靠传输，在DSP EVM板环境下，对算法程序进行优化和比较，完成算法仿真测试，实现软件无缝移植和硬件的结构化设计。
根据算法实时仿真结果，本文给出DSP小系统实现方案。以TMS320C6711为核心，通过其EMIF接口，扩充外部ROM、SDRAM及SBSRAM存储器，采用中断及DMA方式实现外部数据采集及传输。根据系统要求，设计两路电源及复位监控电路，并进行了系统级优化和抗干扰设计。
视频采集单元采用Philips SAA 7111及FPGA芯片，以标准视频信号(PAL或NTSC)为输入，通过FPGA及I2C总线，对图像数据进行剪裁及采集；采用两帧存储体轮换工作机制，省去FIFO器件，降低成本；采用"交叉－连续"地址存储空间，便于DSP进行DMA传输。根据"存储-处理"并行设计思想，提出了一种改进的Sobel算子，利用FPGA芯片内部RAM资源，采用并行流水工作机制，与Sobel算子模板卷积，实现硬件滤波和图像数据的边缘提取，大幅度提高了系统工作效率。
以上实时图像处理系统方案能够满足系统算法要求，配合FPGA液晶显示控制器，能够迅速建立低成本的产品原型，并实现算法软件的固化和产品加密。
Owing to its intrinsic Pre-Accident Warning mechanism, Intelligence Automobile Driver-Assistance System has bright prospects, especially in high quality active automobile safety and accident avoidance measurement. The road driving condition which is Multi-Variables and complex environment requires high real-time quality, stability and limited space. The Driver-Assistance System that employs Computer Vision technology is one of the booming research fields, due to their extensive signal detection range, integrity and excellent "Quality-Cost" ratio.
In this paper, discussion is mainly focused on the Hardware Application Policy of Intelligence Automobile Driver-Assistance System. A qualified product of the Intelligence Driver-Assistance System must display good real-time and easy-carry quality. Traditional equipment based on " Image Acquisition Card-PC-Execution Device" policy cannot meet the requirments above. After systematically analyzed the related research fields, a new solution is proposed, which is based on "DSP Image Acquisition-Processing" integrity policy.
After summarized Digital Signal Processing and Digital Signal Processor technology, the device performances are compared, whose hardware application solutions are independently based on general CPU and DSP chips. According to the needs of different Image Processing Algorithms, a Real-time Image Processing Development Simulation Device is developed. In this equipment, a MCU controller is responsible for Digital Image Acquisition, realized stable data transmission between different running frequency units. The whole algorithm is simulated and optimized on DSP EVM board and CCS environment, which contribute to a seamless software transplant and hardware structure design.
A DSP minimum system solution is proposed according to the Real－Time simulation results. A TMS320C 6711 DSP chip is adopted as the operation unit. External ROM, SDRAM and SBSRAM is constructed through its EMIF interface. The image data are stored and exchanged under an "Interruption & DMA" parallel mechanism, which can run simultaneously with DSP unit. Two different voltage power resources are provided for the whole system, which are watched by one surveillance circuit. System Anti-jamming and system optimization measures are added into system for future circuit debug.
Video Acquisition Unit is constructed on Philips SAA7111 and FPGA chips. Input signal is standard video signal (PAL or NTSC). The brightness and color control can be adjusted through I2C Bus. With alternately storing and intercross address mechanism of two SRAM memory banks, the expensive FIFO memory is avoided and the image data can be stored in a consecutive address range, which can save lots of time in DMA transmission. At the same time, the image data format can be changed. Based on "Store-Processing Integrity" idea, a promoted Sobel operator is proposed. With full use of internal RAM resources and Pipeline mechanism, the image data can be convoluted with Sobel operator, and then the edge of the image data can be extracted entirely by hardware device. This method greatly promoted the efficiency.
The solution can meet the requirements of system algorithm. A fast prototype can be built if a FPGA display controller is added, as well as realize algorithm and products encryption.
引文
[1] Gao Xiaohong，Cross Century Transportation: Its Goals, Trends and Solutions[J]，Journal of Wuhan Transportation University，Vol.23，No.2，April 1999:1
[2] 2002中国统计年报[R]，1～15 http://www.tjb.gov.cn
[3] 赵恩棠，周允， 智能化汽车运输系统的发展[J]，汽车世界，1997，No.2 pp：24-26
[4] DSP Market Reports 2002[R], Forward Concepts Co.pp:1-4
[5] Steven W. Smith ，The Scientist and Engineer's Guide to Digital Signal Processing Second Edition[M]，California Technical Publishing pp:1-3
[6] 杨更新，汽车自动驾驶系统[J]，汽车世界，1999，No.3
[7] 杨晓光、彭国雄、王一如， 高速公路交通事故预防与紧急救援系统[J]，公路交通科技Vol.15，No.4 1 998年12月 pp:1-2
[8] 王宏，何克忠，张跋，智能车辆的自主驾驶与辅助导航[J]，机器人，1997，Vol.19 No，2
[9] 杨大凯，王剑，蔡柏根，GPS及GIS在智能交通监控系统中的应用[J]，交通科技 No.2 Apr.2002 pp:1-2
[10] Massimo Bertozzi, Alberto Broggi, Alessandra Fascioli, Vision-based Intelligent Vehicles; State of the Art and Perspective[J].Robotics and Autonomous Systems 32,2000 pp: 1-6
[11] Masayoshi Aoki, Image Processing in ITS[J].IEEE International Conference on Intelligent Vehicles,1998 pp:1-4
[12] Shinji Ozawa, Image Processing for Intelligent Transport System[J]. IEICE Transaction Information & System,1999;E82-D(3) pp:629-636
[13] 李增良，模糊控制、神经网络控制、智能控制方法[M] 哈尔滨工业大学出版社 1998;pp4-11
[14] Strategic Plan for Intelligent Vehicle- Highway Systems in the United States[R]. Intelligent Vehicle Highway of America,1992 .
[15] 蓝梦，自动高速公路无人驾驶电脑汽车[J]，汽车世界，1998，No.5 pp：16-20
[16] 尚刚 陈宝，智能交通系统ITS在日本的发展综述[J],华东公路No3(Total No.118) 1999.6 pp :62-65
[17] Steven W. Smith ，Digital Signal Processing[M]， California Technical Publishing pp：1-30
[18] 亚科希资讯有限公司[R] 纵谈DSP的发展应用 2001.6.25
[19] 宋正勋 胡贞 许红梅，DSP器件的原理及应用[J]，长春光学精密机械学院学报，1996.6 Vol 22 No.2 pp：1-9
[20] 王念旭等，DSP基础与应用系统设计[M]，北京航空航天大学出版社，2001.8 pp:3-9
[21] Sophodes J. Orfanidis, Introduction to Signal Processing[M], Prentice Hall 1998.12 pp:7-10
[22] 黄爱苹 数字信号处理 国防工业出版社[M] 1991.5 pp：35-40：
[23] 彭启宗 李玉柏 DSP技术，西安电子科技大学出版社[M]，1997.11 pp:29-31
[24] Steven W. Smith ，Digital Signal Processing[M], California Technical Publishing pp: 144
[25] 任丽香 马淑芬 李方慧 TMS320C6000系列DSP的原理与应用[M] 电子工业出版社2000.7 pp:2-15
[26] 张雄伟 DSP芯片的原理与开发应用[M] 电子工业出版社1997.9 pp：10-13
[27] 戴明桢 数字信号处理的硬件实现[M] 人民邮电出版社 1998.3 pp：4-6
[28] 王锁苹 龚建荣 EDA技术及发展趋势[J] 电子世界 2002.12 pp：4
[29] 丁文霞 EDA技术在现代数字系统中的应用[J] 自动化与仪器仪表，2001.11 pp：29
[30] 黄席樾，柴毅，周欣，汽车安全行驶智能辅助操作系统中的道路检测[J]，重庆大学学报，2000，Vol.23，No.2，pp:26-30
[31] 黄席樾，汪先矩，周欣，基于道路几何模型的单目测距算法[J]，重庆大学学报，2000，Vol.23，No.3，pp:70-73
[32] 周欣，汽车辅助智能驾驶系统中的计算机视觉技术[D]，重庆大学硕士学位论文，2000.6, pp:26-30
[33] MURAT TEKALP, Digital Video Processing[M]，电子工业出版社，1998 pp：10-20
[34] DB200数字接口摄像模块用户手册,湖北大学科技开发总公司,2002.4 pp:2-15
[35] Texas Instruments IncorporatedTMS320C6000 Optimizing C Compiler User's Guide Literature Number: SPRU187E February 1999 pp：20-30
[36] Texas Instruments Incorporated，TMS320C6000Assembly Language Tools User's Guide SPRU187E February 1999 pp:20-30
[37] Texas Instruments Incorporated ，C Source Debugger Users Guide Digital Signal Processing Solutions， 1998 pp:10-20
[38] WT6201/6701板使用说明，北京闻亭科技发展有限责任公司，2001.4 pp：47-60
[39] Texas Instruments, TMS320C6000 Technical Brief, 1999.2 pp:2-24
[40] Texas Instruments ,TMS320C6000 CPU and Instruction Set Reference Guide, 1999.3 pp：294-310
[41] Texas Instruments ,TMS320C6000 System Clock Circuit Example, 1999.3 pp：20-30
[42] Texas Instruments ,TMS320C6000 Reset Circuit, 1999.3 pp：20-25
[43] Texas Instruments ,TMS320C6000 Power Supply, 1999.3 pp：10-15
[44] Texas Instruments ,TMS320C6000 Peripheral Reference Guide, 1999 pp:496-100
[45] 周富强，张广军 视觉检测中高速图像采集技术的研究[J] 北京航空航天大学学报，Vol 28 No 2 2002.4
王劲 用两片I2C总线接口通用器件PCF8574扩展的8×8键盘[J] 电子技术 1997.No.4
[46] pp：37-38
[47] 胡跃全 I2C总线与PC机接口设计[J] 测控技术 1995 Vol 14 No 3 pp：21-22
[48] P87LPC761 Datasheet, Philips Semiconductors, 1989 pp:1-10
[49] SAA7111AH Datasheet, Philips Semiconductors, 1998 May 15 pp:2-30
[50] 吕铁英 彭嘉雄，图像轮廓特征提取的新方法的研究[J]，中国图像图形学报 1999.8 Vol 4 No.8
[51] Woodham, R. J. Analysing Images of Curved Surfaces[J], AI. 17(1981) pp: 117-140
[52] N. Kanopoulos, N. Vasanthavada and R. L. Baker, esign of an Image Edge Detection Filter Using the Sobel Operator[J] IEEE Journal of solid-state circuits, vol. 23, No. 2, pp1-2, April 1988
[2] 2002中国统计年报[R]，1～15 http://www.tjb.gov.cn
[3] 赵恩棠，周允， 智能化汽车运输系统的发展[J]，汽车世界，1997，No.2 pp：24-26
[4] DSP Market Reports 2002[R], Forward Concepts Co.pp:1-4
[5] Steven W. Smith ，The Scientist and Engineer's Guide to Digital Signal Processing Second Edition[M]，California Technical Publishing pp:1-3
[6] 杨更新，汽车自动驾驶系统[J]，汽车世界，1999，No.3
[7] 杨晓光、彭国雄、王一如， 高速公路交通事故预防与紧急救援系统[J]，公路交通科技Vol.15，No.4 1 998年12月 pp:1-2
[8] 王宏，何克忠，张跋，智能车辆的自主驾驶与辅助导航[J]，机器人，1997，Vol.19 No，2
[9] 杨大凯，王剑，蔡柏根，GPS及GIS在智能交通监控系统中的应用[J]，交通科技 No.2 Apr.2002 pp:1-2
[10] Massimo Bertozzi, Alberto Broggi, Alessandra Fascioli, Vision-based Intelligent Vehicles; State of the Art and Perspective[J].Robotics and Autonomous Systems 32,2000 pp: 1-6
[11] Masayoshi Aoki, Image Processing in ITS[J].IEEE International Conference on Intelligent Vehicles,1998 pp:1-4
[12] Shinji Ozawa, Image Processing for Intelligent Transport System[J]. IEICE Transaction Information & System,1999;E82-D(3) pp:629-636
[13] 李增良，模糊控制、神经网络控制、智能控制方法[M] 哈尔滨工业大学出版社 1998;pp4-11
[14] Strategic Plan for Intelligent Vehicle- Highway Systems in the United States[R]. Intelligent Vehicle Highway of America,1992 .
[15] 蓝梦，自动高速公路无人驾驶电脑汽车[J]，汽车世界，1998，No.5 pp：16-20
[16] 尚刚 陈宝，智能交通系统ITS在日本的发展综述[J],华东公路No3(Total No.118) 1999.6 pp :62-65
[17] Steven W. Smith ，Digital Signal Processing[M]， California Technical Publishing pp：1-30
[18] 亚科希资讯有限公司[R] 纵谈DSP的发展应用 2001.6.25
[19] 宋正勋 胡贞 许红梅，DSP器件的原理及应用[J]，长春光学精密机械学院学报，1996.6 Vol 22 No.2 pp：1-9
[20] 王念旭等，DSP基础与应用系统设计[M]，北京航空航天大学出版社，2001.8 pp:3-9
[21] Sophodes J. Orfanidis, Introduction to Signal Processing[M], Prentice Hall 1998.12 pp:7-10
[22] 黄爱苹 数字信号处理 国防工业出版社[M] 1991.5 pp：35-40：
[23] 彭启宗 李玉柏 DSP技术，西安电子科技大学出版社[M]，1997.11 pp:29-31
[24] Steven W. Smith ，Digital Signal Processing[M], California Technical Publishing pp: 144
[25] 任丽香 马淑芬 李方慧 TMS320C6000系列DSP的原理与应用[M] 电子工业出版社2000.7 pp:2-15
[26] 张雄伟 DSP芯片的原理与开发应用[M] 电子工业出版社1997.9 pp：10-13
[27] 戴明桢 数字信号处理的硬件实现[M] 人民邮电出版社 1998.3 pp：4-6
[28] 王锁苹 龚建荣 EDA技术及发展趋势[J] 电子世界 2002.12 pp：4
[29] 丁文霞 EDA技术在现代数字系统中的应用[J] 自动化与仪器仪表，2001.11 pp：29
[30] 黄席樾，柴毅，周欣，汽车安全行驶智能辅助操作系统中的道路检测[J]，重庆大学学报，2000，Vol.23，No.2，pp:26-30
[31] 黄席樾，汪先矩，周欣，基于道路几何模型的单目测距算法[J]，重庆大学学报，2000，Vol.23，No.3，pp:70-73
[32] 周欣，汽车辅助智能驾驶系统中的计算机视觉技术[D]，重庆大学硕士学位论文，2000.6, pp:26-30
[33] MURAT TEKALP, Digital Video Processing[M]，电子工业出版社，1998 pp：10-20
[34] DB200数字接口摄像模块用户手册,湖北大学科技开发总公司,2002.4 pp:2-15
[35] Texas Instruments IncorporatedTMS320C6000 Optimizing C Compiler User's Guide Literature Number: SPRU187E February 1999 pp：20-30
[36] Texas Instruments Incorporated，TMS320C6000Assembly Language Tools User's Guide SPRU187E February 1999 pp:20-30
[37] Texas Instruments Incorporated ，C Source Debugger Users Guide Digital Signal Processing Solutions， 1998 pp:10-20
[38] WT6201/6701板使用说明，北京闻亭科技发展有限责任公司，2001.4 pp：47-60
[39] Texas Instruments, TMS320C6000 Technical Brief, 1999.2 pp:2-24
[40] Texas Instruments ,TMS320C6000 CPU and Instruction Set Reference Guide, 1999.3 pp：294-310
[41] Texas Instruments ,TMS320C6000 System Clock Circuit Example, 1999.3 pp：20-30
[42] Texas Instruments ,TMS320C6000 Reset Circuit, 1999.3 pp：20-25
[43] Texas Instruments ,TMS320C6000 Power Supply, 1999.3 pp：10-15
[44] Texas Instruments ,TMS320C6000 Peripheral Reference Guide, 1999 pp:496-100
[45] 周富强，张广军 视觉检测中高速图像采集技术的研究[J] 北京航空航天大学学报，Vol 28 No 2 2002.4
王劲 用两片I2C总线接口通用器件PCF8574扩展的8×8键盘[J] 电子技术 1997.No.4
[46] pp：37-38
[47] 胡跃全 I2C总线与PC机接口设计[J] 测控技术 1995 Vol 14 No 3 pp：21-22
[48] P87LPC761 Datasheet, Philips Semiconductors, 1989 pp:1-10
[49] SAA7111AH Datasheet, Philips Semiconductors, 1998 May 15 pp:2-30
[50] 吕铁英 彭嘉雄，图像轮廓特征提取的新方法的研究[J]，中国图像图形学报 1999.8 Vol 4 No.8
[51] Woodham, R. J. Analysing Images of Curved Surfaces[J], AI. 17(1981) pp: 117-140
[52] N. Kanopoulos, N. Vasanthavada and R. L. Baker, esign of an Image Edge Detection Filter Using the Sobel Operator[J] IEEE Journal of solid-state circuits, vol. 23, No. 2, pp1-2, April 1988