面向车联网的车载智能终端研究与实现
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Key words: Intelligent Transportation; Vehicle Active Safety; Vehicular Network; Embedded; Lane Identification; JPEG
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目录
第一章 绪论 .............................................................................................................................. 1 1.1 论文的研究背景 .......................................................................................................... 1 1.2 本文研究的目的和意义 .............................................................................................. 3 1.3 国内外研究现状 .......................................................................................................... 3 1.3.1 国外研究现状 .................................................................................................... 4 1.3.2 国内研究现状 .................................................................................................... 6 1.4 本文的主要研究内容 .................................................................................................. 8
Experiment results show that the system is stable and reliable. It can meet the needs of engineering application in vehicle identification, image compression & transmission and vehicle driving information sharing.
1、开发了一种面向车联网的车载智能终端系统。该系统将摄像机、GPS 接收器、 无线网卡等设备连接到嵌入式终端上。终端以 ARM11 为主控单元，以 Linux 为运行环 境，实现了车辆自身行车环境信息的感知与传输。
2、设计了基于单目视觉的车辆安全距离预警算法，该算法首先利用车辆前方图像 在目标信息分布、灰度、边缘、纹理和形状五个方面的特征，实现了车道线的自动提取， 然后利用车辆下方阴影特征和矩形特征实现了车道线内车辆的定位，最后根据单目成像 的几何模型，计算当前车与前方车辆的距离。
A Thesis Submitted for the Degree of Master
Candidate：Zhang Licheng Supervisor：Prof. Zhao Xiangmo
Chang’an University, Xi’an, China
摘要
车联网是智能交通领域的一个重要研究方向，车载智能终端是车联网系统中的核心 部件，它通过获取自身及周围车辆的行车环境信息，辅助驾驶员进行安全驾驶，从而提 高车辆的主动安全性。目前一些汽车制造商根据市场需求开发出了一些车辆主动安全设 备，但大都存在功能简单、通信接口不统一、成本较高、短期内不易普及等不足。为此， 论文研究ቤተ መጻሕፍቲ ባይዱ发了一种面向车联网行车安全的车载智能终端系统，并对系统中多项关键技 术问题进行了深入研究，主要内容包括：
4. The problem of mutually information isolation among cars under highway environment was solved. Information was uploaded to the server and could be obtained by other terminals from the server. A back-stage management system was designed, which achieves the view of scene images, vehicle tracking and trace playback.
3、设计了基于图形处理器（GPU:Graphic Processing Unit）的现场图像 JPEG 编解 码算法。该算法充分利用 JPEG 编解码任务的可并行性及 GPU 的多核资源，将占用时 间最长、独立性较好的离散余弦变换及其逆变换移植到 GPU 上执行，提高了系统的实 时性。
4、解决了高速公路行驶环境下，车与车之间的信息不能交互的问题。车载智能终 端将自身的行车环境信息通过无线通信方式上传至服务器，同时，从服务器获取周围车 辆的行车环境信息。后台管理软件从服务器获取数据后，结合 GIS 实现了现场图片查看、 车辆定位及行驶轨迹回放等功能。
分类号：U49 10710-2009124074
硕士学位论文
面向车联网的车载智能终端研究与实现
张立成
导师姓名职称
赵祥模 教授
申请学位级别
工学硕士 学科专业名称 交通信息工程及控制
论文提交日期 2012 年 5 月 30 日 论文答辩日期 2012 年 6 月 11 日
学位授予单位
长安大学
Research and Implementation of an Intelligent Vehicle Terminal for Vehicular Network
3. A JPEG codec algorithm of field images based on graphic processor(GPU: Graphic Processing Unit) was designed, which makes full use of task parallelism and GPU multi-core resources. The discrete cosine transform and its inverse transform were ported to GPU, which enhance the real-time performance of the system.
试验结果表明：本文开发的系统运行稳定可靠，在目标车辆识别、图像压缩传输及 行车环境信息共享等方面均可满足实际工程应用的需求。
关键词：智能交通，车辆主动安全，车联网，嵌入式，车道线识别，JPEG
i
Abstract
Vehicular network is one of the important research directions in intelligent transportation field. And the intelligent vehicle terminal is the core of vehicular network. It obtains self and other information to assist drivers with safety driving and improve the active safety of vehicles. The existing active safety equipments are developed independently by manufactures, which have disadvantages of higher price, nonuniform communication interface and low popularity. So, an intelligent vehicle terminal system for vehicular network was researched and developed. This paper solved several key problems of the system, including:
第二章 车载智能终端总体方案 .............................................................................................. 9 2.1 系统功能需求分析 ...................................................................................................... 9 2.2 系统网络拓扑结构 ...................................................................................................... 9 2.3 系统硬件总体结构 .................................................................................................... 11 2.4 系统软件总体结构 .................................................................................................... 12 2.5 系统工作流程设计 .................................................................................................... 14 2.6 系统开发环境与开发工具选择 ................................................................................ 15
1. An intelligent vehicle terminal for vehicular network was developed. Camera, GPS receiver, wireless network card were connected to an embedded chip. The terminal used ARM11 as the main control unit, with Linux as the operating environment to realize data acquisition and wireless transmission.
2. A method of vehicle safety distance warning based on machine vision was designed. Firstly, the lane line extraction was realized with the five features of the field image, which are target information distribution, gray, edge, texture and shape. Then, the vehicle target within the lane line was identified using the shadow and rectangular feature under the vehicle. Finally, the distance between the current vehicle and target vehicle was calculated based on the geometric model of monocular imaging.
Key words: Intelligent Transportation; Vehicle Active Safety; Vehicular Network; Embedded; Lane Identification; JPEG
iv
目录
第一章 绪论 .............................................................................................................................. 1 1.1 论文的研究背景 .......................................................................................................... 1 1.2 本文研究的目的和意义 .............................................................................................. 3 1.3 国内外研究现状 .......................................................................................................... 3 1.3.1 国外研究现状 .................................................................................................... 4 1.3.2 国内研究现状 .................................................................................................... 6 1.4 本文的主要研究内容 .................................................................................................. 8
Experiment results show that the system is stable and reliable. It can meet the needs of engineering application in vehicle identification, image compression & transmission and vehicle driving information sharing.
1、开发了一种面向车联网的车载智能终端系统。该系统将摄像机、GPS 接收器、 无线网卡等设备连接到嵌入式终端上。终端以 ARM11 为主控单元，以 Linux 为运行环 境，实现了车辆自身行车环境信息的感知与传输。
2、设计了基于单目视觉的车辆安全距离预警算法，该算法首先利用车辆前方图像 在目标信息分布、灰度、边缘、纹理和形状五个方面的特征，实现了车道线的自动提取， 然后利用车辆下方阴影特征和矩形特征实现了车道线内车辆的定位，最后根据单目成像 的几何模型，计算当前车与前方车辆的距离。
A Thesis Submitted for the Degree of Master
Candidate：Zhang Licheng Supervisor：Prof. Zhao Xiangmo
Chang’an University, Xi’an, China
摘要
车联网是智能交通领域的一个重要研究方向，车载智能终端是车联网系统中的核心 部件，它通过获取自身及周围车辆的行车环境信息，辅助驾驶员进行安全驾驶，从而提 高车辆的主动安全性。目前一些汽车制造商根据市场需求开发出了一些车辆主动安全设 备，但大都存在功能简单、通信接口不统一、成本较高、短期内不易普及等不足。为此， 论文研究ቤተ መጻሕፍቲ ባይዱ发了一种面向车联网行车安全的车载智能终端系统，并对系统中多项关键技 术问题进行了深入研究，主要内容包括：
4. The problem of mutually information isolation among cars under highway environment was solved. Information was uploaded to the server and could be obtained by other terminals from the server. A back-stage management system was designed, which achieves the view of scene images, vehicle tracking and trace playback.
3、设计了基于图形处理器（GPU:Graphic Processing Unit）的现场图像 JPEG 编解 码算法。该算法充分利用 JPEG 编解码任务的可并行性及 GPU 的多核资源，将占用时 间最长、独立性较好的离散余弦变换及其逆变换移植到 GPU 上执行，提高了系统的实 时性。
4、解决了高速公路行驶环境下，车与车之间的信息不能交互的问题。车载智能终 端将自身的行车环境信息通过无线通信方式上传至服务器，同时，从服务器获取周围车 辆的行车环境信息。后台管理软件从服务器获取数据后，结合 GIS 实现了现场图片查看、 车辆定位及行驶轨迹回放等功能。
分类号：U49 10710-2009124074
硕士学位论文
面向车联网的车载智能终端研究与实现
张立成
导师姓名职称
赵祥模 教授
申请学位级别
工学硕士 学科专业名称 交通信息工程及控制
论文提交日期 2012 年 5 月 30 日 论文答辩日期 2012 年 6 月 11 日
学位授予单位
长安大学
Research and Implementation of an Intelligent Vehicle Terminal for Vehicular Network
3. A JPEG codec algorithm of field images based on graphic processor(GPU: Graphic Processing Unit) was designed, which makes full use of task parallelism and GPU multi-core resources. The discrete cosine transform and its inverse transform were ported to GPU, which enhance the real-time performance of the system.
试验结果表明：本文开发的系统运行稳定可靠，在目标车辆识别、图像压缩传输及 行车环境信息共享等方面均可满足实际工程应用的需求。
关键词：智能交通，车辆主动安全，车联网，嵌入式，车道线识别，JPEG
i
Abstract
Vehicular network is one of the important research directions in intelligent transportation field. And the intelligent vehicle terminal is the core of vehicular network. It obtains self and other information to assist drivers with safety driving and improve the active safety of vehicles. The existing active safety equipments are developed independently by manufactures, which have disadvantages of higher price, nonuniform communication interface and low popularity. So, an intelligent vehicle terminal system for vehicular network was researched and developed. This paper solved several key problems of the system, including:
第二章 车载智能终端总体方案 .............................................................................................. 9 2.1 系统功能需求分析 ...................................................................................................... 9 2.2 系统网络拓扑结构 ...................................................................................................... 9 2.3 系统硬件总体结构 .................................................................................................... 11 2.4 系统软件总体结构 .................................................................................................... 12 2.5 系统工作流程设计 .................................................................................................... 14 2.6 系统开发环境与开发工具选择 ................................................................................ 15
1. An intelligent vehicle terminal for vehicular network was developed. Camera, GPS receiver, wireless network card were connected to an embedded chip. The terminal used ARM11 as the main control unit, with Linux as the operating environment to realize data acquisition and wireless transmission.
2. A method of vehicle safety distance warning based on machine vision was designed. Firstly, the lane line extraction was realized with the five features of the field image, which are target information distribution, gray, edge, texture and shape. Then, the vehicle target within the lane line was identified using the shadow and rectangular feature under the vehicle. Finally, the distance between the current vehicle and target vehicle was calculated based on the geometric model of monocular imaging.