基于PDA的上海市交通信息网格发布平台

提出了一种网格环境下基于PDA的交通信息发布系统。该系统以强大的交通信息网格为支撑，在PDA嵌入式平台上为用户提供交通信息，尤其是动态信息的获取、可视化、分析、输出等服务。该系统为PDA用户提供基于网络技术的实时交通路况、动态路径决策等传统导航设备所缺乏的实时动态信息。从系统总体架构、实现的关键技术、与后台网格的交互过程等多方面介绍了该移动导航系统的设计与实现。     

基于手机RFSIM与北斗GIS城市实时交通动态导航平台

目前,从智能交通系统的发展（ITS）来看,国内大多数导航系统为静态导航,缺乏根据实时交通信息进行动态导航的功能.从而提出一种基于手机RFSIM与GIS技术结合的城市实时交通动态导航平台,为出行者提供实时动态的交通信息和导航服务.该系统主要包括实时交通信息采集系统,短时交通预测系统,北斗或GPS定位以及GIS实时导航系统.在已获得的相关技术的支撑下,着力解决在此导航系统中涉及到的交通信息的获取、北斗定位和实时交通动态导航中的关键技术问题,并进行可行性分析.     

基于旅行时间检测系统的交通应用研究

由于旅行时间的采集日趋精确，在交通领域被广泛地应用。首先介绍了一种基于精确车牌识别技术的旅行时间检测系统，然后重点阐述了检测数据的决策信息分析和处理，最后提出了一种以旅行时间为目标参数，以元胞自动机模型为基础的短时交通预测模型，并对其关键技术和难点进行了讨论和分析。     

基于DSP的交通信息采集系统

本文介绍了一种基于视频处理的交通信息采集设备的设计方案.该方案利用摄像头采集交通视频,一方面通过DSP6203B进行分析处理得到各种实时交通信息,另一方面通过ADSP 2185进行图像的小波压缩.最后,交通信息和压缩图像通过嵌入式网络传输模块传送到交通控制中心.     

嵌入式视频交通信息检测卡设计

详述了基于嵌入式DSP和PCI总线的视频交通信息检测卡工作原理及软硬件设计方案;该系统能够实时的采集视频交通数据,并且通过DSP处理器完成交通信息参数的提取,提取的交通信息参数通过PCI总线传输至监控主机;实验结果证明该系统能够对交通视频图像完成实时的处理,其技术指标均达到设计要求,在智能交通系统中得到很好的应用。     

基于GPRS的信息采集系统智能终端的设计

介绍了基于GPRS的无线传输技术在智能交通信息采集系统中进行数据传输的优点和A-GPS技术，分析了信息采集系统的组成结构及其工作原理，并重点介绍了中兴通讯P800智能终端硬件和软件的设计；另外，在对采集来的视频信息进行传输时，为了提高视频效果清晰度，给出了视频图像压缩的数据处理流程。最后，阐述了基于P800智能终端信息采集平台在移动奥运的应用。     

基于ARM和GSM的嵌入式农田信息采集系统设计

针对精准农业对农田信息的采集要求和目前基于单片机的采集装置存在的不足,将农田数据采集与嵌入式技术、GPS和GSM通信技术相结合,以ARM9处理器为核心,并辅以高精度数据采集电路,设计了一种基于ARM和GSM的嵌入式农田信息采集系统.系统能将采集的农田信息以GSM短消息的形式发送到数据采集中心,解决了野外信息存储的有限性和移动测量的不便性等问题,为农田信息的远程采集提供一种有效的解决方案.     

一种嵌入式无线车辆信息采集系统设计

提出了一种新的嵌入式无线车辆信息采集系统设计方案,这种方案基于S3C6410硬件平台和嵌入式WinCE操作系统。研究了基于磁阻传感器的无线车辆检测技术的基本原理与通信方式;针对无线车辆信息采集系统的构成与实现方法进行了详细的研究与设计;在嵌入式WinCE平台下完成了基于MFC的无线车辆信息采集系统的应用程序界面和功能的开发,并对系统进行了车辆存在和车速测试。测试结果表明:系统能够在低功耗工况下实现对车辆信息的采集、存储、传输和控制,并且运行良好。     

基于视频检测的高速公路交通信息采集系统设计

基于视频检测技术设计了一种实时的高速公路交通信息采集系统。系统利用图像处理技术对交通视频进行实时分析,能有效地获取车流量、车速、道路占有率等基本交通信息。现场测试结果表明,该系统具有很好的实时性和可靠性。     

基于GPRS的信息采集系统智能终端的设计

介绍了基于GPRS的无线传输技术在智能交通信息采集系统中进行数据传输的优点和A-GPS技术,分析了信息采集系统的组成结构及其工作原理,并重点介绍了中兴通讯P800智能终端硬件和软件的设计;另外,在对采集来的视频信息进行传输时,为了提高视频效果清晰度,给出了视频图像压缩的数据处理流程。最后,阐述了基于P800智能终端信息采集平台在移动奥运的应用。     

Communications-oriented development of component-based vehicular distributed real-time embedded systems

We propose a novel model- and component-based technique to support communications-oriented development of software for vehicular distributed real-time embedded systems. The proposed technique supports modeling of legacy nodes and communication protocols by encapsulating and abstracting the internal implementation details and protocols. It also allows modeling and performing timing analysis of the applications that contain network traffic originating from outside of the system such as vehicle-to-vehicle, vehicle-to-infrastructure, and cloud-based applications. Furthermore, we present a method to extract end-to-end timing models to support end-to-end timing analysis. We also discuss and solve the issues involved during the extraction of these models. As a proof of concept, we implement our technique in the Rubus Component Model which is used for the development of software for vehicular embedded systems by several international companies. We also conduct an application-case study to validate our approach.     

基于实时视觉分析算法的智能图像传感器系统设计

设计了一种智能交通图像传感器系统以实现对监控场景的快速移动侦测和对象识别。该系统具有有线以太网和无线GPRS双重网络接入功能,硬件由基于Au1200嵌入式处理器的网络接口端和基于BlackFin 533 DSP处理器的图像分析端组成。软件系统包括运行于Au1200处理器上的基于嵌入式Linux架构的网络收发软件和运行于BlackFin 533 DSP上的视觉分析算法。本系统引入了基于区域分割的背景模型和基于特征的对象识别算法。实验结果表明该系统能够实时高效地进行自动移动检测和对象分类识别。     

A Parallel Pipeline Based Multiprocessor System For Real-Time Measurement of Road Traffic Parameters

Real-time measurement and analysis of road traffic flow parameters such as volume, speed and queue are increasingly required for traffic control and management. Image processing is considered as an attractive and flexible technique for automatic analysis of road traffic scenes for the measurement and data collection of road traffic parameters. In this paper, the authors describe a novel image processing based approach for analysis of road traffic scenes. Combined background differencing and edge detection techniques are used to detect vehicles and measure various traffic parameters such as vehicle count and the queue length. A RISC based multiprocessor system was designed to enable real-time execution of the authors algorithm. The multiprocessor system has nine processing modules connected in a parallel pipeline fashion. Results shows that the authors multiprocessor system is able to provide measurement of traffic parameters in real-time. Results are presented for real tests of our system by analysing traffic scenes on the highways of Singapore.     

嵌入式视频监控系统实时性研究

针对目前嵌入式系统资源有限及提高视频传输实时性方案不适合嵌入式视频监控系统的情况,提出基于视频流量预测和网络带宽检测的提高视频监控系统实时性方案。该方案采用线性规划视频流量预测算法和数据包的方法检测网络带宽,预测视频流量和网络带宽,据此调整视频缓存,达到提高视频实时性且节约系统资源的目标。     

A NetFlow based flow analysis and monitoring system in enterprise networks

In this paper, a flow analysis and monitoring system based on NetFlow is introduced. The system is built on a Browser–Server framework, aimed at enterprise networks. Data collection and display are separated into two modules, which makes the system clearly demarcated and easy to deploy. The data collection module receives and analyzes NetFlow-exported packets and inserts per flow record information into the Oracle database. The display module acts as a J2EE web server, fetches real-time or history traffic information from the database and shows it to web users. In addition to the above-mentioned functions, the most important part of the system is an IDS. A real-time anomalous traffic monitoring module with a stable matching pattern algorithm and two traffic statistic based intrusion detection algorithms – one algorithm is based on variance similarity while the other is based on Euclidean distance – are embedded in the system to detect worm and other malicious attacks. With the aim of identifying anomalous network traffic simply and effectively, a proved “join” strategy is also designed along with the two traffic statistic based intrusion detection algorithms. The whole IDS module is able to run with low computational complexity and high detection accuracy. Finally, we conduct experiments to verify the performance of our system.     

Trajectory-based vehicle tracking at low frame rates

In smart cities, an intelligent traffic surveillance system plays a crucial role in reducing traffic jams and air pollution, thus improving the quality of life. An intelligent traffic surveillance should be able to detect and track multiple vehicles in real-time using only limited resources. Conventional tracking methods usually run at a high video-sampling rate, assuming that the same vehicles in successive frames are similar and move only slightly. However, in cost effective embedded surveillance systems (e.g., a distributed wireless network of smart cameras), video frame rates are typically low because of limited system resources. Therefore, conventional tracking methods perform poorly in embedded surveillance systems because of discontinuity of the moving vehicles in the captured recordings. In this study, we present a fast and light algorithm that is suitable for an embedded real-time visual surveillance system to detect effectively and track multiple moving vehicles whose appearance and/or position changes abruptly at a low frame rate. For effective tracking at low frame rates, we propose a new matching criterion based on greedy data association using appearance and position similarities between detections and trackers. To manage abrupt appearance changes, manifold learning is used to calculate appearance similarity. To manage abrupt changes in motion, the next probable centroid area of the tracker is predicted using trajectory information. The position similarity is then calculated based on the predicted next position and progress direction of the tracker. The proposed method demonstrates efficient tracking performance during rapid feature changes and is tested on an embedded platform (ARM with DSP-based system).     

构件化可配置实时嵌入式操作系统设计与实现

新一代嵌入应用需要自配置和定制操作系统,剪裁掉不必要的系统功能来获得更高的性能和更低的系统开销。软件构件是以可重用为目的设计、封装软件的技术,是操作系统配置管理的基础。提出设计构件化可配置实时嵌入式操作系统的方法：系统功能划分、构件界面划分、配置处理,并依据该理论进行了系统设计与实现,原型系统证明是可配置的,易于用户定制的,也提供了实时嵌入式操作系统所必要的特性。     

Collaborative real-time traffic information generation and sharing framework for the intelligent transportation system

Real-time traffic information collection and data fusion is one of the most important tasks in the advanced traffic management system (ATMS), and sharing traffic information to users is an essential part of the advance traveler information system (ATIS) among the intelligent transportation systems (ITS). Traditionally, sensor-based schemes or probing-vehicle based schemes have been used for collecting traffic information, but the coverage, cost, and real-time issues have remained unsolved. In this paper, a wiki-like collaborative real-time traffic information collection, fusion and sharing framework is proposed, which includes user-centric traffic event reacting mechanism, and automatic agent-centric traffic information aggregating scheme. Smart traffic agents (STA) developed for various front-end devices have the location-aware two-way real-time traffic exchange capability, and built-in event-reporting mechanism to allow users to report the real-time traffic events around their locations. In addition to collecting traffic information, the framework also integrates heterogeneous external real-time traffic information data sources and internal historical traffic information database to predict real-time traffic status by knowledge base system technique.     

基于嵌入式Linux的实时优化方案

在分析了国外两种主流嵌入式Linux实时化的实现方法的基础上,根据实时操作系统和Linux的特点,就实时调度策略、细粒度定时器等几个方面提出了改善系统实时性的一种优化方案。