基于图像识别与追踪技术的高速公路交通事件有效检测范围

针对视频交通事件检测器的有效检测范围目前在行业内产生的广泛争议,结合摄像机安装高度、安装角度、摄像机性能指标,通过理论计算和试验验证,得到视频交通事件检测系统对相关交通事件的合理检测范围,从而为高速公路全程视频监控系统外场监控摄像机的布设间距、布设方式提供数据支持,实现高速公路全程无盲区智能化监控识别。计算结果表明,对于小汽车停驶等交通事件,其有效检测距离大于1 000 m的传统说法是不准确的,目前的技术水平很难达到,其合理检测距离应该在500 m左右,试验数据验证了这一说法,但视频交通事件检测系统的有效检测距离后续会随着摄像机性能的不断增强而有所提高,从而满足高速公路监控系统不断提高的监控需求。     

高速公路监控系统中几种视频传输方案

总结分析了视频传输2种方式的各自特点,主要针对数字传输的几种方案做了比较.针对高速公路视频传输的构成情况,分别阐述了站点至中心、摄像机至站点的传输方案.最终建议针对项目具体情况采取相应的视频传输方案.     

一种利用参考图象与路面信息的道路监控摄像机标定方法

鉴于基于视频处理技术的交通流检测系统需要进行摄像机的标定才能得到准确的车流速度信息,而传统的人工标定法无法满足道路监控摄像机发生人为转动时的这一要求,提出了一种基于参考图像与路面信息的的道路监控摄像机标定方法.该方法利用车道标线的宽度和间距以及一条垂直于车道标线的线段,即可估计出摄像机的焦距、俯角、水平偏角和距离地面的高度,同时,为了计算“病态条件”下的摄像机参数,提出了在焦距保持不变的情况下,通过旋转摄像机来获取一组合适的参考图像,再通过参考图像来实现标定.在摄像机发生人为转动的情况下,也能方便地通过参考图像和路面信息来实现重标定.仿真试验表明,该方法具有操作方便、计算简单精确的优点,且无需人工现场操作,大大减少了外业工程量.     

福建平潭海峡大桥监控系统研究

文中介绍了福建平潭海峡大桥监控系统设计方案。其监控系统主要通过计算机系统、遥控摄像机、车道指示标志、气象检测、光纤传输设备等共同构成。以全程视频监控、交通信息发布、气象监测为设计重点,着重介绍监控分中心系统构成、外场监控设备布设原则及数据信息传输。本系统为运营管理部门在交通指挥、突发事件的应急处置提供全面的信息服务,实现跨海大桥智能化运营管理。     

广乐高速公路施工视频监控系统的设计与实现

从网络架构、监控技术的选用以及系统软件设计等方面介绍了如何搭建工程建设项目施工视频监控平台,实现了视频监控系统在项目管理公司及分散的监控点大规模网络化应用,而在实际应用中,有效解决网络传输和摄像机的兼容性、开放性等问题。     

基于汽车前照灯的夜间车辆定位方法研究

全天候车辆视频检测白天和黑夜车辆时其检测条件差异很大,要选择不同的检测方法。在夜间无补光光源环境下,将摄像机获得的彩色视频图像进行灰度处理,夜间图像中汽车前照灯具有很强的特征,因此对灰度图像进行二值化处理和灰度统计来提取前照灯的特征,根据汽车前照灯在画面中的形态特征设计了相应的定位算法,实现了夜间车辆的定位检测。实验结果表明,该方法实现夜间车辆定位的突出特点是定位准确,且定位时间短,满足了视频交通系统实时性的要求。     

基于信息融合的车辆险态运行模式评价研究

提出了一种车辆运行状态识别体系.鉴于车辆行驶环境的复杂性,多作业工况条件的影响以及车辆行驶行为表现特征的多元性,采用BP神经网络技术与Dempster-Shafer证据推理技术相结合的信息模式分类及融合判断的解决方案.为验证所提出的方案,建立车载摄像机视频实时检测系统,以车道偏离信息和跟驰车间距信息作为车辆行驶的表征参量,实现车辆险态行驶特征表现的检测和评价.研究结果表明,模式分类和多源信息融合决策技术的综合运用提高了车辆危险行驶姿态表征信息甄别的自适应性和智能化水平.      

基于违法要素的电子警察车辆视频检测技术研究

随着平安城市、智能交通等项目的建设,针对电子警察的研究越来越多,而抓拍违法要素无疑是电子警察违法认定的重要依据,因此对违法要素的检测显得尤为重要。对目前常用的几种车辆视频检测技术在电子警察违法要素中的应用展开初步探讨,并分析和比较各技术特点和限制,以区别其适用的范围,提出在电子警察工程设计和实际应用中,将几种车辆视频检测技术进行有机结合,才能进一步提高车辆违法的捕获率、号牌识别的准确率等技术指标。     

浅谈北京市远郊区县电视监控系统的建设情况及应用效果

为维护好首都的交通治安秩序，把好北京的门户，预防和查处违法逃逸机动车辆通过各进出京交通要道，建立了远郊区县电视监控系统。此系统主要解决过境车辆监控，包括全天候24小时监控，无遗漏视频移动检测、数字图低压缩记数据库管理、图像实时显示、图像回放、利用光缆或电话线实现在数据图像的远程传输等。该系统的应用，收到了良好的社会效益，有力地维护了交通秩序及社会治安环境。     

视频交通事件检测系统在京秦高速公路中的应用

实时视频交通事件检测系统作为全程监控系统建设项目的重要组成部分,实现了交通事件的快速、准确检测以及及时有效的处理。文中对京秦高速公路视频交通事件检测系统的构成、功能及应用状况进行了分析,针对应用中存在的问题提出了改进建议。     

基于单线圈的车速检测算法研究

简述了基于环形线圈车速检测的基本原理、目前利用单线圈检测量进行车速估计的方法。在此基础上，提出了一种利用单线圈进行车速实时检测的算法，并设计了一套基于单线圈的车速检测系统，通过采集系统在实验中的数据，运用Matlab6．5对该检测算法进行了仿真分析。结果表明，算法基本符合设计要求。     

车辆前方行驶环境识别技术探讨

基于雷达和视觉技术对车辆前方行驶环境识别,进而判断车辆安全状态和实现纵向横行运动状态警示和控制,其是实现汽车安全辅助驾驶的主要技术途径。介绍车辆前方行驶环境识别涉及到的雷达和视觉的一些技术,其中包括雷达种类和适用场合,雷达检测障碍物的算法,车用图像的性能要求,基于图像特征和模型的车道线识别的方法,利用图像实现其他环境信息识别的方法。     

Switched control of vehicle suspension based on motion-mode detection

This paper presents a study on switched control of vehicle suspension based on motion-mode detection. This control strategy can be potentially implemented via the interconnected suspension such as hydraulically interconnected suspension by actively switching its interconnection configuration in terms of the dominant vehicle body motion-mode. The design of the switched control law is developed focusing on three vehicle body motion-modes: bounce, pitch, and roll. At first, an H_∞ optimal controller will be designed for each motion-mode with the use of a common quadratic Lyapunov function, which guarantees the stability of the switched system under arbitrary switching functions. Then, a motion-mode detection method based on the calculation of the motion-mode energy is introduced. And then, the possible implementation of the control system in practice is discussed. Finally, numerical simulations are used to validate the proposed study.     

基于机器视觉的车辆检测与参数识别研究进展

近年来公路交通运输快速增长，交通车辆的快速准确检测与识别对智能交通系统和交通基础设施运维具有重要意义。随着机器视觉和深度学习技术的迅速发展及其在目标检测领域的广泛应用，车辆目标检测和参数识别也取得新的突破。该文从车辆参数的识别方法和应用研究两方面梳理了机器视觉和深度学习在车辆检测与参数识别领域的研究现状、最新研究成果和未来发展趋势。在识别方法方面，将车辆检测方法分为3类：运动目标检测方法、目标实例检测方法和细粒度检测方法，系统总结了这3类方法的基本原理和各自特点。在应用研究方面，详细综述了基于机器视觉的车辆检测方法在车辆参数识别中的应用现状，主要包括车辆类别、车辆时空参数、车辆重量参数识别以及车辆多参数识别系统。最后对基于机器视觉和深度学习的车辆参数识别研究进行了归纳总结，并讨论了当前存在的挑战和未来可能的发展趋势。研究表明，对于不同的环境条件和车辆参数，应根据实际需要和各算法特点选择合适的车辆检测方法。目前方法仍局限于单参数或少量参数的独立检测，且识别精度和效率难以同时满足。后续研究应注重与新技术的融合，提高在现实复杂环境下车辆参数识别的精度、效率、鲁棒性及全面性，以使其更好地应用于工程实际。     

Vehicle detection system design based on stereo vision sensors

Vehicle detection is a crucial issue for driver assistance system as well as for autonomous vehicle guidance function and it has to be performed with high reliability to avoid any potential collision. The vision-based vehicle detection systems are regarded promising for this purpose because they require little infrastructure on a highway. However, the feasibility of these systems in passenger car requires accurate and robust sensing performance. In this paper, a vehicle detection system using stereo vision sensors is developed. This system utilizes feature extraction, epipoplar constraint and feature matching in order to robustly detect the initial corresponding pairs. The proposed system can detect a leading vehicle in front and can estimate its position parameters such as the distance and heading angle. After the initial detection, the system executes the tracking algorithm for the vehicles in the lane. The proposed vehicle detection system is implemented on a passenger car and its performances are verified experimentally.     

基于工况双向压力法的商用车空调检漏技术

为解决汽车空调的冷媒泄漏问题,从全系列商用车空调系统的结构和原理研究入手,通过对空调系统的泄漏问题进行调查和分析,建立了空调泄漏失效模式,利用真空度和工况压力差值关系判断空调泄漏质量,探索工况双向压力法空调检漏技术,提高了空调检漏的可靠性、准确率及效率,使空调泄漏的售后赔偿下降60%以上,提升其自身品质质量。     

Field tests for evaluating cooperative intersection signal violation warning system (CISVWS)

This paper demonstrates the results of field tests for assessing a cooperative intersection signal violation warning system (CISVWS), which consists of (a) hardware, including an in-vehicle warning device, roadside antenna, and traffic signal controller, and (b) software to operate and test the cooperative system through vehicle to infrastructure (V2I) communication systems. Field tests were performed under real traffic situations in order to test the system in terms of the initiation time of the signal violation warning from the signal controller, the activation and duration of on board equipment (OBE), and the warning delay based on the relationships between distance variables, including the safe stopping distance, and the location of road side equipment (RSE). Findings from the field test at the real-world signalized intersection sites indicated that the system would be capable of reducing red light violations and intersection collisions through use of the in-vehicle warning device at signalized intersections.     

Low cost design of parallel parking assist system based on an ultrasonic sensor

This paper presents a low cost design and implementation of a parallel parking assist system (PPAS) based on ultrasonic sensors. Generally, a PPAS requires several types of sensors, such as an ultrasonic sensor, camera sensor, radar sensor and laser sensor for parking space detection. However, our proposed PPAS only requires two ultrasonic sensors on the front and lateral sides for parking space detection. Moreover, a steering angle sensor and wheel speed sensor installed in the vehicle are used to obtain vehicle position information for localization in ultrasonic range data. The hardware architecture of the PPAS based on an electronic control unit (ECU) module, sensor modules and a human machine interface (HMI) module was proposed. Moreover, the software architecture of the PPAS is based on system initialization, scheduling, recognition and a control algorithm. In particular, a novel sensor algorithm was proposed to minimize the vehicle corner error of the ultrasonic sensor. A prototype of the PPAS based on the proposed architecture was constructed. The experimental results demonstrate that the implemented prototype is robust and successfully performs parking space detection and automatic steering control. Finally, the low cost design and implementation of the PPAS was possible due to the cheap ultrasonic sensors, simple hardware design and low computational complexity of the proposed algorithm.     

基于视频图像处理的车辆排队长度检测

综合灰度检测和边缘检测的优点，提出了一种将灰度与边缘检测相结合的方法来检测队列长度，采用帧平均法来处理视频流，可以减小由于摄像头抖动或背景微小变化而产生的误差。提出的队列检测算法包含运动检测和车辆存在检测，通过合理分配使用这两种操作，节省了运算时间。实验结果表明，此方法实现简单，能够获得较满意的检测结果。     

Real-time vision-based blind spot warning system: Experiments with motorcycles in daytime/nighttime conditions

This paper describes a real-time vision-based blind spot warning system that has been specially designed for motorcycles detection in both daytime and nighttime conditions. Motorcycles are fast moving and small vehicles that frequently remain unseen to other drivers, mainly in the blind-spot area. In fact, although in recent years the number of fatal accidents has decreased overall, motorcycle accidents have increased by 20%. The risks are primarily linked to the inner characteristics of this mode of travel: motorcycles are fast moving vehicles, light, unstable and fragile. These features make the motorcycle detection problem a difficult but challenging task to be solved from the computer vision point of view. In this paper we present a daytime and nighttime vision-based motorcycle and car detection system in the blind spot area using a single camera installed on the side mirror. On the one hand, daytime vehicle detection is carried out using optical flow features and Support Vector Machine-based (SVM) classification. On the other hand, nighttime vehicle detection is based on head lights detection. The proposed system warns the driver about the presence of vehicles in the blind area, including information about the position and the type of vehicle. Extensive experiments have been carried out in 172 minutes of sequences recorded in real traffic scenarios in both daytime and nighttime conditions, in the context of the Valencia MotoGP Grand Prix 2009.