车道识别过程中搜索车道线的方法

提出了一种在RO I(region of interest)即感兴趣区域中建立搜索窗口的车道识别算法,使其能够很好地处理非理想路况的各种不确定因素,并建立实时动态搜索窗口,除了能精确地追踪车道标志线之外,还能应用于弯路路况。运用LM edSquare曲线拟合算法提高了车道拟合过程的稳健性和精确性。由于RO I的建立,整个识别过程的计算量大大降低,适应实时性要求。     

基于Matlab的汽车偏离车道报警系统

为提高汽车的主动安全性并克服现有的汽车偏离车道报警系统所存在的结构复杂和成本高等缺点,文章设计了一种基于Matlab的汽车偏离车道报警系统,利用摄像头获取车道图像并实时传给车内计算机系统,经过对图像一系列的处理分析判断汽车是否偏离车道而进行报警。经验证,该系统能够实时检测出左右车道标志线,可以根据车道夹角法判断汽车是否偏离车道,满足了汽车偏离车道报警的需要。该系统结构简单高效,能显著提高汽车行驶的主动安全性。     

存在车辆干扰的车道线识别

为避免道路上行驶的其它车辆对车道线识别的干扰,提出了一种结合车辆识别的车道线识别方法。融合雷达数据,车辆识别模块首先在图像中识别出车辆占据的区域;对于每一个车道线识别模块挑出的车道线候选点进行判断,去除处于车辆区域的车道线点;如果有效车道线点数目不足,则利用卡尔曼滤波的跟踪结果,确定符合最小风险函数的车道线位置。经过多种工况下的试验验证,该方法能够稳定地对车道线进行识别,准确地提取车道线参数,并且算法对车辆干扰有良好的抵抗能力。     

基于扩展卡尔曼滤波的车道融合跟踪

车道检测算法的研究是智能车辆自动导航的首要环节。与目前基于视觉的车道检测与跟踪系统不同,本文提出一种基于扩展卡尔曼滤波的车道融合跟踪方法。该方法利用毫米波雷达探测到前方车辆的距离信息,并采用扩展卡尔曼滤波技术和图像处理技术,建立车道跟踪的动态视觉窗口,提取车道边界,并判断前方车辆相对于车道的位置。该方法大大缩减了处理时间,且增强了系统的鲁棒性。     

Driving environment assessment using fusion of in- and out-of-vehicle vision systems

Because the overall driving environment consists of a complex combination of the traffic Environment, Vehicle, and Driver (EVD), Advanced Driver Assistance Systems (ADAS) must consider not only events from each component of the EVD but also the interactions between them. Although previous researchers focused on the fusion of the states from the EVD (EVD states), they estimated and fused the simple EVD states for a single function system such as the lane change intent analysis. To overcome the current limitations, first, this paper defines the EVD states as driver’s gazing region, time to lane crossing, and time to collision. These states are estimated by enhanced detection and tracking methods from in- and out-of-vehicle vision systems. Second, it proposes a long-term prediction method of the EVD states using a time delayed neural network to fuse these states and a fuzzy inference system to assess the driving situation. When tested with real driving data, our system reduced false environment assessments and provided accurate lane departure, vehicle collision, and visual inattention warning signals.     

车道检测中感兴趣区域选择及自适应阈值分割

针对间断线型或因污迹掩盖、磨损导致的车道标线不连续等情况,在基于前帧图像检测结果设置感兴趣区域的车道标线跟踪算法基础上,通过区域对比度分析并结合自适应大津算法,建立了车道标线有效检测区域的筛选及其自适应阈值图像分割算法。多种典型车道线型下的图像检测试验表明,算法在保持良好实时性的同时,也体现出对不连续车道线型处或破损等因素的鲁棒性和自适应性。     

Potential safety benefits of lane departure prevention technology

Motor vehicles with advanced safety technologies are rapidly entering the marketplace and the impact of new features are transforming safety on roadways. Among the several safety related technologies currently available in the market, this paper aims to forecast the reduction in crashes with gradual adoption of vehicles with lane departure prevention (LDP) technology. Crash data for the state of Alabama from 2014 to 2016 were used to evaluate the safety benefits of LDP technology. In Alabama, 75% of single-vehicle crashes are the result of lane departure. A 20% effective LDP system implies, whereby an LDP system would prevent a vehicle from exiting a roadway on 20% of applicable instances, would reduce 2.7% and 16.4% of the relevant single-vehicle lane departure (SVLD) crashes by 2020 and 2045 respectively. With increase in the effectiveness of the technology, a greater reduction in crashes was observed. With 100% effectiveness, this technology can prevent 66.5% of SVLD crashes by year 2045. This study presents the first estimations of the number of crashes that could be reduced using LDP and therefore could have significant impacts on public and industry adoption rates of the technology. The results of this study influence policy making and regulatory approaches to improving motor vehicle safety and further recommend education and outreach activities to increase awareness on the benefits of LDP technology.     

移线综合评价模型及移线策略分析

用GPS导航装置实测了移线轨迹并建立了相应的多项式位移模型。该位移模型不仅与实测移线轨迹符合得较好，而且符合实际转向盘转角变化规律。移线综合评价模型中分析了移线难度和移线安全性。分析结果表明，移线前提高车速并合理选择移线车距是有利的。     

基于最大相关准则图像分割的结构化道路路径识别和跟踪算法

为提高基于视觉导航的智能车辆对结构化道路车道标识线的识别和跟踪精度,同时消除车流、阴影和光照不均匀等不利因素的影响,提出一种基于最大相关准则的图像分割算法及基于感兴趣区域的车道标识线跟踪算法:首先,对图像进行滤波和光线补偿等前期处理,采用最大相关准则的图像分割算法对道路图像进行阈值分割;然后,根据车道的结构特征及先验知识提取车道标识线的特征点,并运用最小二乘法对特征点拟合,得到车道模型的参数;最后,通过建立感兴趣区域(ROI)的方法实现对车道标识线的准确跟踪。试验结果表明,该算法具有很好的准确性、实时性和鲁棒性。     

公交专用车道效益评价方法探讨

对于设置公交专用车道的城市道路,其核心功能是满足人的出行需求。因此公交专用车道的评价应以人为单位,而并非以车辆为单位。本文提出的公交专用车道效益评价方法主要从单点交叉口的交通效益、通道的综合效益进行。文章的最后,运用该理论对广州市某路段公交专用车道及相关道路进行了评价和分析,验证了该方法的可行性。     

基于改进RepVGG网络的车道线检测算法

为提高自动驾驶系统中车道线检测的速度和精度,提出了基于可解耦训练状态与推理状态的车道线检测算法.在结构重参数化VGG(RepVGG)主干网络中引入注意力机制压缩-激励(SE)模块,增强对重要车道线信息的特征提取;同时设计并行可分离的辅助分割分支,对局部特征进行建模以提高检测精度.采用行方向位置分类车道线检测方式,在主干...     

A new shared control for lane keeping and road departure prevention

In recent years, the driver's active assistances have become important features in commercialised vehicles. In this paper, we present one of these features which consists of an advanced driver assistance system for lane keeping. A thorough analysis of its performance and stability with respect to variations in driver behaviour will be given. Firstly, the lateral control model based on visual preview is established and the kinematics model based on visual preview, including speed and other factors, is used to calculate the lateral error and direction error. Secondly, and according to the characteristics of the lateral control, an efficient strategy of intelligent electric vehicle lateral mode is proposed. The integration of the vehicle current lateral error and direction error is chosen as the parameter of the sliding mode switching function to design the sliding surface. The control variables are adjusted according to the fuzzy control rules to ensure that they meet the existence and reaching condition. A new fuzzy logic-based switching strategy with an efficient control law is also proposed to ensure a level of continuous and variable sharing according to the state of the driver and the vehicle positioning on the roadway. The proposed control law acts either at the centre of the lane, as a lane keeping assistance system to reduce the driver's workload for long trips, or as a lane departure avoidance system that intervenes for unintended lane departures. Simulation results are included in this paper to explain this concept.     

基于直接线性变换的车道偏离预警系统

为了提高车道偏离预警系统的检测精度及其便利性,提出了一种在感应区域内建立搜索窗口的车道识别算法,并利用数字图像处理及分析技术对所获道路图像进行滤波、增强及边缘识别处理,然后通过直接线性变换法将所获取的车道边缘信号的像素坐标转换为道路二维物方坐标,最后根据所获车道线坐标及汽车预设坐标显现汽车行驶状态,继而联系汽车驾驶状况,达到对汽车行驶状态的监控和对车道偏离的预警功能,具有良好的发展前景。     

基于路面图像对称性的车道偏离识别方法研究

利用车道边缘信息定义了边缘分布函数EDF,通过分析车道线在道路图像中的方向变化来判断车辆是否偏离了车道中央。将车道偏离识别问题通过EDF函数本身重要形态特征对称轴转换成一个数学问题,减少了动态道路场景噪声的影响,无需在测量车道方向时考虑摄像机自身的参数,提高了适应随机和动态道路环境的能力,是一种可靠的车道偏离识别方法。     

基于效用选择的换车道模型

通过论述当前换车道模型的常见实现方式,指出在换车道需求产生过程中广泛应用的PLC方法存在下列不足:(1)不能反映微观特性;(2)不具有普适性;(3)不能准确反应运行环境变化的影响;并从理论分析的角度指出换车道行为是驾驶员在不同车道行驶状态下满意程度的选择结果,其需求产生的过程可以用随机效用理论进行描述。通过引入随机效用理论,建立基于效用选择的换车道模型,并以其作为核心子模型之一,编写仿真程序并对复杂交通流进行验证,得到较好的效果。     

基于改进Hough变换的车道线检测

针对车道线检测中存在的诸多问题,在道路图像预处理的基础上,对Canny算子中的双阈值选取进行改进,能够自适应精确提取车道线边缘特征,并利用带极角约束的Hough变换完成直线检测。算法能够在不同道路环境中准确检测车道线标识,降低光照等因素对车道线检测结果的影响。     

基于道路模型的弯道检测研究与应用

基于机器视觉的弯道图像能提供车辆行驶道路环境的丰富信息,从建立弯道模型、提取车道线像素点以及拟合车道模型等步骤分析了传统基于道路模型的弯道检测方法,针对传统方法很难适用于多种不同形状弯道的特点,提出一种基于特征点提取的弯道检测新方法;介绍了弯道检测在车道偏离预警、弯道限速以及弯道防碰撞预警等领域的应用情况;最后提出弯道检测应该建立三维车道线模型、注重发展多传感器融合技术,提高其适用性和鲁棒性.     

改进的有限时间最优预瞄横向控制器设计

提出了有限时间最优预瞄横向控制算法,根据高速公路车道保持系统实际控制要求,使用了同时考虑车辆当前偏差、预瞄点偏差和控制变量的有限时间二次型性能指标函数。运用最优跟踪算法并进行预瞄距离内曲率恒定的假设,使得控制器参数可以离线求解,保证了车辆控制的实时性。通过仿真及实车试验验证,该控制算法具有较好的跟踪效果。     

不同光照条件下直线型车道标识识别方法研究

为了解决不同光照条件下车道标识的识别，提出一种基于双标准可调模板关联技术的车道标识识别方法。该方法首先根据光照的变化采用不同的预处理技术对图像进行处理，然后利用基于统计的方法得到车道的初始化标识线，最后在以该书初始化标识线为尽准建立的感兴趣区域内利用双标准可调模板关联技术对初始化标识线进行矫正从而得到可靠的车道标识线参数。     

基于机器视觉的车道偏离警告系统研究综述

介绍了采用智能车辆道路系统对策的车道偏离避撞警告项目和近十几年来开发出的一些典型的基于视觉的车道偏离警告系统,并就这种系统所采用的警告标准进行了总结,最后对车道警告偏离系统研究的发展趋势进行了简述。