【作者】 聂一鸣；

【导师】 贺汉根；

【作者基本信息】 国防科学技术大学 ， 控制科学与工程， 2012， 博士

【摘要】 在国家自然科学基金重点项目“高速公路车辆智能驾驶中的关键科学问题研究”（90820302）和“未知环境中移动机器人导航控制的理论方法研究”（60234030）的支持下，本文研究了自主驾驶汽车在高速公路环境下的视觉感知算法。高速公路正常交通环境下，自主驾驶汽车在自主驾驶及汇入车流的过程中，必须稳定可靠地感知前方的车道形状和车路关系，这是安全行驶的基本的保证。本文以红旗HQ3自主驾驶汽车的道路感知系统为背景，针对车道线不可靠等复杂情况，研究了车道感知问题及相关算法，取得的研究成果和创新点如下：1、提出高速公路设计规范与人类视觉感知规律的一致性，并据此提出面向复杂路况的视觉感知系统及算法，能够有效地完成在车道线模糊、遮挡、缺失等复杂情况下的视觉感知；2、提出驾驶员道路注视点始终为道路的“切线点”，并利用平行线的消失点坐标信息准确获得前方道路的曲率；3、将场景分为可通行区域、不可通行区域和天空，选取颜色、纹理、位置和透视关系这四类特征参数，并利用超像素思想对图像相似区域进行分割，大大减少参与运算的数据量，提高算法效率；4、建立了一种基于道路设计和车辆运动学的三维道路曲率模型，分别分析与高速公路起伏相关的纵切线曲率以及与公路转弯相关的水平曲率，算法实现了对车辆前方道路起伏和弯曲信息的实时估计，能减少由曲线模型引起的误差；5、提出用序列图像，根据“似动现象”原理，算法有效解决了车辆运动轨迹估计和高速公路出口检测问题。上述成果是红旗HQ3自主驾驶汽车道路感知系统的核心技术之一，能在车道线模糊、被遮挡甚至缺失等复杂情况下，稳定可靠地给出车道信息和车路关系信息，并检测高速公路出口。此系统感知周期小于30毫秒，能够满足实时要求，使自主驾驶汽车在无全球定位系统和惯性导航设备的条件下，以时速110千米成功汇入车流行驶，为成功完成我国首次在正常交通状况下长距离（286千米）高速公路自主驾驶实验提供了可靠的车道信息保障。更多还原

【Abstract】 Under the support of the emphasis projects from the Natural Science Foundation ofChina (NSFC):‘Research on key scientific problems in intelligent driving of highwayvehicles’(90820302) and ‘Research on theories and methods for navigation control ofmobile robots in unknown environments’(60234030), this thesis investigates the VisionPerception problems that Autonomous Land Vehicle (ALV) merges into traffic flow onHighway Roads.In the normal traffic environment on highway, to drive and merge into traffic flowsafely, the Autonomous Land Vehicle should satisfy the basic condition which is todetect reliably the road shape and the space relation between vehicle and road. Thevision perception system of the autonomous Hongqi HQ3is designed for some complexsituations such as unreliable lane marking lines. The main contributions and innovationsof this thesis are as follows:1. The consistency between the highway design specifications and the laws ofhuman visual perception has been proposed. The road details imply lots of informationfor visual perception of the autonomous driving system. Thus visual perception systemhas been proposed for complex road environment, for example, when the lane markinglines are faded, obscured, or missed.2. The mathematical meaning of “tangent point” focused on by drivers is to obtainthe curvature of the road. Using the coordinates of the Vanishing Point of the parallellines, this thesis estimates the curvature information of the road.3. The scene is classified into drivable terrain, vertical obstacle and sky. Four kindsof feature parameters are chosen, i.e., color, texture, position and perspective relation.The super-pixel method is adopted to segment the image into areas, greatly reducing thedata amount and improving the computing efficiency.4. The3D road curvature model is established based on road design and vehiclekinematics, and the profile curvature relating to the road undulation and the planecurvature relating to the road bending are analyzed, which can estimate the undulationand bending information of road in real time, and reduce the errors caused by the curvemodel.5. Using a serial of images and based the principle of “apparent movementphenomenon”, the problem of the vehicle trajectory estimation and the highway exitdetection has been solved effectively.The above results are core technologies of the lane perception system of theHongqi HQ3autonomous vehicle, they can reliably provide lane information, the spacerelationship between vehicle and road and the highway exits under the complex situations, such as the lane marking lines are faded, obscured, or missed. The processingcycle of this system is less than30milliseconds, which has satisfied requirement ofreal-time. This system can let an autonomous vehicle to merge into traffic flow at thespeed of110km/h on highway roads without Global Position System and inertialnavigation equipment. And it has provided reliable lane information guarantee for thefirst successful autonomous drive experiment on highway road with long-distance (286kilometers) under normal traffic conditions in China.更多还原