Video-based lane estimation and tracking for driver assistance: Survey, system, and evaluation
Video-based lane estimation and tracking for driver assistance: Survey, system, and evaluation
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DOI：
10.1109/tits.2006.869595
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发表时间：
2006-03-01
影响因子：
8.5
通讯作者：
Trivedi, MM
中科院分区：
文献类型：
--
作者：
McCall, JC;Trivedi, MM
监控驾驶员意图、警告驾驶员车道偏离或协助车辆引导的驾驶员辅助系统都在积极考虑之中。因此，必须严格审视这些系统的关键方面，其中之一就是车道位置跟踪。正是为了这些驾驶员辅助目标，推动了新型“基于视频的车道估计和跟踪”（VioLET）系统的开发。该系统采用可操纵滤波器设计，可实现稳健且准确的车道标记检测。可操纵滤波器提供了一种在不同照明和道路条件下检测圆形反射器标记、实线标记和分段线标记的有效方法。它们有助于为复杂的阴影、立交桥和隧道的照明变化以及路面变化提供鲁棒性。它们对于车道标记提取非常有效，因为通过仅计算三个可分离的卷积，我们就可以提取各种车道标记。通过结合视觉线索（车道标记和车道纹理）和车辆状态信息，曲率检测变得更加稳健。 VioLET 系统的实验设计和评估使用独特的仪表车辆在大型测试路径上的各种测试条件下使用多个定量指标进行展示。还提出了基于先前对人为因素应用的研究以及一天中不同时间、路况、天气和驾驶场景的广泛地面实况测试的指标选择的理由。为了设计 VioLET 系统，首先对车道检测研究的最新技术进行了最新的全面分析。在此过程中，对多种方法进行了比较，指出了方法之间的异同以及各种方法何时何地最有用。
Driver-assistance systems that monitor driver intent, warn drivers of lane departures, or assist in vehicle guidance are all being actively considered. It is therefore important to take a critical look at key aspects of these systems, one of which is lane-position tracking. It is for these driver-assistance objectives that motivate the development of the novel "video-based lane estimation and tracking" (VioLET) system. The system is designed using steerable filters for robust and accurate lane-marking detection. Steerable filters provide an efficient method for detecting circular-reflector markings, solid-line markings, and segmented-line markings under varying lighting and road conditions. They help in providing robustness to complex shadowing, lighting changes from overpasses and tunnels, and road-surface variations. They are efficient for lane-marking extraction because by computing only three separable convolutions, we can extract a wide variety of lane markings. Curvature detection is made more robust by incorporating both visual cues (lane markings and lane texture) and vehicle-state information. The experiment design and evaluation of the VioLET system is shown using multiple quantitative metrics over a wide variety of test conditions on a large test path using a unique instrumented vehicle. A justification for the choice of metrics based on a previous study with human-factors applications as well as extensive ground-truth testing from different times of day, road conditions, weather, and driving scenarios is also presented. In order to design the VioLET system, an up-to-date and comprehensive analysis of the current state of the art in lane-detection research was first performed. In doing so, a comparison of a wide variety of methods, pointing out the similarities and differences between methods as well as when and where various methods are most useful, is presented.