On the quantitative assessment of the Lane Departure Warning System based on road scenes simulator

Yan Wang, Jing Fu, X. An, Jian Li, Er-Ke Shang
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Abstract

Vision-based Lane Departure Warning Systems (LDWSs) have been studied for over two decays. This paper presents an Objective Evaluation Platform of LDWS (OEP-LDWS). It provides simulated road scenes with the possible data as ground truth, such as the vehicle to road relation, vehicle's states and the real Time-to-Lane-Crossing (TLC) value. In our OEP-LDWS, different kinds of driving maneuver can be simulated with the road model, the vehicle model, the camera model and a vehicle trajectory generator. At the same time, the road scene that may be captured by the on board camera can be generated. Using our OEP-LDWS, one can not only evaluate the warning performance of the LDWS quantitatively, but also assess the whole performance under varying circumstance, such as different road surfaces, different road curvatures and so on. Actually, those assessments can hardly be evaluated through real driving test, and are very important aspects for a LDWS, such as warning strategy selection, system tailor. Using our OEP-LDWS, we assess our LDWS with three different warning strategies, and reach the conclusion that the PTLC is the best under the low false warning criterion.
基于道路场景模拟器的车道偏离预警系统定量评估研究
基于视觉的车道偏离预警系统(LDWSs)已经研究了二十多年。本文提出了一种LDWS客观评价平台(OEP-LDWS)。它提供了模拟道路场景的可能的数据作为地面真实,如车辆与道路的关系,车辆的状态和实时到车道交叉口(TLC)值。在我们的OEP-LDWS中,可以使用道路模型、车辆模型、摄像机模型和车辆轨迹生成器来模拟不同类型的驾驶机动。同时,可以生成车载摄像机可能捕捉到的道路场景。利用我们的OEP-LDWS,不仅可以定量评价LDWS的预警性能,还可以对不同路面、不同曲率等不同情况下的预警性能进行综合评价。实际上,这些评估很难通过实际驾驶测试来评估,而这些评估是LDWS非常重要的方面,如预警策略的选择、系统的定制。利用我们的OEP-LDWS,我们用三种不同的预警策略来评估我们的LDWS,得出PTLC在低误报准则下是最好的结论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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