标题: 以车道线侦测为基础之驾驶人昏睡警示安全系统
A Lane-Based Drowiness Estimation System for Safety Driving
作者: 林立倬
Li-Juo Lin
林进灯
Chin-Teng Lin
电控工程研究所
关键字: 车道;鱼眼;昏睡;Lane;Fish-eye;Drowsiness
公开日期: 2006
摘要: 近年来,由于车辆数目的快速成长,造成交通事故问题日益严重。在台湾,每年有超过两千五百人在车祸中丧生。而根据交通部的资料,过去的四年中,每年至少有八万多件的车祸事故发生。这种情况下促成智慧型运输系统(Intelligent transportation system, ITS)相关研究的发展越来越受到关注。而大部分车祸发生的原因主要由于驾驶人本身的分心、不注意车况、疲劳驾驶等不适当驾驶行为所引起。因此,为了能尽量避免驾驶者身处于此危险状态,我们针对车辆后照镜旁的侧边影像资讯,开发一套以智慧型视觉技术为基础的车道侦测及偏移系统,以确保驾驶人行驶的安全性。
在车道线侦测部分,为了提高车辆侧边的视角范围,我们将一支鱼眼(Fish-Eye)摄影机架设在后照镜下方,并利用车体资讯在连续影像中固定的特性,自动选取路面范围,而不需要事先得知摄影机架设的相关资讯。为了可适用于全天候的光线变化条件,我们同时处理空间及时间轴上的影像资讯,使此系统在白天及夜间人眼可视车道范围内,都能获得清晰的车道边界资讯。另外本论文提出一套分段直线搜寻模组来连结车道线的轨迹,以提升整个搜寻速度,并克服鱼眼镜头失真的问题。
在车道偏移判断的部分,本论文利用先前侦测的车道侧向位置,及TLC(Time to Lane Crossing)的瞬时资讯,规划车道偏移警示的触发条件。另外建立一个可以即时更新的车道线位移稳定区间,来模拟驾驶人在直线道路行驶时和车道线保持习惯性距离的特性。最后我们和交通大学脑科学中心(Brain Research Center, NCTU)合作,取得其在虚拟实境动态模拟驾驶系统的环境下,针对驾驶人昏睡状态预测的相关数据,套用在实际驾驶的影像内容中,使本系统除了估测车道偏移的外在因素外,也可针对驾驶人本身的精神状况作更进一步的分析,以提升本系统的安全性及可靠性。
本论文发展的车道侦测辅助系统在1.83GHz的PC平台上平均可达超过15fps的执行结果。测试影像内容为在高速公路的实际驾驶环境,并在白天及夜间范围内都维持稳定的侦测结果。
As the high growth of population of vehicles, the traffic accidents are becoming more and more serious in recent years. In Taiwan, more than two thousand and five hundred people are died in traffic accidents every year. For each of last four yours, the number of traffic accidents is at least eighty thousand according the statistics of the Ministry of Transportation and Communications (MOTC, R.O.C.). In this situation, a lot of researches about the intelligent transportation system (ITS) have been paid more and more attention to the researches of related fields. Most occurrence of the car accidents results from the distraction, inattention for the adjacent cars, and driving fatigue of the driver. As a result, to avoid the driver being in danger as much as possible, an intelligent vision-based system focused on image contents of lateral-view camera setting under the rear-view mirror on vehicle is developed about lane detection and lane departure warning in this study.
In this thesis of lane detection, a fish-eye camera is located on the vicinity of the rear-view mirror to increase the range of lateral-view angle. Furthermore, we make use of the invariant of image for car body fixed in consecutive image sequences to extract the ROI (region of interest) containing the road surface without realizing the intrinsic and extrinsic parameters of camera in advance. To make this algorithm suitable for various light conditions all day, the information of image in spatial and temporal domain must be simultaneously processed so that the lane boundary keeps distinct whether people have seen in the day or night environment. On the other hand, a piece-wise line searching model proposed in this paper is to connect the trajectory of lane and to reduce the computation load and to overcome the fish-eye lens distortion.
In the thesis of lane departure warning, the instantaneous information of the lateral position from the result of lane detection and the TLC (time to lane crossing) can be regarded as the warning triggers for the alarms of lane departure. Then, a stable-driving region with real-time update mechanism is constructed to simulate the straight-road driving habit of different drivers which get used to keep approximately the same distance between the vehicle and lane markers. Eventually, by cooperated with the BRC (Brain Research Center, NCTU), we utilize the statistics about drowsiness estimation of the drivers in Virtual-Reality (VR) dynamic driving simulator to implement in the video contents for realistic driving. Therefore, this mechanism can be not only estimated the external factors such as departure of lane boundary but the internal ones such as the conscious analysis of the driver with higher reliability and safety.
The lane detection and departure warning system proposed in this paper has been successfully evaluated on the PC platform of 1.83-GHz CPU with the average frame-rate is up to 15fps. Moreover, this algorithm can be maintained stable results whether in the day or night environment of the realistic driving on highway.
URI: http://140.113.39.130/cdrfb3/record/nctu/#GT009412606
http://hdl.handle.net/11536/80737
显示于类别:Thesis


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