驾驶行为分析系统的开发与实现

Chien-Chung Wu
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引用次数: 0

摘要

交通事故的发生通常是由于驾驶员的不良驾驶行为。通过分析驾驶员的不良驾驶行为,可以帮助避免危险的驾驶状况,也可以减少交通事故。在这个系统中设计了一个系统,可以同时收集前方道路的图像,以及驾驶员在驾驶时的头部、眼睛和面部的实时图像。该系统主要包括三个子系统:(1)驾驶员视觉状态分析系统;(2)ECU信息捕获与解码系统;(3)驾驶行为分析系统。同时,通过将驾驶员视觉状态分析系统的信息与ECU信息采集与解码系统相结合,现有系统可以检测识别四种不良驾驶行为:(a)不打转向灯转弯;(b)转弯时不看后视镜;(c)分心驾驶;(d)疲劳驾驶。其中,“转弯时不打信号灯”和“转弯时不看后视镜”的正确率分别为89%和87%,分心驾驶和疲劳驾驶的正确率分别为82%和79%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The development and implementation of driving behavior analysis system
The occurrence of traffic accidents usually results from drivers’ bad driving behavior. By analyzing drivers’ bad driving behavior, it can help to avoid dangerous driving conditions, and also reduce traffic accidents. A system has been designed in this system that could simultaneously collect images of the roads ahead, and real-time images of the head, eyes, and face of the driver while driving. There were three subsystems constructed in this system: (1) Driver's visual state analysis system, (2) ECU message capturing and decoding system, (3) Driving behavior analysis system.Meanwhile, through integrating the information of the driver’s visual state analysis system with ECU message capturing and decoding system, the current system could detect and identify four types of bad driving behavior: (a) turning without flashing the turn signals, (b) Not looking in the rearview mirror when turning, (c) Distracted driving and (d) Fatigue driving. On top of that, the accuracy rates of "turning without flashing the signals" and "without looking in the rearview mirror when turning" were 89% and 87%, respectively, while the accuracy rates of distracted driving and fatigue driving were 82% and 79%, respectively.
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