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An object oriented Bayesian network approach for unsafe driving maneuvers prevention system

机译:面向对象的贝叶斯网络方法用于不安全驾驶操纵预防系统

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As the main contributor to the traffic accidents, unsafe driving maneuvers have taken attentions from automobile industries. Although driving feedback systems have been developed in effort of dangerous driving reduction, it lacks of drivers awareness development. Therefore, those systems are not preventive in nature. To cover this weakness, this paper presents an approach to develop drivers awareness to prevent dangerous driving maneuvers. The approach uses Object-Oriented Bayesian Network to model hazardous situations. The result of the model can truthfully reflect a driving environment based upon situation analysis, data generated from sensors, and maneuvers detectors. In addition, it also alerts drivers when a driving situation that has high probability to cause unsafe maneuver to be detected. This model then is used to design a system, which can raise drivers awareness and prevent unsafe driving maneuvers.
机译:作为交通事故的主要起因,不安全的驾驶行为引起了汽车行业的关注。尽管已经开发了用于减少危险驾驶的驾驶反馈系统,但是缺乏驾驶员意识的开发。因此,这些系统本质上不是预防性的。为了弥补这一弱点,本文提出了一种提高驾驶员意识以防止危险驾驶行为的方法。该方法使用面向对象的贝叶斯网络对危险情况进行建模。该模型的结果可以根据情况分析,传感器生成的数据和操纵检测器真实地反映出驾驶环境。此外,当检测到极有可能导致不安全操纵的驾驶状况时,它还会警告驾驶员。然后,此模型用于设计系统,该系统可以提高驾驶员的意识并防止不安全的驾驶操作。

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