Department of Pharmaceutical and Biomedical Sciences, University of Salerno, Via Ponte Don Melillo, 84084 Fisciano, Italy.
Comput Math Methods Med. 2012;2012:868410. doi: 10.1155/2012/868410. Epub 2012 Aug 30.
The search for safe vehicles is increasing with both diffusion of high traffic density over the world and availability of new technologies providing sophisticated tools previously impossible to realize. Design and development of the necessary devices may be based on simulation tests that reduce cost allowing trials in many directions. A proper choice of the arrangement of the drive simulators, as much as of the parameters to be monitored, is of basic importance as they can address the design of devices somehow responsible for the drivers safety or, even their lives. This system setup, consisting of a free car simulator equipped with a monitoring system, collects in a nonintrusive way data of the car lateral position within the road lane and of its first derivative. Based on these measured parameters, the system is able to detect symptoms of drowsiness and sleepiness. The analysis is realized by a fuzzy inferential process that provides an immediate warning signal as soon as drowsiness is detected with a high level of certainty. Enhancement of reliability and minimisation of the false alarm rate are obtained by operating continuous comparison between learned driver typical modalities of operation on the control command of the vehicle the pattern recorded.
随着世界上交通密度的扩散和提供复杂工具的新技术的出现,对安全车辆的搜索正在增加。必要设备的设计和开发可以基于模拟测试,这些测试降低了成本,允许在许多方向上进行试验。驱动模拟器的布置以及要监控的参数的正确选择非常重要,因为它们可以在某种程度上解决负责驾驶员安全甚至生命的设备的设计问题。该系统设置由配备监控系统的自由汽车模拟器组成,以非侵入方式收集汽车在道路车道内的横向位置及其一阶导数的数据。基于这些测量参数,系统能够检测到困倦和嗜睡的症状。分析是通过模糊推理过程实现的,该过程一旦检测到困倦,就会立即发出高度确定的警报信号。通过在记录的模式和车辆控制命令之间进行连续比较,学习驾驶员的典型操作模式,提高了可靠性并降低了误报率。