基于马尔科夫过程的驾驶疲劳监测装置效能分析

    Performance Analysis of Driver Fatigue Monitoring Devices Based on Markov Process

    • 摘要: 提出一种驾驶疲劳监测装置效能的定量评估模型, 用于分析该装置对降低交通事故发生率的作用.首先运用连续马尔科夫过程为工具, 建立了装有驾驶疲劳监测装置的车辆事故发生过程的动态模型, 并用系统平均正常工作时间(MTTF)来衡量驾驶疲劳监测装置的效能;随后对模型进行了求解, 得到了系统平均正常工作时间与驾驶疲劳监测装置各项性能指标之间的关系并进行分析;最后对驾驶疲劳监测装置的使用与发展提出了若干建议.本模型经过参数标定后可直接用于具体问题的分析.

       

      Abstract: While existing studies are mostly concerned about driver fatigue recognition algorithm, this paper proposes a quantitative model for performance analysis of driver fatigue monitoring devices, which is suitable for analyzing the role of the device in traffic accidents prevention. First, we constructed a model of the accident process of the vehicle equipped with a driver fatigue monitoring device based on continuous Markov Process. The Mean Time to Failure (MTTF) was taken as the measurement of the devices' performance. Then we obtained the relationship between MTTF and the performance indicators of driver fatigue monitoring devices by solving the model. Finally, several suggestions were presented for the application and development of driver fatigue monitoring devices. This model can be applied to analyze real problems directly after parameter calibration.

       

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