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Reliability-Based Assessment of the Truck Safe Following Distance Considering Multiple Influencing Factors

机译:考虑多个影响因素的卡车安全跟随距离的可靠性评估

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For heavy trucks, reasonable following distance is an important factor to ensure driving safety. The truck onboard monitoring system is to analyze the crash risk, provide real-time feedback to the driver and remind the drivers. The reliability theory has been used into a vehicle-dynamics-based truck safe following distance model. Two of the model parameters, the friction coefficient of pavement and response time of drivers, have been chosen as the random variables in the reliability method. Then, the first order and second moment (FORM) method has been used to calculate the real-time reliability and failure probability of truck following safety in an 80-second period of truck field test. Moreover, the simulation-based Monte Carlo method has been used to verify the accuracy of the FORM model, which led to a similar result. The results showed that the reliability-based method can give probabilistic analysis results, which has better applicability to the intelligent truck onboard monitoring system compared with traditional safe following distance models which have only two deterministic outcomes: safe or crash.
机译:对于重型卡车,合理的跟随距离是确保行驶安全的重要因素。卡车车载监控系统将分析碰撞风险,向驾驶员提供实时反馈并提醒驾驶员。可靠性理论已被用于基于车辆动力学的卡车安全跟随距离模型中。在可靠性方法中,选择了两个模型参数,即路面的摩擦系数和驾驶员的响应时间作为随机变量。然后,使用一阶矩和第二矩(FORM)方法来计算卡车在80秒的卡车现场测试期间的实时可靠性和卡车跟随安全性的故障概率。此外,基于仿真的蒙特卡洛方法已被用来验证FORM模型的准确性,这导致了相似的结果。结果表明,基于可靠性的方法可以给出概率分析结果,与仅具有两个确定性结果的传统安全跟随距离模型相比,该方法对智能卡车车载监控系统具有更好的适用性:安全或碰撞。

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