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SYSTEM AND METHOD FOR BAYESIAN INFERENCE IN THE CHARACTERIZATION AND PREDICTION OF VEHICLE TIRE WEAR

机译:贝叶斯推理的系统和方法,在车辆轮胎磨损的特征和预测中

摘要

A system and method are provided for Bayesian updating of distributions of factors that affect tire wear. Information is accumulated in data storage regarding probability distributions corresponding to each of a respective plurality of tire wear factors. Vehicle data comprising movement data and location data collected in association with a vehicle is transmitted from the vehicle to a centralized (e.g., cloud) computing device or network. At least one observation corresponding to one or more of the plurality of factors is generated based on the transmitted vehicle data. A Bayesian estimation is then generated of a tire wear status at a given time for at least one tire associated with the vehicle, based at least on the at least one generated observation and the stored information regarding probability distributions. The predictions accordingly carry a measure of uncertainty, and Bayesian inference can be used to update distributions based on the observations.
机译:为贝叶斯更新提供影响轮胎磨损的因素分布的系统和方法。 信息累积在关于对应于各个轮胎磨损因子中的每一个的概率分布的数据存储中。 包括与车辆相关联的移动数据和收集的位置数据的车辆数据从车辆发送到集中(例如云)计算设备或网络。 基于发送的车辆数据生成至少一个对应于多个因子中的一个或多个的观察。 然后基于至少一个生成的观察和存储的关于概率分布的至少一个生成的观察和存储的信息,将贝叶斯估计在给定时间的给定时间生成轮胎磨损状态,用于至少一个与车辆相关联的轮胎。 因此,预测携带不确定性的衡量标准,并且贝叶斯推理可用于基于观察来更新分布。

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