基于CAN数据的渣土车驾驶行为分析

Driving Behavior Analysis of Muck Truck Based on CAN Data

渣土运输行业普遍存在着一些管理难的现象,其主要表现在管理者无法有效地管控车辆的运行、安全等情况;针对渣土车辆管控的要求,着力于分析渣土车驾驶员的驾驶行为,以达到提高渣土车驾驶员的驾驶素质、规范其日常驾驶行为和行车安全意识,减少安全事故发生的目的;研究通过对渣土车辆的北斗定位数据和CAN数据进行采集与解析后;首先,利用K-means聚类算法对渣土车驾驶员的驾驶倾向性行为进行分析识别,帮助管理者在管理车辆的同时,有效地监督驾驶员的驾驶行为规范;其次,构建司机驾驶行为评分模型,使用熵权层次分析法来确定每个指标的权重,进而由权重来制定指标分值;最后,对渣土车驾驶员进行综合评分,实现对渣土车驾驶员的驾驶行为分析;研究对渣土车驾驶行为的分析,有利于驾驶员更有针对性地改善其驾驶行为,提高驾驶安全,减少事故。

There are some difficult management problems in muck transport industry,which are mainly manifested in the inability of managers to effectively control the operation and safety of vehicles.Aimed at the requirements of muck vehicle control,the driving behavior of muck vehicle drivers is mainly analyzed to improve the driving quality of muck vehicle drivers,standardize their daily driving behavior and driving safety awareness,and reduce the occurrence of safety accidents.After collecting and analyzing the Beidou positioning data and CAN data of the muck vehicle;Firstly,K-means clustering algorithm is used to analyze and identify the driving propensity behavior of muck truck drivers,which helps managers to effectively supervise drivers'driving behavior norms while managing vehicles.Secondly,the scoring model of driver's driving behavior is constructed,and the weight of each index is determined by the entropy weight analytic hierarchy process,and then the index score is determined by the weight.Finally,a comprehensive score is given to the drivers of the muck truck to realize the analysis of the driving behavior of muck truck drivers.The analysis of muck truck driving behavior is conducive to the driver's more effective improvement of their driving behavior,which improves driving safety and reduces accidents.