陕西省交通运输厅2018年度交通科研项目(18-31X); 长安大学中央高校基本科研业务费专项资金(300102249102, 300102240201)
随着我国道路运输行业的快速发展, “两客一危”车辆大幅度增长, 给道路出行和乘客的生命财产安全带来了极大的考验. 本文基于海量“两客一危”车辆行驶数据提出了多层模型的“两客一危”车辆行驶状态评价系统. 首先, 对行驶数据进行特征筛选、异常值清洗、归一化等处理. 然后, 在宏观和微观两个层面上分别使用聚类分析模型和动态阈值模型对车辆行驶数据进行分析. 最后通过将聚类分析的结果与动态阈值的分析结果相结合即可实现对车辆行驶状态以及驾驶员的驾驶习惯的综合评价. 研究结果表明, 本文提出的多层模型能够对车辆行程路况以及车辆驾驶员驾驶习惯进行较为准确的评估, 可为“两客一危”车辆的管理监督部门以及车辆运输企业提供合理的安全生产的科学依据和数据支持.
With the rapid development of road transportation industry in China, special transportation vehicles have increased significantly, which has brought great challenges to road travel and the safety of passengers’ lives and property. Based on massive special transportation vehicle driving data, this study proposes a multi-layer model of special transportation vehicle driving state evaluation system. Firstly, the data is processed for feature selection, outlier cleaning, and normalization. Then, the cluster analysis model and the dynamic threshold model are used to process vehicle driving data at the macro and micro layers, respectively. Finally, the results of cluster analysis and dynamic threshold analysis are combined to achieve a comprehensive evaluation of the vehicle’s driving status. The research results show that the multi-layer model proposed in this paper can make a more accurate assessment of the vehicle’s travel conditions and driving habits of vehicle drivers. It can provide reasonable scientific basis and data support for the management and supervision departments of special transportation vehicles and the vehicle transportation enterprises.