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.