Multi feature fusion method for driving status of highway vehicles under rainfall conditions

Estimation of road vehicle driving status under rainfall conditions can achieve real-time vehicle monitoring and effectively reduce the incidence of traffic accidents. The paper proposes a multi feature fusion method for the driving status of road vehicles under rainfall conditions. Firstly, RFID, LiDAR, IMU sensors, and CMOS image sensors are used to collect road vehicle driving data under rainfall conditions, and the experimental data is denoised through member filtering. Then, through image processing, edge features, corner features, and texture features of road vehicle images are extracted. Finally, based on multiple state vector methods, data fusion of vehicle image features is completed to achieve accurate estimation of vehicle driving state. The experimental results show that the average accuracy of road vehicle driving state estimation based on multi feature fusion reaches 96.66%. This method can accurately estimate the driving status of road vehicles, provide a theoretical basis for reducing accidents and casualties on highways.