Research on the Safety Assessment of Heavy Trucks in Transit Based on the Information Entropy-based Weighting and Bi-level Belief Rule Base

Abstract

Heavy trucks have the characteristics of super-length, super-width, super-height and overweight, which are prone to traffic accidents and result in heavy losses. This paper aims to detect various safety hazards and achieve the safety assessment of heavy vehicles in transit by monitoring vehicle parameters. A safety assessment model which combines the information entropy-based weighting method (IEBW) and the bi-level Belief Rule Base (BRB) is proposed for heavy trucks' safety assessment. First, the information entropy-based weighting method is used to select key features which can significantly represent the actual safety status of heavy trucks. Second, the bi-level BRB is used to accurately and timely characterize and predict the heavy trucks' safety status. Meanwhile, the bi-level BRB can greatly reduce the number of BRB rules which makes it a possible to construct a multi-attribute BRB more conveniently. The proposed model is applied to the safety assessment of heavy trucks. Experimental results show that the proposed model can fuse subjective and uncertain information. Meanwhile, the new method is faster, more accurate and more practical.