Application of extended Dempster–Shafer theory of evidence in accident probability estimation for dangerous goods transportation

Abstract

=Transportation of dangerous goods (DGs) is generally associated with significant levels of risk. In the context of DG transportation, risk refers to the likelihood of incurring the undesirable consequences of a possible accident. Since the probability of an accident in a link of a route might depend on a variety of factors, it is necessary to find a way to combine the pieces of evidence/probabilities to estimate the composite probability for the link. Instead of using the Bayesian approach, commonly used in the literature, which requires decision-makers to estimate prior and conditional probabilities and cannot differentiate uncertainty from ignorance, this paper presents a novel approach based on the extended Dempster–Shafer theory of evidence by constructing an adaptive robust combination rule to estimate the accident probability under conflicting evidence. A case study is carried out for the transportation of liquefied petroleum gas in the road network of Hong Kong. Experimental results demonstrate the efficacy of the proposed approach.