Real-time risk analysis of road tanker containing flammable liquid based on fuzzy Bayesian network

Abstract

The risk of road transportation of flammable liquid is of great uncertainty due to the time-varying conditions of the passing locations and the environment, which leads to challenging risk analysis. In this work, a real-time risk analysis method for road tanker transportation based on the fuzzy Bayesian network (FBN) is proposed. The bow-tie model is first employed to identify hazards in flammable liquid road transportation systems and shows risk evolution. The framework of the Bayesian network (BN) is then determined accordingly. In the case that the historical statistics of accidents are limited, a probabilistic estimation model that combines expert judgment and fuzzy set theory is established to determine the prior probabilities and the conditional probabilities of the BN nodes. Case studies of typical road tanker transportation accidents were carried out to show the risk level variation with both the internal and external conditions at different moments. Sensitivities of the parent nodes were analyzed, and the critical factors leading to accidents were identified. Studies show that this method can dynamically characterize the changes in both the probabilities and the consequence levels of road tanker transport accidents. Based on the vehicle’s GPS data and the local environment, the proposed method can provide an estimation of the real-time risk for road tankers.