Risk assessment of highway over-limit cargo transportation based on FTA and FBN

Highway over-limit cargo transportation significantly increases the probability of traffic accidents due to its complexity and potential dangers, requiring urgent control through scientific and effective risk assessment methods. In this paper, an fault tree model for over-limit cargo transportation is developed from four perspectives: human, machine, environment, and control, then mapped to a fuzzy Bayesian network, with triangular fuzzy numbers introduced to calculate prior probabilities. By using GeNIe software to construct and evaluate the fuzzy Bayesian network model, the main risk factors and their degrees of influence are identified through two-way reasoning, and targeted risk management countermeasures are proposed. This study not only enriches the risk assessment methods for highway over-limit cargo transportation, but also provides a scientific basis for risk control in practical transportation processes.