Quantitative risk assessment on the remote control ship navigation in inland waterway
To quantify the inland navigational risk of a remote control ship,a framework is proposed integrating uncertainty modeling and navigational,trial,including threeparts,i.e.,model construction,quantification,and verification.In the part of model construction,nodes of the model are navigational risk influencing factors of remote control ship identified from five aspects,i.e.,the environment,ship side,shore side,communication,and risk.An initial model is built and iteratively updated to construct a Bayesian Belief Network model for risk assessment on a remote ship in an inland river according to experience from experts and navigational trials.In the part of model quantification,a method is proposedto calculate Conditional Probability Tables for Bayesian reasoning,which can describe the linear or nonlinear dependencies between nodes with multiple states.The prior probabilities of some root nodes are derived from the navigational trials that are conducted in an inland river with multiple bridges.During the trials,the recorded items also include the situation of accidents or incidents and risk of navigation evaluated by a risk analyst onboard.In the part of model verification,the model is verified from three analyses,i.e.,scenarios,sensitivity,and comparison analysis.The results of this study are as follows:In the counted 40 cases in the trials,accidents,i.e.,contact or collision,occupy the largest percentage.During the trials,there are some emerging failure modes,i.e.,control conflict,software error,and signal loss.The built Bayesian Network(BN)model can effectively judge the risk levels in different scenarios.Furthermore,the BN model identified nodes that are important to the inland navigational risk of remote control ships.The results can not only provide a theoretical basis for inland ships facilitating the remote control operational mode but also show a methodology for the navigational safety of inland remote control ships.
safety engineeringwater transportationremote control shipinland navigationnavigational trialrisk assessmentBayesian Network(BN)
NETL
NSTL
万方数据
维普
