基于贝叶斯网络的路侧安全评价方法

首先阐述了路侧安全评价对于减少公路交通事故的重要意义，在对国内外相关研究进行分析和比较的基础上，构建了一个用于路侧安全性评价的指标体系。随后利用贝叶斯网络所具有的表达不确定性知识和进行不确定性知识推理的能力，提出了一种基于贝叶斯网络的安全评价模型。该模型能够处理复杂的逻辑关系，很好地表达变量间的不确定性关系，可以灵活方便地对系统进行预测及诊断分析，有效地处理专家意见不一致的情形，并能够在某些专家意见缺失的情况下得到合理的结果。最后将此方法应用于评估某路侧的安全等级，结果表明此方法是合理有效的。

A Roadside Safety Assessment Method Based on Bayesian Network

Roadside safety assessment is necessary for reducing the traffic accidents.An index system for roadside safety assessment was presented according to the studies of home and abroad.In addition,a method for roadside safety measurement using Bayesian network(BN),which has excellent abilities of expressing and reasoning knowledge under uncertain environment,was proposed to construct the safety assessment model.The assessment model is able to deal with complicated logic relationship as well as the different opinions of experts.The output of the safety assessment model can be used to predict and diagnose different safety conditions.The model was validated by application to safety assessment of a roadside,and the results show that the method is effective and reasonable.