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农村公路典型路段事故风险评价方法
引用本文:胡思涛,朱艳茹,项乔君.农村公路典型路段事故风险评价方法[J].淮阴工学院学报,2014(5):30-35.
作者姓名:胡思涛  朱艳茹  项乔君
作者单位:1. 淮阴工学院交通工程学院,江苏淮安223003; 东南大学交通学院,南京210096
2. 淮阴工学院交通工程学院,江苏淮安,223003
3. 东南大学交通学院,南京,210096
基金项目:交通部西部交通建设科技项目(20113182231230);江苏省大学生创新训练计划项目
摘    要:农村公路急弯、陡坡、路侧险要等典型路段往往是事故易发多发路段。在现阶段农村公路安保工程资金有限的情况下,需对既有典型路段的事故风险进行定量评价和排序,为隐患路段的排查和安保工程分期实施提供依据。在现有研究成果的基础上,构建典型路段事故风险评价指标体系,提出一种基于贝叶斯网络的农村公路典型路段事故风险评价方法。该方法能有效集结专家知识和经验定量评价典型路段(包括单一路段和组合路段)的事故风险,并可以随着数据的更新不断完善模型。在农村公路事故资料相对缺乏的情况下,该方法具有较强的实用性。

关 键 词:农村公路  贝叶斯网络  典型路段  事故风险评价

Crash Risk As sessment Method for Typical Sections of Rural Roads Using Bayesian Networks
HU Si-tao,ZHU Yan-ru,XIANG Qiao-jun.Crash Risk As sessment Method for Typical Sections of Rural Roads Using Bayesian Networks[J].Journal of Huaiyin Institute of Technology,2014(5):30-35.
Authors:HU Si-tao  ZHU Yan-ru  XIANG Qiao-jun
Affiliation:HU Si-tao;ZHU Yan-ru;XIANG Qiao-jun;Faculty of Transportation Engineering,Huaiyin Institute of Technology;School of Transportation,Southeast University;
Abstract:Typical sections such as sharp turns, steep slopes and dangerous roadsides of the rural roads tend to be crash prone sections.In the case of limited budget for highway safety enhancement project,in order to identi-fy potential high-risk sections and provide the basis for implement in phases of safety enhancement project, it is necessary to evaluate quantitatively and sort the crash risk of typical sections.On the basis of related resear-ches, a crash risk assessment index system for typical sections has been constructed.And a crash risk assess-ment method for typical sections of rural roads using Bayesian networks was proposed.It is effective to evaluate the crash risk of typical sections ( including single sections and combination sections ) by combining expert knowledge and experience with the proposed method.It was also noted that the proposed model could be con-stantly improved as related data updated.The proposed method showed promise to be used for crash risk assess-ment especially when lack of accident relative information.
Keywords:rural roads  Bayesian networks  typical sections  crash risk assessment
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