基于贝叶斯网络的集疏港道路畅通可靠度研究  

Study on the Unblocked Reliability of Port Collecting and Distributing Roads Based on Bayesian Network

作　　者：王文渊[1] 邹建强 彭云 周勇 

机构地区：[1]大连理工大学,海岸和近海工程国家重点实验室,辽宁大连116024

出　　处：《公路工程》2018年第1期123-126,164,共5页Highway Engineering

基　　金：国家自然科学基金(51309049)

摘　　要：随着港口吞吐量的持续增长,配套基础设施需要不断发展来满足港口日益增长的交通需求。集疏港道路作为港口客货集散的主要基础设施,准确度量其通行状况是合理规划港口集疏运系统的前提。为此,在综合考虑港口集疏运特点的基础上,构建了基于贝叶斯网络的集疏港道路畅通可靠度模型,以畅通可靠度作为评价道路交通状况优良的指标,结合贝叶斯网络结构学习和参数学习方法,分析并量化集疏港道路畅通可靠度。最后,以我国某港疏港高速5月13日7:00~20:00每15 min内道路畅通可靠度为例,对本文所构建的模型进行验证和对比分析。With the steady growth of seaport's cargo throughput,supporting infrastructure needs to be continuously developed to meet the increasing port traffic demands. As the main transportation infrastructure of port collecting and distributing system,how to measure the traffic condition accurately is the precondition of the port transportation system planning. Therefore,in this paper,after the consideration of the characteristics of port transportation,the unblocked reliability of port collecting and distributing road model based on Bayesian network is constructed. Then,the unblocked reliability is regarded as the evaluation index of road traffic condition. Besides,the unblocked reliability is analyzed and quantified after being combined with structure learning and parameter learning method of Bayesian network. Finally,this paper takes the traffic condition on a port expressway in May 13th 7: 00 ~ 20: 00 as an example to validate and analyze the conducted model.

关 键 词：港口 贝叶斯网络 集疏港道路 畅通可靠度 

分 类 号：U491[交通运输工程—交通运输规划与管理]