交通信息与安全Issue(1)：64-70,7.DOI:10.3963/j.issn 1674-4861.2016.01.001
城市主干道安全建模与影响因素分析∗
Modeling Safety of Urban Arterials and Identification of Impact Factors
摘要
Abstract
Arterial roads are the framework of urban road network,where the crash occurs frequently due to com-plex traffic environment.It is necessary to conduct corresponding safety analysis,in order to propose constructive coun-termeasures.Geometric features,land use,traffic volume and average speed are gathered at a total of 1 76 road segments from 18 arterial roads in Shanghai.Average segment speed is calculated from floating car data (FCD),which solved the problems related to speed data collection with sensors installed on fixed locations.Considering correlations among seg-ments along an arterial roads,a set of Bayesian hierarchical Poisson log-normal models are developed.The Full Bayesian Method is used for parameter estimation and different prior distributions are tested.Crash features vary depending on time,so the models for peak and off-peak hours are developed separately.Results indicate that hierarchical models im-prove the goodness-of-fit of the data because deviance information criterion (DIC)values of hierarchical models are signifi-cantly less than maximum likelihood estimation (MLE)prior models.The reliability of parameter estimation can be im-proved by MLE prior.The standard deviations of parameters of the MLE prior models are less than those of non-informa-tive models.Along arterial roads,the longer the segment length,the more crashes.At the segment level,geometric fea-tures and land use are substantially associated with crash frequencies.Higher traffic volume is associated with increased crash frequencies especially during peak hours.Average segment speed contributes to increasing crash occurrence during peak hours.关键词
交通安全/城市主干道/安全模型/影响因素/贝叶斯分层模型/极大似然先验/浮动车数据Key words
traffic safety/urban arterial/safety models/effect factors/Bayesian hierarchical models/maximum likelihood estimation prior/floating car data (FCD)分类
交通工程引用本文复制引用
樊天翔,王雪松..城市主干道安全建模与影响因素分析∗[J].交通信息与安全,2016,(1):64-70,7.基金项目
国家自然科学基金项目(51138003)、上海市科学技术委员会项目(15DZ1204800)资助 （51138003）
