同济大学学报（自然科学版）2013，Vol.41Issue(9)：1378-1383,6.DOI:10.3969/j.issn.0253-374x.2013.09.016
考虑空间自相关的贝叶斯事故预测模型
Bayesian Crash Prediction Model Based on a Consideration of Spatial Autocorrelation
摘要
Abstract
A regional safety prediction model was proposed based on the data from Hillsborough County,Florida,USA.By regionalizing the county into 200,500 and 700 traffic safety analysis zones,we developed a Bayesian spatial model with consideration of spatial autocorrelation to relate crash rate to zonal factors including road network,trip generation and so on.According to the model results,the relationships were investigated between traffic safety and zone-level factors,as well as the effects of varied zoning schemes on the estimation of factor effects.Results show that compared with the traditional Poisson model and Poisson-lognormal model,the Bayesian spatial model has a better model-fitting; the greater the total zone number is,the higher the spatial effects are; the factor estimates are robust given a specific zoning scheme; the most significant factor affecting zonal safety is the total road length with speed limit over 56 krn · h-1.关键词
事故预测模型/贝叶斯方法/交通安全分析小区/空间分析Key words
crash prediction model/ Bayesian approach/traffic safety analysis zone/ spatial analysis分类
交通工程引用本文复制引用
黄合来,邓雪,许鹏鹏..考虑空间自相关的贝叶斯事故预测模型[J].同济大学学报（自然科学版）,2013,41(9):1378-1383,6.基金项目
国家自然科学基金(51108465) （51108465）
中央高校基本科研业务费专项资金(2012ZZTS085) （2012ZZTS085）
