title: Safety modeling of suburban arterials in Shanghai, China.
abstract: As urbanization accelerates in Shanghai, land continues to develop along suburban arterials which results in more access points along the roadways and more congested suburban arterials; all these changes have led to deterioration in traffic safety. In-depth safety analysis is needed to understand the relationship between roadway geometric design, access features, traffic characteristics, and safety. This study examined 161 road segments (each between two adjacent signalized intersections) of eight suburban arterials in Shanghai. Information on signal spacing, geometric design, access features, traffic characteristics, and surrounding area types were collected. The effect of these factors on total crash occurrence was investigated. To account for the hierarchical data structure, hierarchical Bayesian models were developed for total crashes. To identify diverse effects on different crash injury severity, the total crashes were separated into minor injury and severe injury crashes. Bivariate hierarchical Bayesian models were developed for minor injury and severe injury to account for the correlation among different severity levels. The modeling results show that the density of signal spacing along arterials has a significant influence on minor injury, severe injury, and total crash frequencies. The non-uniform signal spacing has a significant impact on the occurrence of minor injury crashes. At the segment-level, higher frequencies of minor injury, severe injury, and total crashes tend to occur for the segments with curves, those with a higher density of access points, those with a higher percentage of heavy vehicles, and those in inner suburban areas. This study is useful for applications such as related engineering safety improvements and making access management policy.
authors.affiliation: School of Transportation Engineering, Tongji University, Shanghai 201804, China; Key Laboratory of Road and Traffic Engineering of the State Ministry of Education, Tongji University, Shanghai 201804, China. Electronic address: wangxs@tongji.edu.cn.
authors.forename: Xuesong
authors.initials: X
authors.lastname: Wang
authors.affiliation: School of Transportation Engineering, Tongji University, Shanghai 201804, China.
authors.forename: Yang
authors.initials: Y
authors.lastname: Song
authors.affiliation: School of Transportation Engineering, Tongji University, Shanghai 201804, China.
authors.forename: Rongjie
authors.initials: R
authors.lastname: Yu
authors.affiliation: Department of Civil & Environmental Engineering, Brigham Young University, 368 Clyde Building, Provo, UT 84602, USA.
authors.forename: Grant G
authors.initials: GG
authors.lastname: Schultz
mesh_terms: D000063:Accidents, Traffic / Q000517:prevention & control* / Q000706:statistics & numerical data; D001499:Bayes Theorem; D002681:China; D004779:Environment Design; D006801:Humans; D015233:Models, Statistical; D012307:Risk Factors; D012449:Safety / Q000706:statistics & numerical data*; D013383:Suburban Population; D015599:Trauma Severity Indices; D014947:Wounds and Injuries / Q000209:etiology / Q000517:prevention & control*
keywords: Bivariate Bayesian models; Hierarchical Bayesian model; Risk factor; Safety analysis; Suburban arterial