Corridor-level signalized intersection safety analysis in Shanghai, China using Bayesian hierarchical models

Xie, Kun; Wang, Xuesong; Huang, Hongwei; Chen, Xiaohong

doi:10.1016/j.aap.2012.10.003

Cited by 127 publications

(52 citation statements)

References 31 publications

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“…FCD can also be used in safety analysis. Xie et al (2013) used FCD to calculate arterial-level travel speed and introduced speed as an explanatory variable to investigate intersection safety in Shanghai. He found higher mean speeds along arterials were associated with increased intersection crashes Fig.…”

Section: Fcd Assumptions and Applicationsmentioning

confidence: 99%

“…In China's cities, the problem is especially severe with many urban arterials having unusual characteristics including short signal spacing, diverse cross-section configurations, mixed traffic flows, and high volumes (Xie et al, 2013). Previous studies showed roadway geometric and cross-section properties (e.g., segment length) and traffic flow characteristics (e.g., average annual daily traffic) to be important predictors of urban arterial safety (Greibe, 2003;EI-Basyouny and Sayed, 2009;Gomes, 2013).…”

Section: Introductionmentioning

confidence: 98%

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Safety modeling of urban arterials in Shanghai, China

Wang

Fan

Chen

et al. 2015

Accident Analysis & Prevention

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Section: Fcd Assumptions and Applicationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

Safety modeling of urban arterials in Shanghai, China

Wang

Fan

Chen

et al. 2015

Accident Analysis & Prevention

Self Cite

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“…The authors stated that the commonly used generalized linear regression models (GLMs) hold the assumption that the residuals from the model exhibit independence, which may not hold true under multi-level data structure. Xie et al (2013) conducted a corridor-level signalized intersection safety analysis for 195 intersections of 22 corridors in Shanghai, China. Corridorlevel data and intersection-level data were employed to construct a multi-level NB model.…”

Section: Introductionmentioning

confidence: 99%

Multi-level Bayesian safety analysis with unprocessed Automatic Vehicle Identification data for an urban expressway

Shi

Abdel-Aty

2016

Accident Analysis & Prevention

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“…Haque et al (2010) constructed Bayesian hierarchical models to examine motorcycle crashes at four-legged and "T" signalized intersections and found that the significant risk factors differed at the two intersections. In a similar study, Xie et al (2013) used Bayesian hierarchical negative binomial models to evaluate the safety of signalized intersections in Shanghai at the intersection and corridor levels.…”

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confidence: 99%

A two-stage bivariate logistic-Tobit model for the safety analysis of signalized intersections

Wong

Choi

2014

Analytic Methods in Accident Research

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a b s t r a c tCrash frequency and crash severity models have explored the factors that influence intersection safety. However, most of these models address the frequency and severity independently, and miss the correlations between crash frequency models at different crash severity levels. We develop a two-stage bivariate logistic-Tobit model of the crash severity and crash risk at different severity levels. The first stage uses a binary logistic model to determine the overall crash severity level. The second stage develops a bivariate Tobit model to simultaneously evaluate the risk of a crash resulting in a slight injury and the risk of a crash resulting in a kill or serious injury (KSI). The model uses 420 observations from 262 signalized intersections in the Hong Kong metropolitan area, integrated with information on the traffic flow, geometric road design, road environment, traffic control and any crashes that occurred during 2002 and 2003. The results obtained from the first-stage binary logistic model indicate that the overall crash severity level is significantly influenced by the annual average daily traffic and number of pedestrian crossings. The results obtained from the second-stage bivariate Tobit model indicate that the factor that significantly influences the numbers of both slight injury and KSI crashes is the proportion of commercial vehicles. The existence of four or more approaches, the reciprocal of the average turning radius and the presence of a turning pocket increase the likelihood of slight injury crashes. The average lane width and cycle time affect the likelihood of KSI crashes. A comparison with existing approaches suggests that the bivariate logistic-Tobit model provides a good statistical fit and offers an effective alternative method for evaluating the safety performance at signalized intersections.

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Corridor-level signalized intersection safety analysis in Shanghai, China using Bayesian hierarchical models

Cited by 127 publications

References 31 publications

Safety modeling of urban arterials in Shanghai, China

Safety modeling of urban arterials in Shanghai, China

Multi-level Bayesian safety analysis with unprocessed Automatic Vehicle Identification data for an urban expressway

A two-stage bivariate logistic-Tobit model for the safety analysis of signalized intersections

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