Analysis of Crash Rates at Freeway Diverge Areas using Bayesian Tobit Modeling Framework

Guo, Yanyong; Li, Zhibin; Sayed, Tarek

doi:10.1177/0361198119837219

Cited by 17 publications

(12 citation statements)

References 52 publications

(129 reference statements)

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“…The random parameters multivariate Tobit model was used by Guo et al to evaluate the risk factors on crash rates of different collision types [15]. On the same note, Guo and Sayed a study using Four candidate Tobit models to evaluate the impact of various risk factors on crash rates at freeway diverge areas [16]. By using random parameters multinomial logit regression, Guo et al identified significant factors contributing to the severity of e-bike collisions [17].…”

Section: Literature Reviewmentioning

confidence: 99%

Crash severity analysis of nighttime and daytime highway work zone crashes

Zhang

Hassan

2019

PLoS ONE

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Introduction Egypt’s National Road Project is a large infrastructure project which presently aims to upgrade 2500 kilometers of road networks as well as construct 4000 kilometers of new roads to meet today’s need. This leads to an increase in the number of work zones on highways and therefore a rise in hazardous traffic conditions. This is why highways agencies are shifting towards night construction in order to reduce the adverse traffic impacts on the public. Although many studies have investigated work zone crashes, only a few studies provide comparative analysis of the difference between nighttime and daytime work zone crashes. Methods Data from Egyptian long-term highway work zone projects between 2010 and 2016 are studied with respect to the difference in injury severity between nighttime and daytime crashes by using separate mixed logit models. Results The results indicate that significant differences exist between factors contributing to injury severity. Four variables are found significant only in the nighttime model and four other variables significant in the daytime model. The results show that older and male drivers, the number of lane closures, sidewise crashes, and rainy weather have opposite effects on injury severity in nighttime and daytime crashes. The findings presented in this paper could serve as an aid for transportation agencies in development of efficient measures to improve safety in work zones.

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Section: Literature Reviewmentioning

confidence: 99%

Crash severity analysis of nighttime and daytime highway work zone crashes

Zhang

Hassan

2019

PLoS ONE

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“…Ignoring this inherent variability could lead to incorrect inferences and may lead to a bias in parameter estimates. To address this, researchers have proposed developing random parameter Tobit models to analyze collision rates and to overcome this limitation [30,[35][36][37][38][39][40][41]. More recent studies have also attempted to account for the correlation between collision severities by developing multivariate Tobit models.…”

Section: Methodsmentioning

confidence: 99%

Using Bayesian Tobit Models to Understand the Impact of Mobile Automated Enforcement on Collision and Crime Rates

Ibrahim¹,

Sayed

2021

Sustainability

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The Data Driven Approaches to Crime and Traffic Safety approach identifies opportunities where a single enforcement deployment can achieve multiple objectives: reduce collision and crime rates. Previous research focused on modeling both events separately despite evidence suggesting a high correlation. Additionally, there is a limited understanding of the impact of Mobile Automated Enforcement (MAE) on crime or the impact of changing a deployment strategy on collision and crime dates. For this reason, this study categorized MAE deployment into three different clusters. A random-parameter multivariate Tobit model was developed under the Bayesian framework to understand the impact of changing the deployment on collision and crime rates in a neighborhood. Firstly, the results of the analysis quantified the high correlation between collision and crime rates (0.86) which suggest that locations with high collision rates also coincide with locations with high crime rates. The results also demonstrated the safety effectiveness (i.e., reduced crime and collision rates) increased for the clusters that are associated with an increased enforcement duration at a neighborhood level. Understanding how changing the deployment strategy at a macro-level affects collision and crime rates provides enforcement agencies with the opportunity to maximize the efficiency of their existing resources.

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“…e conditional logit model was applied to quantitatively analyse the relative safety performance of SC in different traffic flow states while controlling for the effects of other traffic related variables, such as weather condition, geometric metric design, road pavement, etc. e model can be written as [33][34][35][36][37]…”

Section: Bayesian Conditional Logit Modelmentioning

confidence: 99%

Analysis of Freeway Secondary Crashes in Different Traffic Flow States by Three-Phase Traffic Theory

Yang

Zhang

2020

Journal of Advanced Transportation

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The objective of this study is to analyse the relationship between secondary crash risk and traffic flow states and explore the contributing factors of secondary crashes in different traffic flow states. Crash data and traffic data were collected on the I-880 freeway in California from 2006 to 2011. The traffic flow states are categorised by three-phase traffic theory. The Bayesian conditional logit model has been established to analyse the statistical relationship between the secondary crash probability and various traffic flow states. The results showed that free flow (F) state has the best safety performance of secondary crash and synchronized flow (S) state has the worst safety performance of secondary crashes. The traditional logistic regression model has been used to analyse the contributing factors of secondary crashes in different traffic flow states. The results indicated that the contributing factors in different traffic flow states are significantly different.

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Analysis of Crash Rates at Freeway Diverge Areas using Bayesian Tobit Modeling Framework

Cited by 17 publications

References 52 publications

Crash severity analysis of nighttime and daytime highway work zone crashes

Crash severity analysis of nighttime and daytime highway work zone crashes

Using Bayesian Tobit Models to Understand the Impact of Mobile Automated Enforcement on Collision and Crime Rates

Analysis of Freeway Secondary Crashes in Different Traffic Flow States by Three-Phase Traffic Theory

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