Modeling the impact of various variables on severity of crashes involving traffic barriers

Molan, Amirarsalan Mehrara; Rezapour, Mahdi; Ksaibati, Khaled

doi:10.1080/19439962.2018.1547995

Cited by 18 publications

(15 citation statements)

References 18 publications

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“…Similar to past studies [5,24,26,27,29], data analysis was conducted using an ordinal logistic regression. Three categories were defined for crash severity as dependent variables.…”

Section: Statistical Analysis Methodsmentioning

confidence: 99%

“…Traffic barriers were initially designed to avoid the vehicles from running off of the road, while designers were noticing less in terms of the crash severity [4]. Unfortunately, many of the old traffic barrier segments have not been upgraded in accordance with recent design policies due to the substantial cost needed to replace them [4,5]. From another point of view, roadway speed limit, as a parameter related to crash severity, has been changed considerably over the last four decades.…”

Section: Introductionmentioning

confidence: 99%

“…Note that the mean traffic composition in Wyoming's non-interstate roads is 13% based on the data collected in this study, • Rural roads with high-speed limits. The speed limit is typically between 75 and 80 mph on interstate roads, and between 65 and 70 mph on state roads, • Based on previous studies [5,12], traffic barriers have the first rank of the fixed-object fatal crashes (with a percentage of 38%) among all the fixed object in Wyoming. Wyoming's roadsides are almost empty of any tree, building, or even utility poles.…”

Section: Introductionmentioning

confidence: 99%

“…Also, the cable barriers cause less severe crashes in comparison with the other types of traffic barriers. Molan et al [5] compared the variables affecting the severity of crashes involving traffic barriers in truck and non-truck (light vehicles) crashes. Based on results, it was found that cable barriers are performing safer than the other traffic barriers in non-truck crashes.…”

Section: Introductionmentioning

confidence: 99%

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Modeling traffic barriers crash severity by considering the effect of traffic barrier dimensions

2019

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Traffic barriers are in widespread all around the USA as safety countermeasures for reducing the severity of runoff road crashes. The effect of traffic barriers' dimension had been ignored in past real-world crash studies due to the considerable cost and time needed for collecting field data. This paper presented two new analytical models to investigate the effect of different variables on the severity of crashes involving traffic barriers, and end treatments. For this reason, a field survey was conducted on over 1.3 million linear feet of traffic barriers (approximately 4,176 miles road) in Wyoming to measure traffic barriers' geometric features like height, length, offset, and slope rate. The collected data included 55% of all non-interstate roads of Wyoming. Based on results, the crashes involving box beam barriers were less severe than the crashes involved with W-beam or concrete barriers. The traffic barriers with a height between 28 and 31 in. were found safer than the traffic barriers shorter than 28 in., while there was no significant difference between the traffic barriers taller than 31 in. to those shorter than 28 in. in terms of crash severity. The end treatments located nearer to the traffic lane had lower crash severity. Keywords Crash severity Á Runoff road crashes Á Traffic barriers Á End treatments Á Traffic barrier dimensions Á Real-world crash analysis Á Wyoming

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“…Similar to past studies [5,24,26,27,29], data analysis was conducted using an ordinal logistic regression. Three categories were defined for crash severity as dependent variables.…”

Section: Statistical Analysis Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Modeling traffic barriers crash severity by considering the effect of traffic barrier dimensions

2019

Self Cite

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“…Unlike the multinomial logistic regression, the ordinal logistic regression has its outcome values ordered. e ordinal logistic regression has seen several usages in diverse fields of research [40][41][42][43]. With regard to studies about road traffic fatalities, Kadilar [44] and Qian et al [45] used the ordinal logistic regression to analyze the effect of drivers' behavior, roadway, and vehicle characteristics on crash severity in traffic accidents in Turkey and China, respectively.…”

Section: Literature Reviewmentioning

confidence: 99%

Predictive Probability Models of Road Traffic Human Deaths with Demographic Factors in Ghana

2022

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Road traffic carnages are global concerns and seemingly on the rise in Ghana. Several risk factors have been studied as associated with road traffic fatalities. However, inadequate road traffic fatality (RTF) data and inconsistent probability outcomes for RTF remain major challenges. The objective of this study was to illustrate and estimate probability models that can predict road traffic fatalities. We relied on 66,159 recorded casualties who were involved in road traffic accidents (RTAs) in Ghana from 2015 to 2019. Three generalized linear models, namely, logistic regression, probit regression, and linear probability model, were used for the analysis. We found that gender and age groups have significant effects in predicting the probability of road traffic fatality for all three models. Through a likelihood ratio test, however, it was determined that the logit regression model produced consistent probabilities of traffic fatalities which are very close to the actual probability values across the age groups and gender, compared to the other two models. Thus, we recommend intensified campaign for the use of seat belts in vehicles, targeted at the aged and male users of road transport, to reduce the possibility of death in any RTA.

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Crash severity analysis for mixed lane urban road considering shoulder distress condition using SEM and MARS model: a case study in Patna, India

Barman,

Bandyopadhyaya

2023

Innov. Infrastruct. Solut.

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Modeling the impact of various variables on severity of crashes involving traffic barriers

Cited by 18 publications

References 18 publications

Modeling traffic barriers crash severity by considering the effect of traffic barrier dimensions

Modeling traffic barriers crash severity by considering the effect of traffic barrier dimensions

Predictive Probability Models of Road Traffic Human Deaths with Demographic Factors in Ghana

Crash severity analysis for mixed lane urban road considering shoulder distress condition using SEM and MARS model: a case study in Patna, India

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