Modeling of Low Visibility-Related Rural Single-Vehicle Crashes Considering Unobserved Heterogeneity and Spatial Correlation

Cai, Zhenggan; Fan, Wei; Wang, Zhenyu; Guo, Yongqing; Чэн, Лонг; Li, Xin

doi:10.3390/su13137438

Cited by 14 publications

(5 citation statements)

References 76 publications

(118 reference statements)

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“…However, this variable becomes totally insignificant once truck crashes are accommodated. Cai et al [59] obtained a similar conclusion by analyzing rural SV crashes in China and believed that more driving experience may be a dominant factor in determining crash severity. Hence, government departments may consider providing regular training and driving skills tests for older adults, with the aim of improving their traffic safety performance.…”

Section: Discussionmentioning

confidence: 71%

Investigating Rural Single-Vehicle Crash Severity by Vehicle Types Using Full Bayesian Spatial Random Parameters Logit Model

et al. 2021

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The effect of risk factors on crash severity varies across vehicle types. The objective of this study was to explore the risk factors associated with the severity of rural single-vehicle (SV) crashes. Four vehicle types including passenger car, motorcycle, pickup, and truck were considered. To synthetically accommodate unobserved heterogeneity and spatial correlation in crash data, a novel Bayesian spatial random parameters logit (SRP-logit) model is proposed. Rural SV crash data in Shandong Province were extracted to calibrate the model. Three traditional logit approaches—multinomial logit model, random parameter logit model, and random intercept logit model—were also established and compared with the proposed model. The results indicated that the SRP-logit model exhibits the best fit performance compared with other models, highlighting that simultaneously accommodating unobserved heterogeneity and spatial correlation is a promising modeling approach. Further, there is a significant positive correlation between weekend, dark (without street lighting) conditions, and collision with fixed object and severe crashes and a significant negative correlation between collision with pedestrians and severe crashes. The findings can provide valuable information for policy makers to improve traffic safety performance in rural areas.

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Section: Discussionmentioning

confidence: 71%

Investigating Rural Single-Vehicle Crash Severity by Vehicle Types Using Full Bayesian Spatial Random Parameters Logit Model

et al. 2021

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“…Additionally, to study driver characteristics in single-vehicle crashes, we considered vehicle type (16) and driver age (17) as variables. For multi-vehicle crashes, we used (18) vehicle type combination (hit and being hit) and ( 19) driver age combination (hit and being hit) as additional variables.…”

Section: Methodsmentioning

confidence: 99%

Impact Analysis of Road Infrastructure and Traffic Control on Injury Severity of Single- and Multi-vehicle Crashes

Tanishita¹,

Sekiguchi²

2023

Preprint

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Single and multi-vehicle crashes are a significant issue that causes economic and social costs and has therefore gained attention. This study explored the factors associated with injury severity for both single- and multi-vehicle crashes using over 550,000 crash data points in Japan between 2019 and 2021. We identified the determinants of road infrastructure and traffic control while controlling for driver, vehicle, environmental, and accident characteristics by applying ordered logit and bias-reduced binomial regression models. Our findings are as follows. 1) Traffic control variables did not affect single-vehicle crashes. 2) Guardrails had a higher severity in both single-vehicle crashes and multi-vehicle crashes at intersections. 3) The impact of the centerline differed between intersections and non-intersections for multi-vehicle crashes. These results of this study provide transportation agencies with important guidance as to the road infrastructure and transport control.

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“…Additionally, to study driver characteristics in single-vehicle crashes, (17) driver age and (18) vehicle type were considered. For multi-vehicle crashes, (17) driver age combination and (18) vehicle type combination were used as additional variables.…”

Section: Methodsmentioning

confidence: 99%

“…Other variables, such as speed limit and other interaction term, did not have any significant impact on the severity of singlevehicle crashes. Regarding driver age, young people (16)(17)(18)(19)(20)(21)(22)(23)(24) are known to have a higher proportion in the number of accidents, but not as high in fatalities and of lower severity.…”

Section: Single-vehicle Crashmentioning

confidence: 99%

Impact Analysis of Road Infrastructure and Traffic Control on Injury Severity of Single- and Multi-Vehicle Crashes

Tanishita,

Sekiguchi

2023

Sustainability

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Single- and multi-vehicle crashes are a significant issue that has economic and social costs and has therefore gained attention. This study explored the factors associated with injury severity for both single- and multi-vehicle crashes using over 550,000 crash data in Japan from 2019 to 2021. The determinants of road infrastructure and traffic control were identified while considering driver, vehicle, environmental, and accident characteristics, using ordered logit and bias-reduced binomial regression models. Our findings are as follows. Traffic control variables had no significant effect on the injury of single-vehicle crashes. Guardrails were associated with higher severity in both single-vehicle and multi-vehicle crashes at intersections. The impact of the centerline varied between intersections and non-intersections for multi-vehicle crashes. The results of this study provide transportation agencies with important guidance for road infrastructure and transport control.

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Modeling of Low Visibility-Related Rural Single-Vehicle Crashes Considering Unobserved Heterogeneity and Spatial Correlation

Cited by 14 publications

References 76 publications

Investigating Rural Single-Vehicle Crash Severity by Vehicle Types Using Full Bayesian Spatial Random Parameters Logit Model

Investigating Rural Single-Vehicle Crash Severity by Vehicle Types Using Full Bayesian Spatial Random Parameters Logit Model

Impact Analysis of Road Infrastructure and Traffic Control on Injury Severity of Single- and Multi-vehicle Crashes

Impact Analysis of Road Infrastructure and Traffic Control on Injury Severity of Single- and Multi-Vehicle Crashes

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