Investigating the uniqueness of crash injury severity in freeway tunnels: A comparative study in Guizhou, China

Zhou, Zichu; Meng, Fang; Song, Chunqiao; Sze, N.N.; Guo, Zhongyin; Ouyang, Nan

doi:10.1016/j.jsr.2021.02.008

Cited by 17 publications

(18 citation statements)

References 45 publications

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“…Other types of collisions include collisions between a vehicle and tunnel facilities, such as a tunnel wall, as well as collisions between a vehicle and other objects, such as debris and falling objects from other vehicles or an inner wall. Therefore, unlike vehicle-to-object collisions, vehicle-to-vehicle collisions (e.g., rear-end collisions) could result in more severe injuries, which is consistent with the findings in previous studies [ 26 , 27 ]. Another interpretation can be made using the crash angle.…”

Section: Injury Severity Analysissupporting

confidence: 91%

“…However, these variables regarding the tunnel factor did not directly affect the injury severity but did affect the crash factor, and consequently, the crash factor was found to affect the injury severity factor. According to previous studies [ 1 , 3 , 5 , 21 , 23 , 26 ], it is found that the tunnel factor positively affects severe injuries. Although the results of the previous studies and this study show similarity in the relationship between the tunnel factor and the injury severity factor, this study explains the relationship between these two factors through the crash factor.…”

Section: Injury Severity Analysismentioning

confidence: 99%

“…Although this study did not apply a variable regarding crash speeds, the injury-severity effects in longer and wider tunnels can be explained by speeding effects (i.e., higher crash speed) caused by reduced driving attention and vigilance. Caliendo et al [ 21 ], Ma et al [ 2 ], and Zhou et al [ 26 ] also found that a greater tunnel length leads to a higher probability of severe injuries. Moreover, wider roads are presumed to decrease the perceived risk, so that drivers might increase their risky behavior [ 87 ].…”

Section: Injury Severity Analysismentioning

confidence: 99%

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Exploring Factors Affecting Crash Injury Severity with Consideration of Secondary Collisions in Freeway Tunnels

Chung

Kim²

2023

IJERPH

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Although there have been several studies conducted exploring the factors affecting injury severity in tunnel crashes, most studies have focused on identifying factors that directly influence injury severity. In particular, variables related to crash characteristics and tunnel characteristics affect the injury severity, but the inconvenient driving environment in a tunnel space, characterized by narrow space and dark lighting, can affect crash characteristics such as secondary collisions, which in turn can affect the injury severity. Moreover, studies on secondary collisions in freeway tunnels are very limited. The objective of this study was to explore factors affecting injury severity with the consideration of secondary collisions in freeway tunnel crashes. To account for complex relationships between multiple exogenous variables and endogenous variables by considering the direct and indirect relationships between them, this study used a structural equation modeling with tunnel crash data obtained from Korean freeway tunnels from 2013 to 2017. Moreover, based on high-definition closed-circuit televisions installed every 250 m to monitor incidents in Korean freeway tunnels, this study utilized unique crash characteristics such as secondary collisions. As a result, we found that tunnel characteristics indirectly affected injury severity through crash characteristics. In addition, one variable regarding crashes involving drivers younger than 40 years old was associated with decreased injury severity. By contrast, ten variables exhibited a higher likelihood of severe injuries: crashes by male drivers, crashes by trucks, crashes in March, crashes under sunny weather conditions, crashes on dry surface conditions, crashes in interior zones, crashes in wider tunnels, crashes in longer tunnels, rear-end collisions, and secondary collisions with other vehicles.

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Section: Injury Severity Analysissupporting

confidence: 91%

Section: Injury Severity Analysismentioning

confidence: 99%

Section: Injury Severity Analysismentioning

confidence: 99%

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Exploring Factors Affecting Crash Injury Severity with Consideration of Secondary Collisions in Freeway Tunnels

Chung

Kim²

2023

IJERPH

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“…With respect to mountainous highway scenarios, Wang et al, examined the influence of road geometric design on the injury severity of truck-related crashes, using two typical freeways in China, and found that curve factors significantly increased the likelihood of fatalities, but the opposite was true in the case of downgrade sections [ 12 ]. Similarly, Zhou et al selected freeways in a mountainous region of China as the scenario and compared the differences in the injury severity between tunnel sections and general sections [ 30 ]. Based on the estimated results, it appears that trucks were involved in more severe crashes in tunnel sections, and the risk of drivers or occupants being fatally injured is higher in the long tunnels that range from 1000 m to 3000 m in length.…”

Section: Literature Reviewmentioning

confidence: 99%

Analysis of Factors Contributing to the Injury Severity of Overloaded-Truck-Related Crashes on Mountainous Highways in China

Wen

Chen

et al. 2022

IJERPH

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Overloaded transport can certainly improve transportation efficiency and reduce operating costs. Nevertheless, several negative consequences are associated with this illegal activity, including road subsidence, bridge collapse, and serious casualties caused by accidents. Given the complexity and variability of mountainous highways, this study examines 1862 overloaded-truck-related crashes that happened in Yunnan Province, China, and attempts to analyze the key factors contributing to the injury severity. This is the first time that the injury severity has been studied from the perspective of crashes involving overloaded trucks, and meanwhile in a scenario of mountainous highways. For in-depth analysis, three models are developed, including a binary logit model, a random parameter logit model, and a classification and regression tree, but the results show that the random parameter logit model outperforms the other two. In the best-performing model, a total of fifteen variables are found to be significant at the 99% confidence level, including random variables such as freeway, broadside hitting, impaired braking performance, spring, and evening. In regards to the fixed variables, it is likely that the single curve, rollover, autumn, and winter variables will increase the probability of fatalities, whereas the provincial highway, country road, urban road, cement, wet, and head-on variables will decrease the likelihood of death. Our findings are useful for industry-related departments in formulating and implementing corresponding countermeasures, such as strengthening the inspection of commercial trucks, increasing the penalties for overloaded trucks, and installing certain protective equipment and facilities on crash-prone sections.

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“…Another type of dependent variable is multivariate dependent variables, which analyze the risk factors' contribution to crashes of different injury severity levels. Study [18] used a two-level binary logistic modeling approach to identify significant influential factors with tunnel crash safety, shows that speed limit, tunnel length, truck involvement, rear-end crash, rainy and foggy weather, and sequential crash were found to be positively associated with crash severity in freeway tunnels. Research [19] employed a random parameter logit model to examine the factors affecting the injury severity of the freeway tunnel group crashes, the result shows that the daytime, weekdays, entrance zone, downgrades, elder drivers, speeding, fatigue driving, and rollover collisions are positively associated, while winter, curves, and sideswipes are negatively associated with severe crashes.…”

Section: Introductionmentioning

confidence: 99%

A Bayesian Bivariate Random Parameters and Spatial-Temporal Negative Binomial Lindley Model for Jointly Modeling Crash Frequency by Severity: Investigation for Chinese Freeway Tunnel Safety

Cai

Tang

2022

IEEE Access

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As hazardous locations of a road, freeway tunnels have a higher risk of casualty than open roads. Therefore, it is necessary to seek a reliable crash prediction model and propose targeted improvement measures. However, existing studies on freeway tunnel crash models mainly suffer from the following problems: 1) They ignore the correlation between different injury severity levels of crashes; 2) They ignore the impact of excess zero observations; 3) They do not consider the influence of heterogeneity between samples and the spatio-temporal correlation. To solve the above problems, this paper has compiled a dataset with freeway tunnel design features, three years of traffic conditions, pavement conditions, and traffic crash data. Then, a bivariate random parameters negative binomial Lindley model (ST-BRPNB-L) is established for jointly modeling crash counts and injury severity levels, which consider excess zero observations by introducing Lindley parameters, characterize the heterogeneity, and spatial-temporal correlation between samples by introducing random parameters and spatio-temporal parameters. The Bayesian estimation results have shown that ST-BRPNB-L has the best goodness-of-fit among a series of comparison models, which verifies the superiority of the proposed model. On this basis, the influence of the risk factors on the frequency and severity of crashes was quantitatively analyzed based on the ST-BRPNB-L model's parameters estimation results, which provides a scientific basis for safety improvement measures of freeway tunnels. INDEX TERMSFreeway tunnel, traffic safety, crash modeling techniques, crashes by severity, excess zero observations, spatio-temporal correlation, unobserved heterogeneity, bivariate random parameters Lindley model.

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Investigating the uniqueness of crash injury severity in freeway tunnels: A comparative study in Guizhou, China

Cited by 17 publications

References 45 publications

Exploring Factors Affecting Crash Injury Severity with Consideration of Secondary Collisions in Freeway Tunnels

Exploring Factors Affecting Crash Injury Severity with Consideration of Secondary Collisions in Freeway Tunnels

Analysis of Factors Contributing to the Injury Severity of Overloaded-Truck-Related Crashes on Mountainous Highways in China

A Bayesian Bivariate Random Parameters and Spatial-Temporal Negative Binomial Lindley Model for Jointly Modeling Crash Frequency by Severity: Investigation for Chinese Freeway Tunnel Safety

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