Analysis of driver injury severity in rural single-vehicle crashes

Xie, Yuanchang; Zhao, Kaiguang; Huynh, Nathan

doi:10.1016/j.aap.2011.12.012

Cited by 166 publications

(71 citation statements)

References 23 publications

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“…The random parameters found in the RPL model (indicated by rp superscripts) were assumed to be normally distributed [see [5]] and had statistically significant standard deviations at 0.05 significance levels. [75,81,87,88]]. An attempt was made to develop LC random parameters logit model for this study.…”

Section: Estimation Resultsmentioning

confidence: 99%

“…The cross-marginal effect shows the impact of a unit change in variable of alternative ( ̸ = ) on the probability for crash to result in outcome . According to [80,81], the final marginal effect of an explanatory variable is the sum of the marginal effects for each class weighted by their posterior latent class probabilities. It should be noted that there are no definitive rules for selecting a set number of latent classes to be modeled [81].…”

Section: Latent Class Logitmentioning

confidence: 99%

“…According to [80,81], the final marginal effect of an explanatory variable is the sum of the marginal effects for each class weighted by their posterior latent class probabilities. It should be noted that there are no definitive rules for selecting a set number of latent classes to be modeled [81]. It is documented, however, that too many classes can negatively affect model convergence and complicate model interpretation [82].…”

Section: Latent Class Logitmentioning

confidence: 99%

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Effects of Human-Centered Factors on Crash Injury Severities

Adanu

Jones

2017

Journal of Advanced Transportation

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Factors related to drivers and their driving habits dominate the causation of traffic crashes. An in-depth understanding of the human factors that influence risky driving could be of particular importance to facilitate the application of effective countermeasures. This paper sought to investigate effects of human-centered crash contributing factors on crash outcomes. To select the methodology that best accounts for unobserved heterogeneity between crash outcomes, latent class (LC) logit model and random parameters logit (RPL) model were developed. Model estimation results generally show that serious injury crashes were more likely to involve unemployed drivers, no seatbelt use, old drivers, fatigued driving, and drivers with no valid license. Comparison of model fit statistics shows that the LC logit model outperformed the RPL model, as an alternative to the traditional multinomial logit (MNL) model.

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Section: Estimation Resultsmentioning

confidence: 99%

Section: Latent Class Logitmentioning

confidence: 99%

Section: Latent Class Logitmentioning

confidence: 99%

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Effects of Human-Centered Factors on Crash Injury Severities

Adanu

Jones

2017

Journal of Advanced Transportation

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“…Previous researches have reported conflicting results on the effect of clear 113-10 weather condition on crash severity. Some studies by (52,59,70) found that clear weather is associated with increased severity, while (51,66,69) have concluded the opposite. Accordingly, it can be inferred that higher speeds for males and more careful driving for females in such conditions are the reasons for the mentioned results.…”

Section: Discussionmentioning

confidence: 99%

A Study of Sex Differences on Road Crash Severity

Razi-Ardakani¹,

Ariannezhad²,

Kermanshah³

2018

Proceedings of the 3rd International Conference on Civil, Structural and Transportation Engineering (ICCSTE'18)

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-This study aims to investigate the factors affecting the severity of urban crashes among male and female drives. Traffic crashes occurred in Tehran, Iran during the year 2009 were utilized in this research. The observations were divided into two groups based on driver's gender. Two crash severity models were estimated for each group using binary logit model in which dependent variable included damage only crashes and injury/fatal crashes. Pseudo-elasticity values were calculated to better compare the male and female drivers and understand the exact effect of each variable. The results showed that factors such as increased driver's age, noneducated drivers, weekend, nighttime and intersections have increased the crash severity in both male and female drivers. Among human factors which affect the crash severity, violating the rules, speeding, unnecessary haste and diversion to left, increased the crash severity in males, while lack of driving experience, loss of control and vehicle mechanical defect increased the females' crash severity. Furthermore, accidents involving male drivers were more severe in clear and foggy weather conditions, while female drivers were observed to have more severe crashes in rainy weather. Significant differences in contributing factors to severity of crashes in male and female drivers prove that discrete policies for these two groups of drivers should be adopted. The obtained results suggested that in order to improve the safety of roads and to encourage drivers to obey driving laws, educational programs about males' driving habits should be adopted.

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“…Utilizing both the MNL model and the LCL model, factors such as driver age, influence of alcohol or drug, seat belt usage, speed are found to be closely related to driver injury severity levels in rural single-vehicle accidents [1] . Using a stepwise logistic regression model, the district board, road type, speed limit, time of the accident, driver's gender, and vehicle type are significant factors influencing the injury severity in multiple-vehicle traffic accidents in Hong Kong [2] .…”

Section: Introductionmentioning

confidence: 99%

Risk Factors for the Injury Severity of Fatigue-Related Traffic Accidents

Wang

Pei

Liu

2012

AEF

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Abstract. Traffic accidents caused by drivers' fatigue carry less than one percent of the whole accidents in HLJ Province during the years 2006 to 2008. However, more than forty percent of such accidents accompanied fatalities. Drivers' fatigue is usually hard to be identified and there are no valid measures that could make real-time detection for it. Accordingly, variables such as drivers' characteristics, time of accident and whether using seat belt are considered to have close association with the injury severity in fatigue-related traffic accidents. This research focuses on analyzing injury severities of traffic accidents caused by drivers' fatigue, utilizing stepwise logistic regression method. Potential risk factors such as human, environment, road, and so on, were examined. Driving year, road pavement type, road grade and alignment, terrain, time and type of the accident, streetlight condition, vehicle type, speed limit, the number of vehicles involved, and whether using seat belt are significant factors impacting the injury severity. Identifying the high risk factors influencing the injury severity of fatigue-related accidents helps prevent the occurrence of drivers' fatigue and improve road safety conditions.

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Analysis of driver injury severity in rural single-vehicle crashes

Cited by 166 publications

References 23 publications

Effects of Human-Centered Factors on Crash Injury Severities

Effects of Human-Centered Factors on Crash Injury Severities

A Study of Sex Differences on Road Crash Severity

Risk Factors for the Injury Severity of Fatigue-Related Traffic Accidents

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