Assessment of tire failure related crashes and injury severity on a mountainous freeway: Bayesian binary logit approach

Haq, Muhammad Tahmidul; Zlatkovic, Milan; Ksaibati, Khaled

doi:10.1016/j.aap.2020.105693

Cited by 30 publications

(14 citation statements)

References 38 publications

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“…Injury severity levels are often condensed to form only two categories, and as a result, binary logit or probit models were used (19). Apart from the traditional logit or probit models, Bayesian statistics are also popular in traffic safety analysis because of their satisfactory performance (20)(21)(22)(23). For this study, binary logit models with a Bayesian inference approach were applied to explore the effects of the vehicle, driver, crash, roadway, and environmental factors contributing to fatalities or any other injuries in commercial truck-related crashes, broken down by various driving actions.…”

Section: Methodsmentioning

confidence: 99%

Assessment of Commercial Truck Driver Injury Severity as a Result of Driving Actions

Haq

Zlatkovic

Ksaibati

2021

Transportation Research Record

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The disaggregate modeling approach is a new trend in the literature to analyze the injury severity of truck-involved crashes. The assessment of truck driver injury severity based on driver action is still missing in the literature. This paper presents an extensive exploratory analysis that highlights significant variability in the severity of truck drivers’ injuries based on various action types (i.e., aggressive driving, failure to keep proper lane, driving too fast, and no improper driving). Binary logistic regression with the Bayesian random intercept approach was developed to examine the factors contributing to fatal or any injuries of truck drivers using 10 years (2007–2016) of historical crash data in Wyoming. Log-likelihood ratio tests were performed to justify that separate models by various driving action types are warranted. The results demonstrated the effects of various vehicle, driver, crash, and roadway characteristics, combined with truck driver-specific action, on the corresponding severity of driver injury. The gross vehicle weight, age and gender of the driver, time of day, lighting condition, and the presence of junctions were found to have significantly different impacts on the severity of truck driver injury in various driving action-related crashes. With the incorporation of the random intercept in the modeling procedure, the analysis found a strong presence (27%–33%) of intra-crash correlation in driver injury severity within the same crash. Finally, based on the findings of this study, several recommendations are made.

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Section: Methodsmentioning

confidence: 99%

Assessment of Commercial Truck Driver Injury Severity as a Result of Driving Actions

Haq

Zlatkovic

Ksaibati

2021

Transportation Research Record

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“…Statistical analyses on the dependence of road accident rate on tire tread depth are essential and are frequently carried out in many countries [7,8,13]. Through road accident research, the relative probability of occurrence of a road accident on dry and wet pavements depending on tire tread depth was found (Figure 2).…”

Section: The Impact Of Tire Wear On the Accident Riskmentioning

confidence: 99%

“…Tires of road vehicles present only one of the varieties of factors that impact the degree of road accident risk. However, road accidents related to tire failure contribute to more severe injuries; therefore, appropriate state-wide inspection programs are meaningful [7]. A seven-year study of Louisiana data showed that tire failure and worn tires together with defective brakes impact road crash severity to a great extent [8].…”

Section: Introductionmentioning

confidence: 99%

“…In many countries, statistical tests on the dependence of road accident rate on tire tread depth were carried out [7,8]. In the course of investigation of road accidents, it was found that relative road accident probability depends on tire tread depth when road pavement is dry or wet.…”

Section: Introductionmentioning

confidence: 99%

“…A vehicle tire is an irreparable product, i.e. a product that is replaced after its first fault (a certain level of wear) because driving stability and general safety directly depend on it [7].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Prediction of Road Accident Risk for Vehicle Fleet Based on Statistically Processed Tire Wear Model

Pečeliūnas

Žuraulis

Dróździel

et al. 2022

PROMTT

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The goal of the paper is to investigate the impact of tire tread depth on road accident risk and to develop an accident rate prediction model. The state of 4288 vehicle tires using tread depth gauge was inspected and processed statistically. The tread depth of the most worn tire from each vehicle was registered for further analy-sis. Based on the collected data, a statistical tire tread depth model for an insurance company vehicle fleet had been developed. The conformity of the gamma distribu-tion to the data was verified upon applying the Pearson compatibility criterion. The paper provides the histo-grams of the frequencies of tire tread depths and the theoretical curves of the distribution density. The prob-ability of the accident risk depending on the tire tread depth (adaptive risk index) was calculated applying the formed distributions and risk index dependence on the tire tread depth for the inspected vehicle fleet. Accord-ing to the developed prediction model, an upgrade of the regulation for the minimum allowed tire tread depth by 2 mm (up to 3.6 mm) could reduce road accident risk (caused by poor adhesion to road surface) to 19.3% for the chosen vehicle fleet. Such models are useful for road safety experts, insurance companies and accident cost evaluation specialists by predicting expenses related to insurance events.

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Assessment of commercial truck driver injury severity based on truck configuration along a mountainous roadway using hierarchical Bayesian random intercept approach

Haq

Zlatkovic

Ksaibati

2021

Accident Analysis & Prevention

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Assessment of tire failure related crashes and injury severity on a mountainous freeway: Bayesian binary logit approach

Cited by 30 publications

References 38 publications

Assessment of Commercial Truck Driver Injury Severity as a Result of Driving Actions

Assessment of Commercial Truck Driver Injury Severity as a Result of Driving Actions

Prediction of Road Accident Risk for Vehicle Fleet Based on Statistically Processed Tire Wear Model

Assessment of commercial truck driver injury severity based on truck configuration along a mountainous roadway using hierarchical Bayesian random intercept approach

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