Influence of seat-belt use on the severity of injury in traffic accidents

Febres, Juan Diego; Herrero, Susana Garcı́a; Herrera, Sixto; Gutiérrez, José Manuel; López-García, J.R.; Saldaña, Miguel Ángel Mariscal

doi:10.1186/s12544-020-0401-5

Cited by 30 publications

(13 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The deployment of the Bayesian methodology in recent decades has been developed for various subject areas for learning, modeling, forecasting and decision-making [ 32 , 33 ]. As regards the regulatory alignment and traffic safety research, Bayesian networks have been used to assess the safety impact of red-light cameras on the reduction of traffic signal violations [ 34 ], predict road safety hotspots [ 35 ], analyze the causation of road accidents [ 36 , 37 ], measure the influence the drivers’ behaviors and psychophysical factors on injury severity and distractions [ 38 ], measure the influence of the seat-belt use on the traffic accidents severity [ 39 ] and analyze the role of the journey purpose in road traffic injuries [ 40 ].…”

Section: Methodsmentioning

confidence: 99%

An Investigation into Unsafe Behaviors and Traffic Accidents Involving Unlicensed Drivers: A Perspective for Alignment Measurement

Boulagouas

Herrero

Chaib

et al. 2020

IJERPH

Self Cite

View full text Add to dashboard Cite

Road traffic plays a vital role in countries’ economic growth and future development. However, traffic accidents are considered a major public health issue affecting humankind. Despite efforts by governments to improve traffic safety, the misalignment between the policy efforts and on-ground infringements, distractions and breaches reflect the regulatory failure. This paper uses the Bayesian network method to investigate unsafe behaviors and traffic accidents involving unlicensed drivers as a perspective for the regulatory alignment assessment. The findings suggest that: (1) unlicensed drivers are more likely to have unsafe driving behaviors; (2) the probability of being involved in a severe traffic accident increases when the drivers are unlicensed and decreases in the case of licensed drivers; (3) young drivers are noticeably more likely to engage in unsafe behaviors, usually leading to serious injuries and deaths, when their driving licenses are invalid; (4) women are more likely to engage in right-of-way violations and to have collisions with no serious injuries, contrary to unlicensed men drivers, who are involved in other types of traffic accidents resulting in serious injuries.

show abstract

Section: Methodsmentioning

confidence: 99%

An Investigation into Unsafe Behaviors and Traffic Accidents Involving Unlicensed Drivers: A Perspective for Alignment Measurement

Boulagouas

Herrero

Chaib

et al. 2020

IJERPH

Self Cite

View full text Add to dashboard Cite

show abstract

“…The vehicle issues may be overcome by adopting a proper maintenance policy [59]. Committing human error is due to the unprofessional approach adopted in driving [60]. The negligence in driving caused by not adhering to rules is another important neglected factor in the main criteria.…”

Section: Ahp Resultsmentioning

confidence: 99%

Assessing the Risk of University-Student Driving to enhance Safe and Sustainable Traffic Management: A Logistic Regression and Analytic Hierarchy Approach

et al. 2022

View full text Add to dashboard Cite

Road accidents have become more common these days and it is pathetic when the accidents happen due to ignorance. The research objective is focused on university students, creating awareness about road safety and improving a sustainable traffic management scenario in the Kingdom of Saudi Arabia. An analytical hierarchy process and a logistic regression model were used to determine the risk priorities ranking of severity factors based on the comparisons of different driver behaviour factors. A cross-sectional survey was conducted among 3200 university students in Saudi Arabia to evaluate the risk associated with accident factors. The main factors taken for risk analysis were Stability during driving, not adhering to rules, committing human errors, Insufficient Visibility, Facing Vehicles Issues. The model estimation analysis revealed the severity, which was based on the student's behavioural factors as a driver which contributed to the high fatality. It is further proposed to teach an interdisciplinary course on Traffic Management to various university students. The awareness towards traffic sense and safety rules would bring down the accidents rates and help the government to maintain smooth traffic density.

show abstract

“…In the present study, Bayesian Networks have been deployed to model the influence of distracted driving on the severity of traffic accidents and unsafe driving behaviors. Over the last few decades, the Bayesian approach has been extensively applied to traffic safety studies, for instance, an assessment of road safety [ 56 , 57 ], an assessment of the influence of seatbelt use on the severity of traffic accidents [ 58 ], an estimation of committing an infraction due to mobile use [ 59 ], music distraction among young drivers [ 60 ], a prediction of traffic accidents [ 61 ], etc.…”

Section: Methodsmentioning

confidence: 99%

Assessment of the Influence of Technology-Based Distracted Driving on Drivers’ Infractions and Their Subsequent Impact on Traffic Accidents Severity

Herrero

Febres

Boulagouas

et al. 2021

IJERPH

Self Cite

View full text Add to dashboard Cite

Multitasking while driving negatively affects driving performance and threatens people’s lives every day. Moreover, technology-based distractions are among the top driving distractions that are proven to divert the driver’s attention away from the road and compromise their safety. This study employs recent data on road traffic accidents that occurred in Spain and uses a machine-learning algorithm to analyze, in the first place, the influence of technology-based distracted driving on drivers’ infractions considering the gender and age of the drivers and the zone and the type of vehicle. It assesses, in the second place, the impact of drivers’ infractions on the severity of traffic accidents. Findings show that (i) technology-based distractions are likely to increase the probability of committing aberrant infractions and speed infractions; (ii) technology-based distracted young drivers are more likely to speed and commit aberrant infractions; (iii) distracted motorcycles and squad riders are found more likely to speed; (iv) the probability of committing infractions by distracted drivers increases on streets and highways; and, finally, (v) drivers’ infractions lead to serious injuries.

show abstract

Influence of seat-belt use on the severity of injury in traffic accidents

Cited by 30 publications

References 18 publications

An Investigation into Unsafe Behaviors and Traffic Accidents Involving Unlicensed Drivers: A Perspective for Alignment Measurement

An Investigation into Unsafe Behaviors and Traffic Accidents Involving Unlicensed Drivers: A Perspective for Alignment Measurement

Assessing the Risk of University-Student Driving to enhance Safe and Sustainable Traffic Management: A Logistic Regression and Analytic Hierarchy Approach

Assessment of the Influence of Technology-Based Distracted Driving on Drivers’ Infractions and Their Subsequent Impact on Traffic Accidents Severity

Contact Info

Product

Resources

About