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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.
speed infractions, Automobile Driving, Technology, Technology-based distractions, Aberrant infractions, Salud, Transportation, http://metadata.un.org/sdg/3, Article, Transportes, bayesian network, Humans, Ensure healthy lives and promote well-being for all at all ages, aberrant infractions, Road traffics accidents, Speed infractions, Accidents, Traffic, Tecnología, Road traffic accidents, Traffic accidents severity, road traffic accidents, Bayesian networks, Bayesian network, Health, Spain, Distracted Driving, traffic accidents severity, technology-based distractions, Safety
speed infractions, Automobile Driving, Technology, Technology-based distractions, Aberrant infractions, Salud, Transportation, http://metadata.un.org/sdg/3, Article, Transportes, bayesian network, Humans, Ensure healthy lives and promote well-being for all at all ages, aberrant infractions, Road traffics accidents, Speed infractions, Accidents, Traffic, Tecnología, Road traffic accidents, Traffic accidents severity, road traffic accidents, Bayesian networks, Bayesian network, Health, Spain, Distracted Driving, traffic accidents severity, technology-based distractions, Safety
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 26 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
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