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

Susana García-HerreroJuan Diego FebresWafa BoulagouasJosé Manuel GutiérrezMiguel Ángel Mariscal Saldaña
Published in: International journal of environmental research and public health (2021)
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.
Keyphrases
  • machine learning
  • air pollution
  • big data
  • deep learning
  • mental health
  • working memory
  • artificial intelligence
  • electronic health record
  • middle aged
  • neural network