Influence of seat belt use on driver severity injuries and use trend analysis
DOI:
https://doi.org/10.5944/ribim.28.1.41712Keywords:
Driver injury severity, Seat belt, Machine Learning Methods, Bayesian Hierarchical Model, Lightduty vehicles N1, Passenger carsAbstract
The accident rate of Light Commercial Vehicles (VLC) has increased in recent years, a priori mainly due to professional use in the logistics area. The main objective is to analyse the most important variables that influence the severity of the driver with the involvement of four types of VLC of the same category N1. Subsequently, the evolutionary trend of the rates for the most important variable for data from the period: 2000-2015 is studied. In the first part of this work, some results of driver severity classification models using Machine Learning techniques are described, which show the use of seat belts as the most important variable in the two types of accidents analysed. In the second part, hierarchical Bayesian models are applied to analyse the trend in the rate of use of seat belts by drivers in 2 types of VLC and passenger car. In this period, it is highlighted that the rate of seat belt use by drivers involved in fatal accidents (statistical average is ~ 73%), percentage of use much lower than what the surveys establish (~ 90%). The trend analysis for the 3 groups of drivers
indicates the increase in the use of this security system, highlighting a higher proportion of use in truck drivers. Monitoring of some specific groups is recommended to reduce the probability of risky behaviour by the driver, such as not using a seat belt.
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