Polytechnic University of Valencia Congress, CARMA 2020 - 3rd International Conference on Advanced Research Methods and Analytics

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Regression scores to identify risky drivers from braking pulses
Shuai Sun, Jun Bi, Montserrat Guillen, Ana Maria Pérez-Marín

Last modified: 14-05-2020

Abstract


Driving data record information on style and patterns of vehicles that are in
motion. These data are analysed to obtain risk scores that can later be
implemented in insurance pricing schemes. Scores may also be used in on-
board sensors to create risk alerts that help drivers to keep up with safety
margins. Regression methods are proposed and a prototype real sample of 253
drivers is analysed. Conclusions are drawn on the mean number of brake
pulses per day as measured within 30 seconds time-intervals. Linear and
logistic regressions serve to construct a label that classifies drivers. A novel
factor based on the driving range that is defined from geo-localization
improves the results considerably. Driving range is expressed as measures the
diagonal of a rectangle that contains the furthest North-South versus East-
West weekly vehicle trajectory. This factor shows that frequent braking activity
is negatively related to the square of driving range.


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