title: ÐÐ»Ð³Ð¾ÑÐ¸ÑÐ¼ Ð¾ÑÐµÐ½ÐºÐ¸ ÑÑÐ¸Ð»Ñ Ð²Ð¾Ð¶Ð´ÐµÐ½Ð¸Ñ ÑÑÐ°Ð½ÑÐ¿Ð¾ÑÑÐ½Ð¾Ð³Ð¾ ÑÑÐµÐ´ÑÑÐ²Ð° Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð´Ð°Ð½Ð½ÑÑ Ð¼Ð¾Ð±Ð¸Ð»ÑÐ½Ð¾Ð³Ð¾ ÑÑÑÑÐ¾Ð¹ÑÑÐ²Ð° Ð²Ð¾Ð´Ð¸ÑÐµÐ»Ñ
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: Mobile phone data-driven scoring algorithm
Creators: name: Ð¢Ð¸ÑÐ¾Ð², ÐÐ½ÑÐ¾Ð½
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2020
Subjects: Ð¾ÑÐµÐ½ÐºÐ° ÑÑÐ¸Ð»Ñ Ð²Ð¾Ð¶Ð´ÐµÐ½Ð¸Ñ
Ð°Ð½Ð°Ð»Ð¸Ð· Ð´Ð°Ð½Ð½ÑÑ
ÑÐµÐ½ÑÐ¾ÑÑ Ð¼Ð¾Ð±Ð¸Ð»ÑÐ½Ð¾Ð³Ð¾ ÑÐµÐ»ÐµÑÐ¾Ð½Ð°
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ÑÑÐ°Ð½ÑÐ¿Ð¾ÑÑÐ½Ð¾Ðµ ÑÑÐµÐ´ÑÑÐ²Ð¾
ÐºÐ¾Ð¼Ð¿ÑÑÑÐµÑÐ½Ð°Ñ Ð´Ð¸Ð°Ð³Ð½Ð¾ÑÑÐ¸ÐºÐ° Ð°Ð²ÑÐ¾Ð¼Ð¾Ð±Ð¸Ð»Ñ
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Ð°Ð²Ð°ÑÐ¸Ð¹Ð½ÑÐµ ÑÐ¸ÑÑÐ°ÑÐ¸Ð¸
driver behaviour scoring
data analysis
mobile phone sensors
cluster analysis
safety
usage-based insurance
telematics
k-means clustering
vehicle
on-board diagnostics
driver
algorithm
microelectromechanical systems
road accidents

description: Ð ÑÐ¾Ð²ÑÐµÐ¼ÐµÐ½Ð½ÑÑ ÑÐ¸ÑÑÐµÐ¼Ð°Ñ, Ð¾Ð±ÐµÑÐ¿ÐµÑÐ¸Ð²Ð°ÑÑÐ¸Ñ Ð±ÐµÐ·Ð¾Ð¿Ð°ÑÐ½Ð¾ÑÑÑ Ð´Ð¾ÑÐ¾Ð¶Ð½Ð¾Ð³Ð¾ Ð´Ð²Ð¸Ð¶ÐµÐ½Ð¸Ñ, Ð°ÐºÑÑÐ°Ð»ÑÐ½Ð° Ð·Ð°Ð´Ð°ÑÐ° Ð¾ÑÐµÐ½ÐºÐ¸ ÑÑÐ¸Ð»Ñ Ð²Ð¾Ð¶Ð´ÐµÐ½Ð¸Ñ ÑÑÐ°Ð½ÑÐ¿Ð¾ÑÑÐ½Ð¾Ð³Ð¾ ÑÑÐµÐ´ÑÑÐ²Ð°. ÐÐ°Ð¸Ð±Ð¾Ð»ÐµÐµ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð½ÑÐ¼ Ð¸ Ð¿Ð¾Ð¿ÑÐ»ÑÑÐ½ÑÐ¼ Ð¿Ð¾Ð´ÑÐ¾Ð´Ð¾Ð¼ Ð² ÑÐµÑÐµÐ½Ð¸Ð¸ ÑÑÐ¾Ð¹ Ð·Ð°Ð´Ð°ÑÐ¸ ÑÐ²Ð»ÑÐµÑÑÑ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸Ðµ Ð´Ð°Ð½Ð½ÑÑ ÑÐ¿ÐµÑÐ¸Ð°Ð»Ð¸Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð½ÑÑ Ð¿Ð¾Ð´ÐºÐ»ÑÑÐµÐ½Ð½ÑÑ Ðº ÑÑÐ°Ð½ÑÐ¿Ð¾ÑÑÐ½Ð¾Ð¼Ñ ÑÑÐµÐ´ÑÑÐ²Ñ ÑÑÑÑÐ¾Ð¹ÑÑÐ². ÐÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸Ðµ ÑÐ°ÐºÐ¸Ñ ÑÑÑÑÐ¾Ð¹ÑÑÐ² ÑÐ¾Ð¿ÑÐ¾Ð²Ð¾Ð¶Ð´Ð°ÐµÑÑÑ ÑÑÐ´Ð¾Ð¼ ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ñ Ð¾Ð³ÑÐ°Ð½Ð¸ÑÐµÐ½Ð¸Ð¹ Ð¸ ÑÐ°ÑÑÑ ÑÑÐ°Ð½ÑÐ¿Ð¾ÑÑÐ½ÑÑ ÑÑÐµÐ´ÑÑÐ² Ð¾ÐºÐ°Ð·ÑÐ²Ð°ÐµÑÑÑ Ð½ÐµÐ¾ÑÐ²Ð°ÑÐµÐ½Ð½Ð¾Ð¹. Ð ÑÐ¾ Ð²ÑÐµÐ¼Ñ ÐºÐ°Ðº ÐºÐ°ÑÐµÑÑÐ²Ð¾ ÑÐ°Ð±Ð¾ÑÑ Ð±Ð¾Ð»ÑÑÐ¸Ð½ÑÑÐ²Ð° ÑÐ¾Ð²ÑÐµÐ¼ÐµÐ½Ð½ÑÑ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð°Ð½Ð°Ð»Ð¸Ð·Ð° Ð´Ð°Ð½Ð½ÑÑ Ð² Ð±Ð¾Ð»ÑÑÐµÐ¹ ÑÑÐµÐ¿ÐµÐ½Ð¸ Ð·Ð°Ð²Ð¸ÑÐ¸Ñ Ð¾Ñ ÐºÐ¾Ð»Ð¸ÑÐµÑÑÐ²Ð° Ð½Ð°Ð±Ð»ÑÐ´ÐµÐ½Ð¸Ð¹, Ð½ÐµÐ´Ð¾ÑÑÐ°ÑÐ¾ÑÐ½ÑÐ¹ Ð¾ÑÐ²Ð°Ñ Ð¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°ÑÐµÐ»ÐµÐ¹ ÑÐ¸ÑÑÐµÐ¼ ÑÐ²Ð»ÑÐµÑÑÑ Ð²Ð°Ð¶Ð½Ð¾Ð¹ Ð´Ð»Ñ ÑÐ°ÑÑÐ¼Ð¾ÑÑÐµÐ½Ð¸Ñ Ð¿ÑÐ¾Ð±Ð»ÐµÐ¼Ð¾Ð¹. ÐÐ»Ñ ÑÐ²ÐµÐ»Ð¸ÑÐµÐ½Ð¸Ñ Ð¾ÑÐ²Ð°ÑÐ° Ð½Ð°Ð±Ð»ÑÐ´ÐµÐ½Ð¸Ð¹ ÑÑÐµÐ±ÑÐµÑÑÑ ÑÐ°ÑÑÐ¼Ð¾ÑÑÐµÑÑ Ð°Ð»ÑÑÐµÑÐ½Ð°ÑÐ¸Ð²Ð½ÑÐµ Ð½ÐµÑÐ¿ÐµÑÐ¸Ð°Ð»Ð¸Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð½ÑÐµ Ð¸ÑÑÐ¾ÑÐ½Ð¸ÐºÐ¸ Ð´Ð°Ð½Ð½ÑÑ. Ð¢Ð°ÐºÐ¸Ð¼Ð¸ Ð¸ÑÑÐ¾ÑÐ½Ð¸ÐºÐ°Ð¼Ð¸ Ð¼Ð¾Ð³ÑÑ ÑÐ²Ð»ÑÑÑÑÑ Ð¼Ð¾Ð±Ð¸Ð»ÑÐ½ÑÐµ ÑÑÑÑÐ¾Ð¹ÑÑÐ²Ð°, Ð¾Ð´Ð½Ð°ÐºÐ¾ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ðµ ÑÐ°ÐºÐ¸Ñ Ð´Ð°Ð½Ð½ÑÑ Ð² Ð·Ð°Ð´Ð°ÑÐ°Ñ Ð¾ÑÐµÐ½ÐºÐ¸ ÑÑÐ¸Ð»Ñ Ð²Ð¾Ð¶Ð´ÐµÐ½Ð¸Ñ ÑÐ»Ð°Ð±Ð¾ Ð¾ÑÐ²ÐµÑÐµÐ½Ð¾ Ð² ÑÐ¾Ð²ÑÐµÐ¼ÐµÐ½Ð½ÑÑ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸ÑÑ. Ð Ð´Ð°Ð½Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÐµ ÑÐ°ÑÑÐ¼Ð°ÑÑÐ¸Ð²Ð°ÑÑÑÑ Ð¼ÐµÑÐ¾Ð´Ñ Ð¾Ð±ÑÐ°Ð±Ð¾ÑÐºÐ¸ Ð´Ð°Ð½Ð½ÑÑ ÑÐ¸Ð³Ð½Ð°Ð»Ð° Ð¼Ð¸ÐºÑÐ¾ÑÐ»ÐµÐºÑÑÐ¾Ð¼ÐµÑÐ°Ð½Ð¸ÑÐµÑÐºÐ¸Ñ ÑÐ¸ÑÑÐµÐ¼ Ð¼Ð¾Ð±Ð¸Ð»ÑÐ½ÑÑ ÑÑÑÑÐ¾Ð¹ÑÑÐ² Ð´Ð»Ñ Ð²ÑÑÐ²Ð»ÐµÐ½Ð¸Ñ ÑÐ¾Ð±ÑÑÐ¸Ð¹, Ð¿ÑÐ¾Ð¸Ð·Ð¾ÑÐµÐ´ÑÐ¸Ñ Ð² ÑÐµÑÐµÐ½Ð¸Ð¸ Ð¿Ð¾ÐµÐ·Ð´ÐºÐ¸ ÑÑÐ°Ð½ÑÐ¿Ð¾ÑÑÐ½Ð¾Ð³Ð¾ ÑÑÐµÐ´ÑÑÐ²Ð° Ð¸ Ð¿Ð¾Ð´ÑÐ¾Ð´ Ðº ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ Ð¿Ð¾ÐµÐ·Ð´Ð¾Ðº Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð²ÑÑÐ²Ð»ÐµÐ½Ð½ÑÑ ÑÐ¾Ð±ÑÑÐ¸Ð¹. Ð ÐµÐ·ÑÐ»ÑÑÐ°ÑÐ¾Ð¼ ÑÐ°Ð±Ð¾ÑÑ ÑÐ²Ð»ÑÐµÑÑÑ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½ÑÐ¹ ÐºÐ¾Ð´ ÑÐµÐ°Ð»Ð¸Ð·ÑÑÑÐ¸Ð¹ Ð¾Ð¿Ð¸ÑÑÐ²Ð°ÐµÐ¼ÑÐ¹ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼. Ð ÑÐ°Ð¼ÐºÐ°Ñ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ¸ Ð¿ÑÐ¾Ð²Ð¾Ð´Ð¸ÑÑÑ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ðµ Ð¾ÑÐ½Ð¾Ð²Ð½ÑÑ Ð¿Ð°ÑÐ°Ð¼ÐµÑÑÐ¾Ð², Ð²Ð»Ð¸ÑÑÑÐ¸Ñ Ð½Ð° ÑÐ°Ð±Ð¾ÑÑ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð°, Ð¸ Ð¿ÑÐ¸Ð²Ð¾Ð´ÑÑÑÑ Ð¿ÑÐµÐ´Ð»Ð¾Ð¶ÐµÐ½Ð¸Ñ Ð¿Ð¾ Ð¸Ñ Ð½Ð°ÑÑÑÐ¾Ð¹ÐºÐµ. ÐÐ»Ð³Ð¾ÑÐ¸ÑÐ¼ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½ Ðº ÑÐ¾Ð±ÑÐ°Ð½Ð½ÑÐ¼ Ð¸Ð· Ð¾ÑÐºÑÑÑÑÑ ÑÐµÑÑÑÑÐ¾Ð² Ð½Ð°Ð±Ð¾ÑÐ°Ð¼ Ð´Ð°Ð½Ð½ÑÑ Ñ ÑÐµÐ»ÑÑ Ð¿ÑÐ¾Ð²ÐµÐ´ÐµÐ½Ð¸Ñ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ Ð¿ÑÐ¸Ð¼ÐµÐ½Ð¸Ð¼Ð¾ÑÑÐ¸ Ð¼ÐµÑÐ¾Ð´Ð° Ð½Ð° Ð¿ÑÐ°ÐºÑÐ¸ÐºÐµ. Ð ÑÐµÐ°Ð»Ð¸Ð·Ð°ÑÐ¸Ð¸ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ñ Ð½Ð°Ð¸Ð±Ð¾Ð»ÐµÐµ ÑÐ¾Ð²ÑÐµÐ¼ÐµÐ½Ð½ÑÐµ Ð¿Ð¾Ð´ÑÐ¾Ð´Ñ Ðº Ð¾Ð±ÑÐ°Ð±Ð¾ÑÐºÐµ Ð´Ð°Ð½Ð½ÑÑ, Ð¿Ð¾Ð·Ð²Ð¾Ð»ÑÑÑÐ¸Ðµ ÑÐ¾ÐºÑÐ°ÑÐ¸ÑÑ ÑÑÐ¸Ð»Ð¸Ñ Ð¿ÑÐ¸ Ð¸Ð½ÑÐµÐ³ÑÐ°ÑÐ¸Ð¸ Ð² ÐºÑÑÐ¿Ð½ÑÐµ ÑÐ¸ÑÑÐµÐ¼Ñ.
description: In modern road traffic safety systems important to score driver behaviour. The most researched and popular approach to solving this problem is the use of data from specialized on-board diagnostics units. The use of such devices is accompanied by a number of technical limitations and some of the vehicles are not considered. While the quality of application of modern data analysis methods is depends on the number of observations, insufficient number of system users is an important issue to consider. To increase the coverage of observations, need to research alternative non-specialized data sources. Mobile devices may be such data sources, but the use of such data for driver behaviour scoring is poorly researched. This thesis discusses preprocessing methods for data of MEMS-sensors to identify events that occurred during a vehicle trip and an approach to classifying trips based on identified events. Outcome of the thesis was program code that implements the described algorithm. As part of the development, a study is carried out of the main parameters that affect the operation of the algorithm and offers suggestions for setting them up. The algorithm is applied to data sets collected from open sources in order to conduct a study of the applicability of the method in practice. The most modern approaches to data processing were applied in the development, that allows to reduce efforts during integration of algorithm into large systems.