The Application of GPS-trackers Data to the Analysis of Spatial Behaviour Patterns of Drivers

The paper analyses the driving behavior and its possible applications to insurance companies tariff policy. A price tariff for a driver is designed according to his/her riskiness. Nowadays there are a lot of opportunities to measure a driver’s probability of getting into an accident. The research provides a modern approach using real-time data concerning driving patterns to make the existing system more flexible and transparent. This can be achieved by evaluating data from GPS-trackers combined with behavioral characteristics of each driver: for instance, his/her reaction when passing by the traffic-lights, speed bumps and etc. The main idea is to measure driving style as the driver’s behavior before and after passing the particular transport objects. The analysis of this metric can be achieved by implementing machine learning algorithms, which proved to be successful in the identification of car accidents. As a result, a scoring process will become more manageable and adequate.