Data-driven approach for anomaly detection of real GPS trajectory data

The last decade was marked by rapid growth and development of technology. One example of that is the automotive industry. This industry has made an enormous progress, and its main goal is to achieve safer and better driving. The vehicle incorporates GPS devices that send information about the current location and speed of the vehicle. Large amounts of collected data can be used in companies for tracking vehicles and various analysis and statistics. Sometimes, however, GPS data is not accurate. In this paper, the potential of real data sets will be used to analyze possible anomalies that may occur when reading GPS position of vehicles. The approach for solving this problem used in this paper consists of calculating distance and time, based on GPS measurements, then calculating average speed based on these two values, and comparing that speed with the speed given by GPS device.