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Driver behavior is one of the most important factors in safe mobility. In general, various driver maneuvers can be determined from acceleration of the vehicle. Physically, the acceleration and brake can be detected with longitudinal acceleration while turning and lane change can be detected with lateral acceleration. Normally, IMU (inertia measurement unit) has been designated to get these data. However, the IMU is not convenience to install in the vehicles especially as aftermarket parts. Nowadays, navigation system technologies have been much improved, both on availability and accuracy with combination of multiple navigation satellite systems. Normally, it's called Multi-GNSS (multiple global navigation satellite system). In particular, the satellite navigation systems available in this work are GPS, GLONASS, and QZSS. With decimeter precision and the update rate scale up to 10-Hz, the GNSS can be a viable alternative for driver behavior detection.

According to the recent study, Thailand has the 2nd most dangerous road in the world. Based on many researches, the driver is the main influencers of the traffic fatalities. Since the more dangerous the driver drive, the more chance of accident become. Therefore, driver’s monitoring system become one of the solutions that acceptable and reliable, especially for fleet management and public transportation. This paper’s goal is to find an algorithm that can distinguish driving behaviour based on cars’ acceleration and velocity, calling it as Risk Driving Score (RDS). The algorithm was tested by driving test by volunteers on highways with observers, who were told to rank the drivers in terms of driving risk from the 1-5 point. Meanwhile, the drivers were asked to drive in 3 different styles, normal, safety, and hurry. All drives were recorded by satellite and video data then filtered and used for the algorithm calculation.