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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.

The road accident is major concern around the world, so do Thailand. It is caused by three main factors: man, vehicle and infrastructure. The most important part that accounts the safety of vehicle is human. With experiences and careful driver, the accident could be diminished. So that the vehicle monitoring systems are the vital tools to screen out the inexperience or aggressive driver. In this paper, we state the problem about the dangerous driving behavior by monitoring lateral and longitudinal acceleration. For this purpose, the inertial measurement unit should be applied but it is inconvenient to install in the vehicle. Consequently, the vehicle monitoring system were developed based on novel consumer grade multi-satellite navigation receivers and were compared to Racelogic Video V-Box system in controlled condition tested track. The incidents were virtually detected and reviewed. The incident detection algorithm were proposed and tested alongside with receivers.