Amirkabir University of Technology Amirkabir Journal of Mechanical Engineering 2008-6032 53 Issue 6 (Special Issue) 2021 08 23 Analyzing driving behavior based on vehicle information logging using MPU6050 Analyzing driving behavior based on vehicle information logging using MPU6050 3855 3874 4285 10.22060/mej.2021.18910.6916 FA Amir Ayat K. N. Toosi University of Technology Amir Taghavipour خواجه نصیرالدین طوسی-مهندسی مکانیک Journal Article 2020 08 26 <strong>The most important factor in car accidents and even traffic congestion is the driving behavior of human. Analyzing the driving behavior and applying restrictions on risk-making drivers can reduce probable causalities and improve transportation safety. A hardware can collect the data related to the driving conditions and processes that information that may be useful in this regard. By analyzing the information recorded by the hardware, one can obtain an approximate prospective of the driving behavior. This prospective can distinguish a careful driver from a careless one. By collecting various data in different conditions, the accuracy of these criteria will be improved. On the other hand, the accuracy of different components of the hardware is crucial since the unexpected noises deteriorate the performance of data collection. In this research, a data analysis module is developed to record the acceleration and angular velocity of a sample vehicle to identify the driving behavior and propose quantitative criteria to distinguish aggressive and cautious drivers. In this way, one can figure out if his/her driving habits are dangerous or not.</strong> <strong>The most important factor in car accidents and even traffic congestion is the driving behavior of human. Analyzing the driving behavior and applying restrictions on risk-making drivers can reduce probable causalities and improve transportation safety. A hardware can collect the data related to the driving conditions and processes that information that may be useful in this regard. By analyzing the information recorded by the hardware, one can obtain an approximate prospective of the driving behavior. This prospective can distinguish a careful driver from a careless one. By collecting various data in different conditions, the accuracy of these criteria will be improved. On the other hand, the accuracy of different components of the hardware is crucial since the unexpected noises deteriorate the performance of data collection. In this research, a data analysis module is developed to record the acceleration and angular velocity of a sample vehicle to identify the driving behavior and propose quantitative criteria to distinguish aggressive and cautious drivers. In this way, one can figure out if his/her driving habits are dangerous or not.</strong> https://mej.aut.ac.ir/article_4285_63cb524a9f51b7858733e1108bf556fa.pdf