Context

Driver behavior is one of the most important aspects in the design, development, and application of Advanced Driving Assistance Systems (ADAS) and Intelligent Transportation Systems (ITS), which can be affected by many factors. If you are able to measure the driving style of your staff, there is a lot of actions you can take in order to improve fleet safety, global road safety as well as fuel efficiency and emissions.

Content

• Dataset for modeling risky driver behaviors based on accelerometer (X,Y,Z axis in meters per second squared (m/s2)) and gyroscope (X,Y, Z axis in degrees per second (°/s) ) data.
• Sampling Rate: Average 2 samples (rows) per second
• Cars: Ford Fiesta 1.4, Ford Fiesta 1.25, Hyundai i20
• Drivers: 3 different drivers with the ages of 27, 28 and 37
• Driver Behaviors:
  1.Sudden Acceleration (Class Label: 1)
  2.Sudden Right Turn (Class Label: 2)
  3.Sudden Left Turn (Class Label: 3)
  4.Sudden Break (Class Label: 4)
• Best Window Size: 14 seconds
• Sensor: MPU6050
• Device: Raspberry Pi 3 Model B

Acknowledgements

Yuksel, Asim; Atmaca, Şerafettin (2020), “Driving Behavior Dataset”, Mendeley Data, V2, doi: 10.17632/jj3tw8kj6h.2

Data set is available in below link-
Click here