Proactive Road Safety

The project aims to implement smart solutions which are proactive in anticipating safety incidents and potential accidents to take necessary corrective actions by alerting the driver on their risky driving habits rather than being reactive through conducting analysis post accidents with losses assets or even worse leading to driver’s or passengers injuries or deaths.

Below are Key main control going to be implemented:

  • Fatigue system – drivers tracking technology while feeling drowsy and being distracted while driving
  • Lane Departure warning
  • Headway Monitoring warning
  • Pedestrian Collision warning
  • Forward Collision warning
  • Harsh Braking
  • Harsh Acceleration
  • Over Revving
  • Over Speeding at Humps


  • IoT Driver Behavior (link)
  • Driver behaviour profiles for road safety analysis (link)
  • Driver Behavior Analysis for Safe Driving: A Survey (link)
  • Need data for driver behaviour analysis? Presenting the public UAH-DriveSet (link , dataset )
  • AMODO: Advanced Driving Behavior Analytics Solution (link)
Posted in Computer Vision, Projects.