Systems and Methods of Reminding Drivers of the Stalking Vehicles on the Road

The Need

In today’s world, privacy and safety are paramount. Being followed by other vehicles during driving can be unnerving and potentially dangerous, leading to privacy leakage and even significant traffic accidents. There is a pressing need for a solution that can detect abnormal following vehicles and ensure the driver’s privacy and safety.

The Technology

The Ohio State University researchers Dr. Kannan Athrey and Wei Sun have developed P2D2, a Privacy-Preserving Defensive Driving system designed to detect abnormal following vehicles. This innovative system uses sensor fusion, combining camera data to extract each following vehicle’s following time, and IMU sensors (e.g., Gyroscope) to extract our vehicle’s critical driving behavior. It leverages the space diversity of IMU sensing data to remove the artifacts of road surface conditions on critical driving behavior detection. Finally, it employs a machine learning-based anomaly detection algorithm to detect abnormal following vehicles based on the following vehicle’s following time and our vehicle’s critical driving behavior within the following time.

Commercial Applications

  • Personal Vehicles: Enhance safety and privacy for everyday drivers.
  • Fleet Management: Improve security for commercial fleets.
  • Ride-Sharing Services: Provide an added layer of safety for both drivers and passengers.
  • Law Enforcement: Aid in identifying potential stalking or suspicious behavior.


  • Enhanced Safety: Detects abnormal following vehicles, reducing the risk of accidents.
  • Improved Privacy: Protects against location tracking by identifying stalking vehicles.
  • Real-Time Alerts: Provides immediate notifications about potential threats.
  • Easy Integration: Can be integrated with existing vehicle systems.
  • High Accuracy: Experimental results show an F-1 score of 97.45% for abnormal following vehicle detection in different driving scenarios.

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