17894320. COMPENSATING MISMATCH IN ABNORMAL DRIVING BEHAVIOR DETECTION simplified abstract (TOYOTA JIDOSHA KABUSHIKI KAISHA)

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COMPENSATING MISMATCH IN ABNORMAL DRIVING BEHAVIOR DETECTION

Organization Name

TOYOTA JIDOSHA KABUSHIKI KAISHA

Inventor(s)

Seyhan Ucar of Mountain View CA (US)

Emrah Akin Sisbot of Menlo Park CA (US)

Kentaro Oguchi of Mountain View CA (US)

COMPENSATING MISMATCH IN ABNORMAL DRIVING BEHAVIOR DETECTION - A simplified explanation of the abstract

This abstract first appeared for US patent application 17894320 titled 'COMPENSATING MISMATCH IN ABNORMAL DRIVING BEHAVIOR DETECTION

Simplified Explanation

The patent application describes a method for compensating for a mismatch in abnormal driving behavior detection between an ego vehicle and its human driver by presenting an amplified version of the abnormal driving behavior to the human driver.

  • Sensor data of the surrounding driving environment is acquired.
  • The acquired sensor data is analyzed to detect abnormal driving behavior by a vehicle in the surrounding driving environment.
  • If abnormal driving behavior is detected, it is classified as severe or not severe.
  • If the abnormal driving behavior is not classified as severe, an amplified version of it is presented to the human driver of the ego vehicle.

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      1. Potential Applications
  • Autonomous vehicles
  • Driver assistance systems
  • Fleet management systems
      1. Problems Solved
  • Improving safety on the road by alerting human drivers to abnormal driving behavior
  • Enhancing communication between autonomous vehicles and human drivers
  • Providing real-time feedback to drivers for better decision-making
      1. Benefits
  • Increased safety for all road users
  • Improved driver awareness and responsiveness
  • Enhanced overall driving experience


Original Abstract Submitted

Compensation can be made for mismatch in abnormal driving behavior detection between an ego vehicle and its human driver. Sensor data of a surrounding driving environment can be acquired. The acquired sensor data can be analyzed to detect abnormal driving behavior by a vehicle in the surrounding driving environment. Responsive to detecting abnormal driving behavior by the vehicle in the surrounding driving environment, the abnormal driving behavior can be classified as to whether it is severe. If the abnormal driving behavior is classified as not being severe, an amplified version of the abnormal driving behavior can be caused to be presented to the human driver of the ego vehicle.

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