17874025. ADAPTIVE DYNAMIC DRIVER TRAINING SYSTEMS AND METHODS simplified abstract (TOYOTA JIDOSHA KABUSHIKI KAISHA)
Contents
ADAPTIVE DYNAMIC DRIVER TRAINING SYSTEMS AND METHODS
Organization Name
TOYOTA JIDOSHA KABUSHIKI KAISHA
Inventor(s)
MINORU BRANDON Araki of Saratoga CA (US)
Michael Thompson of San Juan Capistrano CA (US)
James Dallas of Mountain View CA (US)
Yan Ming Jonathan Goh of Palo Alto CA (US)
Avinash Balachandran of Sunnyvale CA (US)
ADAPTIVE DYNAMIC DRIVER TRAINING SYSTEMS AND METHODS - A simplified explanation of the abstract
This abstract first appeared for US patent application 17874025 titled 'ADAPTIVE DYNAMIC DRIVER TRAINING SYSTEMS AND METHODS
Simplified Explanation
The patent application describes systems and methods for dynamic driver training. Here are the key points:
- Communication interface: The system includes a communication interface to receive sensor data from the vehicle. This sensor data includes driver biometric data (such as heart rate, breathing rate, etc.) and driver performance data (such as speed, acceleration, etc.).
- Driver inference circuit: The system also includes a driver inference circuit that analyzes the sensor data to infer the skill level and emotional state of the driver operating the vehicle. This inference is based on the biometric and performance data received.
- Driver training circuit: Based on the inferred skill level and emotional state of the driver, the system dynamically adjusts the driver training level. This means that the system can adapt the training program for the driver in real-time while they are operating the vehicle.
Potential applications of this technology:
- Driver education: This technology can be used in driver education programs to provide personalized and adaptive training to new drivers. It can help them improve their skills and emotional control while driving.
- Fleet management: Companies that manage a fleet of vehicles can use this technology to monitor and train their drivers. It can help improve driver performance, reduce accidents, and enhance overall fleet safety.
Problems solved by this technology:
- Lack of personalized training: Traditional driver training programs are often generic and do not consider individual differences in skill level and emotional state. This technology solves this problem by providing personalized and adaptive training based on real-time data.
- Inefficient training methods: This technology addresses the issue of inefficient training methods by dynamically adjusting the training level. It ensures that the training program is challenging enough to improve skills but not overwhelming for the driver.
Benefits of this technology:
- Improved driver safety: By providing personalized training and monitoring driver performance, this technology can help improve driver safety on the roads. It can reduce the risk of accidents and promote safer driving habits.
- Enhanced driver skills: The adaptive nature of the training program allows drivers to continuously improve their skills. This can lead to more confident and competent drivers on the road.
- Cost savings: By reducing accidents and improving driver performance, this technology can result in cost savings for individuals and companies. It can lower insurance premiums, maintenance costs, and potential legal expenses.
Original Abstract Submitted
Systems and methods are provided for dynamic driver training, and may include: a communication interface to receive sensor data, the sensor data comprising driver biometric data and driver performance data for a driver operating a vehicle; a driver inference circuit to infer a skill level and emotional state of the driver operating the vehicle; and a driver training circuit to, based on the inferred skill level and emotional state of the driver operating the vehicle, dynamically adjust a driver training level for the driver while the driver is operating the vehicle.
