Honda motor co., ltd. (20240112582). MOVING BODY PREDICTION DEVICE, TRAFFIC SAFETY SUPPORT SYSTEM, AND STORAGE MEDIUM simplified abstract
Contents
- 1 MOVING BODY PREDICTION DEVICE, TRAFFIC SAFETY SUPPORT SYSTEM, AND STORAGE MEDIUM
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 MOVING BODY PREDICTION DEVICE, TRAFFIC SAFETY SUPPORT SYSTEM, AND STORAGE MEDIUM - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Unanswered Questions
- 1.11 Original Abstract Submitted
MOVING BODY PREDICTION DEVICE, TRAFFIC SAFETY SUPPORT SYSTEM, AND STORAGE MEDIUM
Organization Name
Inventor(s)
Akihito Kimata of Saitama (JP)
Tim Puphal of Offenbach/Main (DE)
Masaki Okumoto of Saitama (JP)
MOVING BODY PREDICTION DEVICE, TRAFFIC SAFETY SUPPORT SYSTEM, AND STORAGE MEDIUM - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240112582 titled 'MOVING BODY PREDICTION DEVICE, TRAFFIC SAFETY SUPPORT SYSTEM, AND STORAGE MEDIUM
Simplified Explanation
The abstract describes a predictor that predicts the future of a prediction target in a monitoring area by acquiring movement state information, surrounding state information, and confirmation state information, and using this data to predict moving speed and potential collisions.
- Movement state information acquirer: Acquires information about the movement state of the prediction target.
- Surrounding state information acquirer: Gathers information about the movement states of traffic participants around the prediction target.
- Confirmation state information acquirer: Obtains confirmation state information about the surrounding confirmation state of the driver of the prediction target.
- Moving speed predictor: Predicts the future moving speed of the prediction target based on the acquired information.
- Collision predictor: Determines whether a collision will occur in the future based on the movement state information, surrounding state information, and predicted moving speed.
Potential Applications
This technology could be applied in autonomous vehicles, traffic management systems, and driver assistance systems.
Problems Solved
This technology helps in predicting potential collisions and optimizing driving strategies to prevent accidents.
Benefits
The benefits of this technology include improved road safety, enhanced traffic flow, and reduced accidents.
Potential Commercial Applications
Potential commercial applications include integrating this technology into autonomous vehicles, traffic monitoring systems, and insurance telematics.
Possible Prior Art
One possible prior art could be predictive analytics systems used in autonomous vehicles to anticipate potential hazards on the road.
Unanswered Questions
How accurate are the collision predictions made by this technology?
The accuracy of collision predictions may vary depending on the quality of the acquired data and the algorithms used for prediction.
What is the impact of environmental factors on the performance of this predictor?
Environmental factors such as weather conditions, road conditions, and visibility may affect the accuracy of predictions made by this technology.
Original Abstract Submitted
a predictor predicts a future of a prediction target in a monitoring area. the predictor includes a movement state information acquirer configured to acquire movement state information, a surrounding state information acquirer configured to acquire surrounding state information regarding movement states of traffic participants around the prediction target, a confirmation state information acquirer configured to acquire confirmation state information regarding a surrounding confirmation state of a driver of the prediction target, a moving speed predictor configured to predict a future moving speed of the prediction target on a basis of the movement state information, the surrounding state information, and the confirmation state information, and a collision predictor configured to predict whether or not a collision will occur in a future of the prediction target on the basis of the movement state information, the surrounding state information, and the future moving speed.
