17936857. MOVING BODY PREDICTION DEVICE, TRAFFIC SAFETY SUPPORT SYSTEM, AND STORAGE MEDIUM simplified abstract (HONDA MOTOR CO., LTD.)
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 17936857 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. It includes a moving speed predictor and a collision predictor to predict the future moving speed and potential collisions of the prediction target.
- Movement state information acquirer: Acquires information about the movement state of the prediction target.
- Surrounding state information acquirer: Acquires information about the surrounding movement states of traffic participants around the prediction target.
- Confirmation state information acquirer: Acquires information about the 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: Predicts whether a collision will occur in the future based on the movement state, surrounding state information, and future 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 future moving speed of a prediction target, which can improve safety on the roads.
Benefits
The benefits of this technology include improved road safety, better traffic management, and enhanced driver assistance.
Potential Commercial Applications
The technology could be commercially applied in autonomous vehicles, smart transportation systems, and automotive safety systems.
Possible Prior Art
One possible prior art could be existing collision prediction systems in vehicles or traffic management systems.
Unanswered Questions
How accurate are the predictions made by this technology?
The accuracy of the predictions made by this technology would depend on the quality of the acquired information and the algorithms used for prediction.
What are the limitations of this technology in real-world scenarios?
The limitations of this technology could include factors such as unpredictable human behavior, adverse weather conditions, and technical malfunctions in the prediction system.
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.
