Honda motor co., ltd. (20240112570). MOVING BODY PREDICTION DEVICE, LEARNING METHOD, TRAFFIC SAFETY SUPPORT SYSTEM, AND STORAGE MEDIUM simplified abstract

MOVING BODY PREDICTION DEVICE, LEARNING METHOD, TRAFFIC SAFETY SUPPORT SYSTEM, AND STORAGE MEDIUM

Organization Name

honda motor co., ltd.

Inventor(s)

Akihito Kimata of Saitama (JP)

Izumi Kondo of Saitama (JP)

Tim Puphal of Offenbach/Main (DE)

Naohiro Sakamoto of Saitama (JP)

Masaki Okumoto of Saitama (JP)

Ryohei Hirano of Saitama (JP)

MOVING BODY PREDICTION DEVICE, LEARNING METHOD, TRAFFIC SAFETY SUPPORT SYSTEM, AND STORAGE MEDIUM - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240112570 titled 'MOVING BODY PREDICTION DEVICE, LEARNING METHOD, TRAFFIC SAFETY SUPPORT SYSTEM, AND STORAGE MEDIUM

Simplified Explanation

The patent application describes a predictor for predicting the future of a prediction target in a traffic area. The predictor includes various components such as information acquirers, a traffic scene specifier, an action pattern selector, and an action predictor.

• Movement state information acquirer: Acquires information about the movement state of the target.
• Surrounding state information acquirer: Acquires information about the surrounding state of the target.
• Traffic environment information acquirer: Acquires information about the traffic environment in the area.
• Driver state information acquirer: Acquires information about the state of the driver.
• Traffic scene specifier: Specifies a traffic scene based on the acquired information.
• Action pattern selector: Selects a predicted action pattern based on the traffic scene and driver state information.
• Action predictor: Predicts future actions based on the selected action pattern.

Potential Applications

This technology could be applied in autonomous vehicles, traffic management systems, and driver assistance systems.

Problems Solved

1. Predicting future actions of targets in a traffic area. 2. Enhancing safety and efficiency in traffic environments.

Benefits

1. Improved traffic flow and safety. 2. Enhanced decision-making for autonomous vehicles. 3. Reduced accidents and traffic congestion.

Potential Commercial Applications

"Predictive Traffic Action Predictor Technology in Autonomous Vehicles"

Possible Prior Art

There may be existing technologies related to predicting future actions in traffic environments, such as predictive analytics for traffic flow optimization.

Unanswered Questions

How accurate are the predictions made by this technology?

The level of accuracy of the predictions made by this technology is not specified in the abstract. It would be important to know the reliability of the predictions for real-world applications.

What is the computational complexity of the predictor system?

The abstract does not mention the computational requirements or complexity of the predictor system. Understanding the computational resources needed would be crucial for implementation and scalability.

Original Abstract Submitted

a predictor predicts a future of a prediction target in a traffic 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, a traffic environment information acquirer configured to acquire traffic environment information, a driver state information acquirer configured to acquire driver state information, a traffic scene specifier configured to specify a traffic scene on the basis of the movement state information, the surrounding state information, and the traffic environment information, an action pattern selector configured to select, as a predicted action pattern, at least one from among a plurality of predetermined action patterns on the basis of the traffic scene and the driver state information, and an action predictor configured to predict future action on the basis of the predicted action pattern.