Robert bosch gmbh (20240282190). Movement Prediction for Road Users simplified abstract
Contents
Movement Prediction for Road Users
Organization Name
Inventor(s)
Faris Janjos of Stuttgart (DE)
Maxim Dolgov of Renningen (DE)
Movement Prediction for Road Users - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240282190 titled 'Movement Prediction for Road Users
Simplified Explanation:
This patent application describes a method for predicting the movement of traffic-related objects based on observations of their surroundings. The method involves mapping observations to a reduced-dimensional representation, using trained networks to predict future representations and actions, and determining dynamic state predictions for the objects.
- Trained encoder network maps observations to a reduced-dimensional representation.
- Trained prediction network predicts future representations and actions based on the initial observation and first action performed by the object.
- Dynamic state predictions are determined for the object at a future time.
Key Features and Innovation:
- Prediction of traffic-related object movement based on surroundings.
- Use of trained networks for representation mapping and prediction.
- Integration of dynamic state predictions for future time.
Potential Applications:
- Traffic management systems.
- Autonomous driving technology.
- Surveillance and security systems.
Problems Solved:
- Enhancing traffic flow efficiency.
- Improving safety on the roads.
- Anticipating and preventing accidents.
Benefits:
- Increased road safety.
- Enhanced traffic management.
- Improved efficiency in transportation systems.
Commercial Applications:
Predictive traffic analysis software for transportation companies to optimize routes and schedules.
Prior Art:
Prior research in the field of predictive modeling for traffic flow and object movement.
Frequently Updated Research:
Ongoing studies on real-time traffic prediction algorithms and object tracking technologies.
Questions about Predictive Traffic Analysis:
1. How does this method improve upon existing traffic prediction technologies? 2. What are the potential limitations of using prediction networks for traffic-related object movement forecasting?
Original Abstract Submitted
a method is for predicting movement of at least one traffic-related object based on observations of the surroundings of the object. the method includes mapping an observation of the surroundings at a first time by a trained encoder network to a representation with reduced dimensionality. the method also includes, based on a first action performed by the object at the first time and the representation, using at least one trained prediction network to determine a first representation prediction of the representation to which a future observation is likely to be mapped by the trained encoder network at a first future time, and/or determine a first action prediction of a second action that the object is likely to perform at the first future time. the method also includes determining a first dynamic state prediction for a dynamic state of the object at the first future time.
