18570376. Movement Prediction for Road Users simplified abstract (Robert Bosch GmbH)
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 18570376 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.
- Key Features and Innovation:**
- Prediction of traffic-related object movement based on surroundings observations.
- Mapping observations to reduced-dimensional representations.
- Use of trained networks for prediction of future representations and actions.
- Determination of dynamic state predictions for traffic-related objects.
- Potential Applications:**
This technology could be applied in autonomous driving systems, traffic management systems, and surveillance systems for monitoring traffic flow and predicting object movements.
- Problems Solved:**
This technology addresses the challenge of accurately predicting the movement of traffic-related objects based on their surroundings, which is crucial for ensuring safety and efficiency in transportation systems.
- Benefits:**
- Improved accuracy in predicting traffic-related object movements.
- Enhanced safety and efficiency in transportation systems.
- Potential for reducing traffic accidents and congestion.
- Commercial Applications:**
The technology could be utilized in autonomous vehicles, traffic control systems, smart city infrastructure, and surveillance systems for various commercial applications in transportation and urban planning.
- Prior Art:**
Prior research in the field of autonomous driving systems, computer vision, and machine learning may provide insights into similar methods for predicting object movements based on surroundings observations.
- Frequently Updated Research:**
Researchers are continuously exploring advancements in machine learning algorithms, computer vision techniques, and predictive modeling to enhance the accuracy and efficiency of predicting traffic-related object movements.
- Questions about Traffic Prediction:**
1. How does this technology improve the accuracy of predicting traffic-related object movements? 2. What are the potential real-world applications of this method in transportation systems?
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.
