Nvidia corporation (20240329639). GUIDING VEHICLES THROUGH VEHICLE MANEUVERS USING MACHINE LEARNING MODELS simplified abstract
Contents
GUIDING VEHICLES THROUGH VEHICLE MANEUVERS USING MACHINE LEARNING MODELS
Organization Name
Inventor(s)
Chenyi Chen of Fremont CA (US)
Artem Provodin of Highlands NJ (US)
GUIDING VEHICLES THROUGH VEHICLE MANEUVERS USING MACHINE LEARNING MODELS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240329639 titled 'GUIDING VEHICLES THROUGH VEHICLE MANEUVERS USING MACHINE LEARNING MODELS
Simplified Explanation: The patent application describes a system where a vehicle's trajectory for a maneuver is determined using sensor data and machine learning models.
Key Features and Innovation:
- Trigger signal received for vehicle maneuver.
- Sensor data used to determine recommended vehicle trajectory.
- Machine learning models compute vehicle control data.
- Control component of the vehicle receives and implements vehicle control data.
Potential Applications: This technology can be applied in autonomous vehicles, advanced driver assistance systems, and robotics for precise maneuvering and control.
Problems Solved: This technology addresses the need for accurate and efficient vehicle control during maneuvers, enhancing safety and performance.
Benefits:
- Improved vehicle maneuvering capabilities.
- Enhanced safety and precision in driving.
- Potential for reducing accidents and improving traffic flow.
Commercial Applications: The technology can be utilized in the automotive industry for self-driving cars, logistics companies for automated vehicles, and military applications for unmanned vehicles.
Prior Art: Readers can explore prior patents related to vehicle control systems, machine learning in autonomous vehicles, and sensor fusion technologies.
Frequently Updated Research: Stay updated on advancements in machine learning algorithms for vehicle control, sensor technologies for autonomous vehicles, and real-time data processing for maneuvering.
Questions about Vehicle Maneuvering Technology: 1. How does this technology improve vehicle safety during maneuvers? 2. What are the potential limitations of using machine learning models for vehicle control?
Original Abstract Submitted
in various examples, a trigger signal may be received that is indicative of a vehicle maneuver to be performed by a vehicle. a recommended vehicle trajectory for the vehicle maneuver may be determined in response to the trigger signal being received. to determine the recommended vehicle trajectory, sensor data may be received that represents a field of view of at least one sensor of the vehicle. a value of a control input and the sensor data may then be applied to a machine learning model(s) and the machine learning model(s) may compute output data that includes vehicle control data that represents the recommended vehicle trajectory for the vehicle through at least a portion of the vehicle maneuver. the vehicle control data may then be sent to a control component of the vehicle to cause the vehicle to be controlled according to the vehicle control data.
