18086924. AUTONOMOUS VEHICLE ENERGY EFFICIENCY USING DEEP LEARNING ADAPTIVE SENSING simplified abstract (Hyundai Motor Company)
Contents
- 1 AUTONOMOUS VEHICLE ENERGY EFFICIENCY USING DEEP LEARNING ADAPTIVE SENSING
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 AUTONOMOUS VEHICLE ENERGY EFFICIENCY USING DEEP LEARNING ADAPTIVE SENSING - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Key Features and Innovation
- 1.6 Potential Applications
- 1.7 Problems Solved
- 1.8 Benefits
- 1.9 Commercial Applications
- 1.10 Prior Art
- 1.11 Frequently Updated Research
- 1.12 Questions about Autonomous Vehicle Sensor Frequency Adjustment
- 1.13 Original Abstract Submitted
AUTONOMOUS VEHICLE ENERGY EFFICIENCY USING DEEP LEARNING ADAPTIVE SENSING
Organization Name
Inventor(s)
Bilal Javaid of Westland MI (US)
Tuncer Yumak of Taylor MI (US)
AUTONOMOUS VEHICLE ENERGY EFFICIENCY USING DEEP LEARNING ADAPTIVE SENSING - A simplified explanation of the abstract
This abstract first appeared for US patent application 18086924 titled 'AUTONOMOUS VEHICLE ENERGY EFFICIENCY USING DEEP LEARNING ADAPTIVE SENSING
Simplified Explanation
The patent application describes a method for adjusting the sensing frequency of sensors in an autonomous vehicle based on environmental factors to optimize driving performance and energy consumption.
- Uses a neural network to determine environmental factors affecting the vehicle.
- Adjusts sensor frequency to improve driving performance and energy efficiency.
- Utilizes a computing device within the vehicle to perform the adjustments.
Key Features and Innovation
- Utilization of a neural network to analyze environmental factors.
- Dynamic adjustment of sensor frequency for optimal performance.
- Integration of computing device to execute adjustments.
Potential Applications
This technology can be applied in various autonomous vehicles, such as self-driving cars, drones, and robots, to enhance their efficiency and performance.
Problems Solved
- Optimizes driving performance and energy consumption.
- Enhances the adaptability of autonomous vehicles to different environments.
Benefits
- Improved efficiency and performance of autonomous vehicles.
- Reduction in energy consumption and operational costs.
- Enhanced safety and reliability of autonomous systems.
Commercial Applications
- Title: "Optimized Sensor Frequency Adjustment for Autonomous Vehicles"
- This technology can be utilized by automotive companies, logistics firms, and tech companies developing autonomous systems.
- Market implications include improved competitiveness, cost savings, and enhanced customer satisfaction.
Prior Art
Research on sensor frequency adjustment in autonomous vehicles and related technologies can be found in academic journals, industry publications, and patent databases.
Frequently Updated Research
Stay updated on advancements in neural network technology, sensor optimization, and autonomous vehicle systems to enhance the effectiveness of this innovation.
Questions about Autonomous Vehicle Sensor Frequency Adjustment
How does adjusting sensor frequency impact the overall performance of autonomous vehicles?
Adjusting sensor frequency can optimize data collection, improve decision-making processes, and enhance the efficiency of autonomous vehicles.
What are the potential challenges in implementing sensor frequency adjustments in autonomous vehicles?
Challenges may include compatibility issues with existing systems, calibration requirements, and ensuring real-time responsiveness.
Original Abstract Submitted
Systems and methods are provided for adjusting a sensing frequency for one or more sensors of an autonomous vehicle (AV) is provided. The method comprises determining one or more environmental factors of a current environment of an AV, using a neural network, determining, based on the one or more environmental factors, one or more actions for adjusting driving performance and energy consumption of the AV, wherein the one or more actions comprises adjusting a sensing frequency of one or more sensors coupled to the AV, and performing, using a computing device of the AV, the one or more actions, wherein the computing device comprises a processor and a memory.
