18086924. AUTONOMOUS VEHICLE ENERGY EFFICIENCY USING DEEP LEARNING ADAPTIVE SENSING simplified abstract (Kia Corporation)
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 Sensing 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 discusses systems and methods 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 of the vehicle's surroundings.
- Adjusts sensor frequency to improve driving performance and energy efficiency.
- Utilizes a computing device within the vehicle to carry out the adjustments.
Key Features and Innovation
- Utilization of a neural network to analyze environmental factors.
- Adaptive adjustment of sensor frequency for optimal performance.
- Integration of computing device for real-time implementation of 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 based on changing environmental conditions.
Problems Solved
- Optimizes driving performance and energy consumption in autonomous vehicles.
- Enhances adaptability to different environmental factors.
- Improves overall efficiency and effectiveness of autonomous systems.
Benefits
- Increased safety and reliability of autonomous vehicles.
- Reduced energy consumption and operating costs.
- Enhanced performance in varying environmental conditions.
Commercial Applications
- Autonomous vehicle manufacturers can integrate this technology to improve the efficiency and performance of their products, attracting more customers and increasing market competitiveness.
Prior Art
Readers interested in prior art related to this technology can explore research on neural networks in autonomous vehicles, sensor frequency optimization, and energy-efficient driving systems.
Frequently Updated Research
Stay updated on advancements in neural network technology, sensor optimization algorithms, and energy-efficient autonomous systems to enhance the implementation of this patent.
Questions about Autonomous Vehicle Sensing Frequency Adjustment
How does adjusting sensor frequency impact the overall performance of autonomous vehicles?
Adjusting sensor frequency can optimize the vehicle's response to its surroundings, improving safety and efficiency.
What are the potential challenges in implementing sensor frequency adjustments in autonomous vehicles?
Challenges may include ensuring real-time data processing, maintaining system reliability, and integrating the technology seamlessly into existing autonomous systems.
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.
