Autonomous Vehicle Navigation Using Embedded Image Distance
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Solution Overview
Problem
Autonomous vehicles face challenges in accurately determining road conditions and navigating around obstructions, particularly in rural areas with poor road conditions, due to the high cost and limitations of existing LIDAR technology.
Innovation Solution
A system and method that generates an embedded image using a pre-generated reference object image and an obstruction image captured by an image capturing device, determining the reference-obstruction distance, and subsequently the distance between the vehicle and the obstruction, to control navigation based on this distance, employing image processing techniques and a processing circuit with modules for distance determination, speed control, and direction control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If LIDAR technology is used to determine distance to obstructions, then measurement precision is improved, but device cost increases significantly
Solution Approach 1:
The patent uses a camera to capture images of obstructions and creates a 2D image copy of the real-world scene. This image copy is then processed to extract depth information and determine distances, replacing the need for expensive LIDAR hardware while achieving comparable measurement functionality through computational methods
Solution Approach 2:
The patent replaces the mechanical/optical LIDAR system with an electronic image processing system. Instead of using laser beams and physical sensors to measure distance, the system uses a camera to capture images and computational algorithms to derive depth information, substituting a complex mechanical measurement system with a simpler electronic and software-based solution
2Productivity
If autonomous vehicles move with constant speed without considering road conditions, then productivity is improved, but reliability deteriorates due to accidents and vehicle damage
Solution Approach 1:
The patent implements dynamic speed adjustment by continuously monitoring road conditions through image processing and modifying vehicle speed in real-time. The system transitions from static constant-speed operation to dynamic speed control that adapts to changing environmental conditions, obstacles, and road quality, thereby maintaining both productivity and reliability
Solution Approach 2:
The patent establishes a feedback loop where the camera continuously captures road condition images, the processing system analyzes these images to detect obstacles and assess road quality, and the vehicle's navigation system adjusts speed and path accordingly. This closed-loop feedback mechanism enables the vehicle to respond to changing conditions while maintaining safe operation
Data Source
AI summary
This disclosure relates generally to controlling navigation of a vehicle and more particularly to a system and method for controlling the navigation of the vehicle based on a distance between the vehicle and an obstruction.A system for controlling navigation of a vehicle is disclosed. The system comprises a processor and a memory communicatively coupled to the processor. The memory stores processor instructions, which, on execution, causes the processor to generate an embedded image comprising a pre-generated reference object image and an obstruction image. The processor further determines a reference-obstruction distance based on the embedded image, wherein the reference-obstruction distance is a distance between a reference object and an obstruction. The processor further determines a distance between the vehicle and the obstruction based on the reference-obstruction distance. The processor further controls navigation of the vehicle based on the distance between the vehicle and the obstruction.