Optical Feature Matching for Autonomous Vehicle Dispatch
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Solution Overview
Problem
Existing human-to-vehicle communication systems face challenges in accurately determining a user's location, especially in indoor or outdoor spaces with limited GPS accuracy due to signal reflection and attenuation by tall structures, leading to inaccuracies in dispatching autonomous vehicles.
Innovation Solution
A method utilizing a mobile computing device to capture optical images, detect image features, and match them with geospatially labeled templates to calculate the user's actual location, allowing for precise dispatch of autonomous vehicles by scanning known features within a threshold distance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS positioning system is used to determine user location, then the system is simple and provides coverage everywhere, but the location accuracy deteriorates in areas with signal reflection and attenuation by tall structures
Solution Approach 1:
The patent introduces an intermediary system consisting of optical sensors, image processing algorithms, and feature matching mechanisms that mediate between the GPS positioning system and the final location determination. This intermediary layer processes optical images to extract geometric features and calculate device orientation, thereby compensating for GPS inaccuracies in urban canyons and tall structure environments without completely replacing the GPS system
Solution Approach 2:
The patent partially replaces the mechanical/GPS-based positioning system with an optical-based positioning approach. By using optical sensors to capture images and analyzing geometric features in these images, the system substitutes radio wave-based GPS positioning with light-based visual positioning, achieving improved accuracy in GPS-challenged environments
2Measurement precision
If optical images are captured and processed to improve location accuracy, then the measurement precision improves, but the processing time and computational resources increase
Solution Approach 1:
The patent applies preliminary action by pre-processing and pre-storing geographic information data, including pre-identified geometric features and their spatial relationships. This preparation work is done in advance so that during actual positioning, the system only needs to perform feature matching rather than complete image analysis from scratch, significantly reducing processing time
Solution Approach 2:
The patent extracts only the essential geometric features from optical images that are necessary for positioning, rather than processing the entire image data. By selectively extracting key features such as building corners, road intersections, and distinctive landmarks, the system achieves accurate positioning with minimal computational overhead
Data Source
AI summary
One variation of a method for determining a location of a user includes: at a mobile computing device, receiving from the user a request for pickup by a road vehicle; accessing an optical image recorded by the mobile computing device at approximately the first time; detecting a set of image features in the optical image; accessing an approximate location of the mobile computing device from a geospatial positioning system; accessing a set of known features associated with geographic locations within a threshold distance of the approximate location; in response to detecting correspondence between a first image feature in the set of image features and a first known feature in the set of known features, extrapolating an action geographic location of the mobile computing device based on a particular geographic location associated with the particular known feature; and dispatching an autonomous vehicle to proximal the actual geographic location.