AR Navigation Overlay for Rideshare Pickup Location Accuracy
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Solution Overview
Problem
Existing systems face challenges in accurately determining a rider's location and navigating them to a pickup point, especially in areas with distorted GPS signals, leading to inefficiencies and frustration in ridesharing services.
Innovation Solution
A system that uses a client device with a camera to capture images, compares them to a database of known images to determine the rider's location, and generates augmented reality navigation instructions to guide the rider to the pickup point, reducing reliance on GPS data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS coordinates are used to estimate rider position, then the system can provide location information, but the location accuracy deteriorates in urban canyons with tall buildings that distort satellite signals
Solution Approach 1:
The patent introduces image recognition technology as an intermediary method to determine rider location when GPS signals are unreliable. The system captures images of the surrounding environment, processes them through neural networks to identify landmarks and features, and uses these visual data to estimate the rider's position, thereby mediating between the unreliable GPS and the need for accurate location information
Solution Approach 2:
The system dynamically changes the parameter of location determination method based on GPS signal quality. When GPS reliability drops below a threshold, the system switches from GPS-based coordinate estimation to image-based visual positioning, altering the fundamental parameter of how location is measured and determined
2Measurement precision
If the system prompts riders to manually confirm their locations, then location accuracy may improve, but the ease of operation deteriorates as riders become cumbersome and frustrated
Solution Approach 1:
The system implements self-service by automatically determining rider location through image recognition without requiring manual user input. The neural network autonomously processes captured images, identifies environmental features, calculates position, and provides navigation instructions, allowing the system to serve itself in the location determination task
Solution Approach 2:
The patent replaces the mechanical interaction of manual location confirmation with an automated image processing system. Instead of requiring riders to physically interact with the interface to confirm locations, the system uses optical input (camera images) and automated computational processing to determine and confirm location automatically
3Measurement precision
If the system uses image recognition to determine location, then location accuracy improves in GPS-denied areas, but the device complexity increases due to additional camera and processing requirements
Solution Approach 1:
The patent applies multi-functionality by using the mobile device's camera not only for location determination but also for augmented reality navigation display and environmental awareness. The same imaging hardware and processing pipeline serve multiple purposes: capturing location data, generating navigation overlays, and providing visual context to the rider
Solution Approach 2:
The system merges the location determination function with the augmented reality navigation display. The image processing that determines location also generates the visual context for AR overlays, combining what was previously separate functions (GPS positioning and AR display) into an integrated visual navigation system
4Ease of operation
If the system generates augmented reality navigation instructions, then the ease of navigation improves, but the use of energy increases due to continuous camera operation and image processing
Solution Approach 1:
The system implements periodic action by capturing images at intervals rather than continuously during navigation. The neural network processes images at predetermined time intervals or when significant environmental changes are detected, reducing continuous camera operation and associated energy consumption while maintaining effective navigation guidance
Data Source
AI summary
Systems and methods are disclosed herein for monitoring a location of a client device associated with a transportation service and generating augmented reality images for display on the client device. The systems and methods use sensor data from the client device and a device localization process to monitor the location of the client device by comparing renderings of images captured by the client device to renderings of the vicinity of the pickup location. The systems and methods determine navigation instructions from the user's current location to the pickup location and select one or more augmented reality elements associated with the navigation instructions and/or landmarks along the route to the pickup location. The systems and methods instruct the client device to overlay the selected augmented reality elements on a video feed of the client device.