Visual Pickup Location Selection for Urban Canyon Ride-Hailing
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Solution Overview
Problem
Current GPS and cellular triangulation methods for ride-hailing services face inaccuracies in urban environments due to 'urban canyons' and other environmental factors, leading to delays and missed pickups, as they struggle to accurately locate users and vehicles, especially in areas with limited sight lines and real-time changes.
Innovation Solution
A system that uses image data from a user's device to generate a 3D point cloud, identifying their location relative to known objects and suggesting alternative pickup locations based on visual and map data, ensuring accurate user and vehicle positioning and minimizing delays.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS and cellular triangulation are used to identify user location, then the system can provide location information, but the positional accuracy is limited due to urban canyons and environmental factors
Solution Approach 1:
The patent introduces image data as an intermediary to bridge the gap between GPS coordinates and actual physical location. By capturing images of surrounding environment and comparing them with map data, the system identifies landmarks and features to correct GPS inaccuracies caused by urban canyons, thereby improving positional accuracy without being directly affected by the environmental harmful factors
Solution Approach 2:
The patent replaces reliance on purely mechanical/electronic positioning systems (GPS and cellular triangulation) with an optical-based system using camera images and computer vision. This substitution allows the system to overcome the limitations of signal-based positioning in urban environments by using visual feature recognition to determine accurate location
2Measurement precision
If visual identification method is used to locate user, then pickup accuracy can be improved, but the system complexity increases due to image processing requirements
Solution Approach 1:
The patent makes the mobile device serve multiple functions: it acts as both a GPS receiver and a camera for environmental imaging. By utilizing the existing camera and processor in smartphones, the system achieves enhanced location accuracy without requiring separate dedicated imaging equipment, thereby limiting the increase in system complexity
Solution Approach 2:
The system performs preliminary image capture and processing to identify location features before the vehicle arrives. By pre-processing images and comparing them with map data to determine accurate location, the system reduces the computational burden during the actual pickup process and minimizes real-time processing requirements
3Loss of time
If alternative pickup locations are suggested based on image data, then pickup delays can be reduced, but the processing time for analyzing images increases
Solution Approach 1:
The system performs partial image processing by focusing on identifying key landmarks and features necessary for location verification, rather than analyzing every detail of the captured image. This selective processing approach reduces computation time while still achieving sufficient accuracy to suggest alternative pickup locations and reduce delays
Solution Approach 2:
The system performs preliminary comparison of captured images with pre-stored map data and landmark databases. By preparing reference data in advance and performing initial matching operations before the vehicle arrives, the system reduces the time required for final location determination and alternative pickup location suggestion
4Ease of operation
If stopping spaces are identified using image data, then pickup location suitability can be determined, but the measurement complexity increases
Solution Approach 1:
The system creates a visual copy of the environment through captured images and uses image processing to identify features such as curbs, sidewalks, and open spaces. By analyzing these visual copies rather than directly measuring physical characteristics, the system determines stopping space suitability without complex physical measurement operations
Data Source
AI summary
A system includes a processor configured to receive image data of a scene around a user location, including identification of a plurality of vehicle objects within the image. The processor is also configured to process the image data to determine where stopping spaces, not occupied by vehicle objects, exist within the image. The processor is further configured to select a determined stopping space and provide the selected stopping space to a passenger and driver to arrange a pickup location for a ride request.