Autonomous Vehicle Pickup Navigation Using Mobile Image Selection
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Solution Overview
Problem
Conventional methods for specifying pick-up or drop-off locations for autonomous vehicles, such as using addresses or geocoding systems, lack precision and can lead to inefficient navigation and user confusion, especially in unfamiliar areas, as they do not account for human sensory recognition and may result in undesirable or inconvenient locations.
Innovation Solution
An autonomous vehicle navigates to a requested position indicated by an image captured by a mobile computing device's camera, using geographic location data and image data to set a precise pick-up or drop-off location, with a graphical user interface to confirm the vehicle's arrival and allow for real-time adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If address or geocoding systems are used to specify pick-up location, then the system is simple to operate, but the location precision is insufficient
Solution Approach 1:
The patent replaces traditional text-based address input systems with an image-based visual selection system. The mobile device captures an image of the surroundings, and the user selects the pick-up location visually from the image rather than typing or searching for an address. This substitution of the interaction mechanism directly improves location precision while maintaining ease of operation.
Solution Approach 2:
The patent creates a visual copy of the physical environment through camera imaging. Instead of using abstract address coordinates, the system presents a real-time visual replica of the surroundings, allowing users to select locations based on visual recognition. This copying approach enables precise location specification through intuitive visual selection rather than complex address input.
2Reliability
If GPS coordinates are transmitted for pick-up location, then the system operates automatically, but the location may not match user intent
Solution Approach 1:
The patent implements a feedback mechanism where the captured image is displayed to the user for confirmation. The system automatically captures the image and processes it, but then provides visual feedback to the user showing the detected surroundings and proposed pick-up location. The user can review this feedback and adjust the selection if it doesn't match their intent, combining automation with user verification.
Solution Approach 2:
The system performs preliminary automatic processing of the captured image to identify potential pick-up locations and generate route information before presenting options to the user. This preliminary action reduces the user's workload while ensuring the automated processing results are verified against user intent through visual confirmation.
3Measurement precision
If visual image selection is implemented for pick-up location, then location precision is improved, but the device complexity increases
Solution Approach 1:
The patent leverages the universal functionality of the mobile device's existing camera and display components. Rather than adding specialized hardware, the system uses the device's universal imaging and visualization capabilities to enable precise location selection. This multi-functional approach improves location precision without significantly increasing device complexity.
Solution Approach 2:
The mobile device's camera and processing systems serve themselves by utilizing existing sensors and computational resources already present in the device. The image capture, processing, and display functions are all self-contained within the mobile device, eliminating the need for additional external equipment and keeping the system complexity manageable while achieving high location precision.
4Productivity
If conventional address-based navigation is used, then the system is easy to implement, but navigation efficiency is reduced
Solution Approach 1:
The patent transitions from one-dimensional text-based address input to two-dimensional visual image selection. By adding the spatial dimension of visual representation, the system enables more efficient location specification. Users can directly select locations by visual inspection of the captured image rather than navigating through text addresses or coordinates, significantly improving navigation efficiency.
Solution Approach 2:
The system changes the fundamental parameter of location specification from textual addresses to visual image coordinates. This parameter change enables more efficient navigation by allowing direct visual selection of pick-up locations. The underlying technology processes image data and extracts location information automatically, achieving high navigation efficiency through this parameter transformation.
Data Source
AI summary
An autonomous vehicle receives geographic location data defined via a mobile computing device operated by a user. The geographic location data is indicative of a device position of the mobile computing device. The autonomous vehicle also receives image data generated by the mobile computing device. The image data is indicative of a surrounding position nearby the device position. The surrounding position is selected from an image captured by a camera of the mobile computing device. A requested vehicle position (e.g., a pick-up or drop-off location) is set for a trip of the user in the autonomous vehicle based on the geographic location data and the image data. A route from a current vehicle position of the autonomous vehicle to the requested vehicle position for the trip of the user in the autonomous vehicle is generated. Moreover, the autonomous vehicle can follow the route to the requested vehicle position.