3D Image Tile Updating Using Deviation-Based Vehicle Scheduling
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Solution Overview
Problem
Current systems for generating and updating three-dimensional (3D) map tiles of transportation networks face challenges in maintaining accuracy and timeliness, especially when active cameras are not available, as they rely on periodic updates that may not reflect real-time changes or specific areas requiring refreshment.
Innovation Solution
A method and system that utilize image deviation data to determine when image tiles need updating, scheduling vehicles with sensors to capture new data, and employing a prioritization model to ensure accurate map refreshment by identifying and updating tiles based on change thresholds and metadata analysis, allowing for efficient updating of virtual reality maps within transportation networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If periodic updates are used to refresh map tiles, then system complexity is reduced, but map accuracy and timeliness deteriorate
Solution Approach 1:
The system implements feedback mechanisms by continuously monitoring image deviation data and comparing current sensor data with existing map tiles. This feedback loop enables the system to detect changes and trigger updates only when necessary, maintaining high map accuracy while avoiding unnecessary updates that would increase system complexity and resource consumption.
Solution Approach 2:
The system transitions from static periodic updates to dynamic on-demand updates. Update frequency and timing are adjusted dynamically based on detected changes in the environment, traffic conditions, and image deviation thresholds. This dynamic approach optimizes the balance between map accuracy and system complexity by adapting update behavior to actual needs.
2Measurement precision
If active cameras are deployed in all areas, then map accuracy is improved, but system cost and complexity increase
Solution Approach 1:
The system makes existing vehicles multi-functional by equipping them with sensors for both their primary transportation function and map updating function. Vehicles already operating in the network capture images and contribute to map updates during their normal routes, eliminating the need for dedicated camera infrastructure while maintaining map accuracy.
Solution Approach 2:
The system enables vehicles to self-contribute to map maintenance by capturing images during their normal operations. Vehicles automatically detect changes in their environment and contribute updated imagery without requiring dedicated monitoring infrastructure, reducing system complexity while improving map accuracy through distributed data collection.
3Reliability
If full map refreshes are performed frequently, then map currency is improved, but resource consumption and time loss increase
Solution Approach 1:
The system segments the map into individual tiles and processes updates at the tile level rather than refreshing the entire map. This allows selective updating of only those tiles that have changed, significantly reducing update time and resource consumption while maintaining map currency through targeted refreshes based on image deviation detection.
Solution Approach 2:
The system performs partial updates by refreshing only the specific map tiles that require updating based on detected changes. This partial action approach avoids the excessive time and resource consumption of full map refreshes while ensuring that currency is maintained for areas that actually need updates, optimizing the balance between reliability and time loss.
4Productivity
If selective tile updates are implemented, then resource efficiency is improved, but system complexity increases
Solution Approach 1:
The system performs preliminary analysis by examining image deviation data and comparing sensor images with existing map tiles before executing updates. This preliminary action identifies which tiles require updating, enabling selective refreshes that improve resource efficiency. The complexity introduced by this selection process is offset by the elimination of unnecessary full map refreshes, resulting in net resource savings.
Data Source
AI summary
A method may include examining image deviation data of image tiles of a set that form a set view of a volume of space and determining whether the tiles are due for revision to update the tiles. The method may include scheduling a first vehicle to capture updated image tiles and/or identifying a second vehicle to capture the updated image tiles. A system may include one or more processors to examine image deviation data of image tiles of a set that form a set view of a volume of space and determine whether the one or more image tiles of the set are due for revision to update the view. The one or more processors schedule a first vehicle to move through or by the volume of space to capture one or more updated image tiles or identify a second vehicle to capture the one or more updated image tiles.