Unified Destination Entry Tiling for In-Car Speech Context Loading
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Solution Overview
Problem
Existing mapping systems face challenges in providing location-dependent information efficiently, as they often rely on large monolithic data structures that consume significant memory, and users interacting with map data through speech interfaces lack sufficient context data for accurate responses.
Innovation Solution
The system utilizes context data, referred to as 'unified destination entry data' (UDE data), which is partitioned into tiles that are dynamically loaded based on the user's location. This approach includes loading the local tile and neighborhood tiles into memory, and decomposing remote tiles into overlay tiles to optimize memory usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If context data is partitioned into tiles and dynamically loaded based on user location, then memory usage is optimized, but the complexity of data management increases
Solution Approach 1:
The patent partitions context data into discrete geographic tiles that can be independently loaded and managed. Each tile contains context information for a specific geographic region, allowing the system to load only the tiles relevant to the user's current location rather than loading all context data into memory. This segmentation directly reduces memory usage while the tile-based structure provides a manageable framework for data organization.
Solution Approach 2:
The system dynamically loads and unloads context tiles based on the user's current location and movement. As the user moves between geographic regions, the system automatically loads new tiles and unloads previously loaded tiles that are no longer needed. This dynamic approach optimizes memory usage by ensuring that only currently relevant context data resides in memory, while the underlying data structure remains organized and easily manageable through location-based criteria.
2Quantity of substance
If remote tiles are decomposed into overlay tiles, then memory usage is further optimized, but the device complexity increases
Solution Approach 1:
The patent further segments remote tiles by decomposing them into multiple overlay tiles, each representing a subset of the original remote tile's geographic area. This allows the system to load only specific portions of remote tiles that are relevant to the user's location or area of interest, rather than loading entire remote tiles. This finer-grained segmentation reduces memory usage while maintaining an organized hierarchical structure where overlay tiles can be managed independently.
Solution Approach 2:
The overlay tile structure enables the system to provide different levels of detail and information density for different geographic regions. Local tiles near the user's current location can be fully loaded with complete context information, while remote tiles can be represented by selective overlay tiles containing only the most relevant information. This local quality approach optimizes memory usage by allocating memory resources according to the importance and proximity of different geographic regions.
3Quantity of substance
If only local tile and neighborhood tiles are loaded, then memory usage is optimized, but the accuracy of speech recognition may deteriorate
Solution Approach 1:
The system loads not only the strictly necessary local tile but also additional neighborhood tiles that surround the user's current location. This partial extension beyond the minimum required data ensures that context information is available for speech recognition even when the user's location changes slightly or when referring to nearby locations. The neighborhood tiles provide a buffer zone of context data that maintains speech recognition accuracy while still limiting overall memory usage compared to loading all possible context data.
Data Source
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AI summary
In an infotainment system of a vehicle, a mass storage unit stores map data and context data. The map data comprises geographic information about a geographic area around the vehicle and the context data comprises location-dependent context information about the geographic area for use when engaging in speech interaction with an occupant of the vehicle. The context data includes subsets of context data, each of which is pertinent to a different geographic area. A memory manager copies these subsets of context data into a dynamic memory based on the vehicle's movement.