Vehicle Localization Data Containers for Multi-App Resource Allocation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing vehicle localization systems face inefficiencies in resource utilization, particularly in processing, memory, and bandwidth, when providing localization data to multiple applications simultaneously, which can lead to reduced performance and increased resource allocation challenges.
Innovation Solution
A vehicle localization system that utilizes a localization computer to instantiate and manage data containers, allocating resources based on application priorities, quality of service, and confidence levels, allowing for efficient provision of localization data to multiple applications while optimizing computing resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If localization data is provided to multiple applications simultaneously using existing systems, then all applications receive localization data, but resource utilization efficiency deteriorates due to redundant processing and memory allocation
Solution Approach 1:
The patent merges multiple application-specific localization data processing streams into a single unified data container that serves all applications simultaneously. This consolidation eliminates redundant processing operations and memory allocations, ensuring that localization data is delivered reliably to multiple applications while significantly reducing overall computing resource consumption.
2Adaptability or versatility
If resources are allocated to multiple applications simultaneously, then all applications can access localization data, but resource allocation complexity increases
Solution Approach 1:
The patent creates a universal data container that serves multiple applications with different localization data requirements through a single unified structure. This multi-functional container can be dynamically configured to serve various applications simultaneously, reducing resource allocation complexity while maintaining high adaptability to different application needs.
3Productivity
If processing power is increased to handle multiple applications, then localization data can be provided to all applications, but system cost and complexity increase
Solution Approach 1:
The patent uses efficient data copying mechanisms within the unified container architecture, where localization data is processed once and then distributed to multiple applications through controlled copy operations. This approach maintains high processing throughput for supporting multiple applications while avoiding the need for separate processing chains, thereby reducing overall system complexity.
Data Source
AI summary
In a vehicle computer, a trigger may be received to provide localization data to a first vehicle application that is one of a plurality of vehicle applications in a vehicle that receive the localization data. Based on the trigger, resources can be allocated to a first data container that provides the localization data in a first format specified for the application, and that is one of a plurality of data containers included in the system. The localization data can be provided in the first format to the first vehicle application upon receiving a location request from the application.