Vehicle Localization Data Fusion for Multi-App Resource Allocation
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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, leading to suboptimal performance and increased resource consumption.
Innovation Solution
A system that includes a localization computer with a network interface, capable of identifying and combining various localization data sources, such as map data, V2X data, and vehicle sensor data, using a data fusion procedure to output vehicle location, while prioritizing applications and data sources based on their operational needs, and utilizing machine learning to optimize resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If localization data is provided to multiple applications simultaneously using existing systems, then all applications receive necessary localization data, but resource consumption (processing, memory, bandwidth) increases and system performance decreases
Solution Approach 1:
The patent combines multiple localization data sources (GPS, map data, sensor data) into a unified localization service that serves multiple applications simultaneously. The localization computer aggregates data from various sources and distributes processed localization information to multiple applications, reducing redundant processing and resource consumption while maintaining the ability to serve all applications.
Solution Approach 2:
The localization computer is designed as a universal system that can serve multiple different applications (navigation, telematics, autonomous driving) with a single integrated localization service. This multi-functional approach allows the system to provide localization data to various applications without requiring separate dedicated systems for each application, thereby improving resource utilization and performance.
2Adaptability or versatility
If existing localization systems process data for multiple applications, then all applications get localization data, but processing, memory, and bandwidth consumption increases
Solution Approach 1:
The patent segments the localization service into modular components including data acquisition modules, data fusion modules, and distribution modules. Each module performs a specific function and can be independently optimized. This segmentation allows the system to process and distribute localization data efficiently to multiple applications without requiring all applications to consume the same computational resources simultaneously.
Solution Approach 2:
The localization system implements self-service mechanisms where the localization computer automatically manages data processing and distribution based on application requirements. The system monitors which applications need localization data and dynamically allocates resources, reducing unnecessary processing and memory consumption while ensuring all applications receive the data they need.
3Reliability
If multiple localization data sources are combined without optimization, then comprehensive localization data is available, but resource allocation becomes inefficient
Solution Approach 1:
The patent employs parameter changes by dynamically adjusting the weighting and priority of different localization data sources (GPS, map data, sensor data) based on current system conditions and application requirements. The localization computer can change parameters such as data fusion weights, processing priorities, and resource allocation levels to optimize both reliability and resource efficiency without requiring complex manual configuration.
Data Source
AI summary
A plurality of localization data sources accessible on a vehicle network in a vehicle can be identified. A plurality of active vehicle applications that request localization data provided by one or more of the localization data sources can be identified. Based on the active vehicle applications, a plurality of the localization data sources to be combined to output a vehicle location can be selected.