Vehicular Knowledge Layer for Efficient V2X Distribution
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Solution Overview
Problem
Current vehicle systems face inefficiencies due to redundant analysis of sensor data by multiple applications, leading to computational resource waste and limited compatibility of knowledge across different applications and vehicles, hindering effective knowledge distribution within and between vehicles.
Innovation Solution
Implementing a knowledge layer that generates knowledge in a standard format, allowing individual applications to share and distribute knowledge efficiently across vehicles via V2X communications, using knowledge inference rules and tags to ensure compatibility and timely dissemination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple applications execute redundant analysis in parallel to generate knowledge, then each application can independently produce its own knowledge, but computational resources are wasted and efficiency decreases
Solution Approach 1:
The patent merges the knowledge generation function into a centralized knowledge layer that serves all applications. Instead of each application independently analyzing sensor data, the knowledge layer performs unified analysis and distributes knowledge to multiple applications, eliminating redundant computational efforts while maintaining knowledge generation capability across all applications.
Solution Approach 2:
The knowledge layer is designed as a universal component that serves multiple applications simultaneously. It generates knowledge in a standardized format that can be consumed by different applications with varying requirements, allowing one component to fulfill multiple functions and serve the entire system rather than requiring separate analysis for each application.
2Adaptability or versatility
If applications generate knowledge in individual formats, then each application has full control over its knowledge structure, but compatibility and distribution capability across different applications and vehicles is limited
Solution Approach 1:
The patent applies parameter changes by standardizing the knowledge format parameters at the knowledge layer. Knowledge is generated with standardized schemas, data types, and structures that ensure compatibility across different applications and vehicles. This standardization transforms the variability of individual application formats into a unified parameter set that enables widespread distribution while maintaining adaptability through configurable knowledge types.
Solution Approach 2:
The knowledge layer acts as an intermediary between sensor data and applications. It translates diverse sensor inputs into standardized knowledge formats that can be consumed by multiple applications, and vice versa, applications can request knowledge in their specific formats from the standardized knowledge layer. This intermediary role resolves the compatibility issue by mediating between individual application needs and system-wide standardization.
3Speed
If knowledge is distributed without standardization, then applications can access knowledge quickly, but the capability to share knowledge across different vehicles and platforms is hindered
Solution Approach 1:
The patent implements preliminary action by pre-defining standardized knowledge schemas and formats at the knowledge layer before distribution occurs. Knowledge is generated and structured in advance using standardized templates, ensuring that when knowledge is distributed to applications or other vehicles, it is already in a compatible format. This preliminary standardization enables both fast distribution and broad compatibility without requiring format conversion during transmission.
Data Source
AI summary
The disclosure includes embodiments for generating and distributing knowledge. In some embodiments, a method for a connected endpoint includes analyzing, on an information layer, sensor data to generate a set of information that describes one or more events that occur in a roadway environment. The method includes generating, on a knowledge layer, knowledge based on the set of information according to a standard to increase a use efficiency of one or more computational resources of the connected endpoint and to improve a capability of the connected endpoint to distribute the knowledge.