GNSS Correction Monitoring for ASIL Safety
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Solution Overview
Problem
Current satellite positioning systems face challenges in achieving Automotive Safety Integrity Level (ASIL) ratings, particularly when using cloud computing servers, due to interference issues between software processes and the difficulty in ensuring safety levels like ASIL A, B, C, and D, which are crucial for applications such as autonomous vehicles and IoT devices.
Innovation Solution
The system decomposes ASIL targets into lower levels, using separate parent and child processes for software components like integrity monitors and correction generators, operating on uncorrelated processors to mitigate interference and achieve ASIL ratings by combining independent checks within a cloud computing environment, ensuring freedom from interference in timing, execution, and memory.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If cloud computing servers are used for GNSS correction processing, then computational power and flexibility are improved, but software process interference and safety integrity certification become problematic
Solution Approach 1:
The system segments the GNSS correction processing into separate parent and child processes that operate independently on different processors. The parent process generates corrections while child processes monitor integrity, ensuring functional separation and eliminating software process interference. This segmentation enables cloud-based processing to achieve ASIL certification by isolating safety-critical functions from non-critical operations.
Solution Approach 2:
The patent introduces an intermediary monitoring layer that acts as a mediator between the correction generation processes and the positioning solution. Independent integrity monitor processes verify the integrity of corrections before they are applied, providing an intermediate safety check that enables cloud computing to meet ASIL requirements without compromising reliability.
2Device complexity
If multiple software processes operate on the same processor, then device complexity is reduced, but interference between processes compromises safety integrity
Solution Approach 1:
The system divides software processes into separate parent and child processes that run on different processors. Correction generation occurs on one processor while integrity monitoring occurs on another, physically separating potentially interfering processes. This segmentation maintains manageable device complexity while ensuring freedom from interference through architectural isolation.
Solution Approach 2:
The patent moves the integrity monitoring function to a different dimensional space - specifically, a separate processor dimension. Instead of running monitors on the same processor as corrections (temporal dimension only), the system utilizes multiple processors (spatial dimension), adding a new dimension of independence that eliminates interference while keeping the overall system architecture manageable.
3Reliability
If ASIL certification requirements are implemented, then safety integrity is improved, but system complexity and implementation difficulty increase
Solution Approach 1:
The patent segments the system into standardized parent and child process templates that can be certified independently. Each process type has a defined safety function and can be certified to appropriate ASIL levels separately. This segmentation reduces certification complexity by allowing modular certification of process components rather than requiring certification of the entire complex system as a monolith.
Solution Approach 2:
The system changes the parameter of process independence from a binary state (same/different processor) to a graded state based on ASIL levels. Different process combinations can achieve different ASIL levels (A, B, C, D) depending on the degree of independence implemented. This parameter change allows flexible certification paths that match the actual safety requirements of different applications, reducing unnecessary complexity.
Data Source
AI summary
A system can include a computing system and optionally a GNSS receiver. The computing system can include a correction generator, one or more correction checker, one or more correction combiner, a positioning engine, and/or any suitable components. The computing system may be designed to be free from interference between components.