AV Edge Diagnostics Framework for Reliable Low-Traffic Health Reporting
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Solution Overview
Problem
Existing autonomous vehicle (AV) systems face challenges in managing the health status information of numerous edge devices, which are not standardized, require custom software, and generate high volumes of data, leading to network traffic overload and difficulty in ensuring reliable diagnostics.
Innovation Solution
An edge devices diagnostics framework that includes monitors, aggregators, and diagnostics drivers to standardize health status reporting, utilize efficient communication protocols like UDP, and implement fault injection for testing, along with configuration files to simplify deployment and management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If custom software is used for each edge device to manage health status, then device-specific diagnostics can be implemented, but system complexity and deployment difficulty increase significantly
Solution Approach 1:
The patent implements a universal diagnostics framework that can handle multiple edge device types through a common architecture. The framework uses standardized interfaces and configuration files that allow different edge devices to be managed through the same software infrastructure, eliminating the need for custom software development for each device while maintaining device-specific diagnostic capabilities.
Solution Approach 2:
The framework utilizes configuration files that contain device-specific parameters and settings. By changing parameters in these configuration files rather than modifying the core software, the system can adapt to different edge device types without increasing overall system complexity or requiring custom software deployment.
2Reliability
If health status data from all edge devices is collected and transmitted, then comprehensive diagnostics are achieved, but network traffic load increases
Solution Approach 1:
The framework extracts only the essential health status parameters that are critical for diagnostics, rather than transmitting all available data from edge devices. By selecting and transmitting only the most relevant metrics, the system maintains comprehensive diagnostic capability while significantly reducing network traffic volume.
Solution Approach 2:
The system implements selective data collection where only specific health status parameters are gathered and transmitted based on diagnostic needs. This partial action approach ensures sufficient diagnostic information is obtained without the overhead of collecting and transmitting excessive data, thereby reducing network load while maintaining reliability.
3Ease of operation
If standardized health status reporting is implemented across all edge devices, then system management is simplified, but flexibility in handling device-specific protocols is reduced
Solution Approach 1:
The framework segments the health status reporting system into standardized communication protocols and device-specific configuration parameters. The standardized portion handles the core reporting mechanism across all devices, while device-specific protocols and parameters are managed through separate configuration files, allowing both standardization and flexibility to coexist.
Solution Approach 2:
Configuration files serve as an intermediary layer between the standardized reporting framework and device-specific protocols. This intermediary allows the system to maintain standardized management procedures while accommodating various device-specific communication protocols through configurable parameters without requiring changes to the core framework.
Data Source
AI summary
Vehicles, e.g., autonomous vehicles, can have sophisticated networked systems onboard. A networked system for a vehicle may include many edge devices, such as sensors, network devices, microcontrollers, boards, operating systems, etc. Many edge devices may report health status information to help vehicles achieve a certain integrity level and safety goals. The health status information may be collected and processed by a compute system to assess whether certain flags or alerts should be raised, and whether the vehicle should enter a degraded state of operation. It is not trivial to implement an effective and efficient framework that can manage many edge devices in a networked system reporting a high volume of health status information. An edge devices diagnostics framework may ensure reliable transmission of health status information, mechanisms for fault injection, and the use of configuration templates to standardize and simplify configuration of monitors for various edge devices.


