Sensor Validator Monitoring Using Mutated Autonomous Vehicle Data

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Solution Overview

Problem

Existing sensor validation methods for autonomous vehicles may fail to detect erroneous sensor readings if the sensor validator itself is faulty, leading to potential safety hazards due to misalignment, excessive noise, or other sensor issues.

Innovation Solution

The method involves mutating sensor data to simulate adverse sensor events and monitoring the output of the sensor validator to determine its performance metric, such as true positive detection rate, thereby ensuring the validator's reliability.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If large volumes of sensor data are mutated at variable instances, then performance metric assessment coverage is improved, but data processing complexity increases

Engineering Contradiction:

Improveperformance metric assessmentVSAvoiddata processing system

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

Sensor data is mutated in advance to simulate adverse sensor events before validation, allowing the sensor validator to be tested with pre-prepared test cases that cover various fault conditions without requiring real-time generation of test data

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

Mutated sensor data serves as a copy or representation of actual sensor data under adverse conditions, allowing testing and performance assessment without requiring actual faulty sensor hardware or real-world hazardous scenarios

Inventive Principle:

Principle #26Copying

Data Source

PatentUS12244485B1Methods and apparatus for monitoring a sensor validator

Publication Date: 2025.03.04 WAYMO LLC

AI summary

A method includes monitoring, at a computing device, outputs of a sensor validator. Each output is generated by the sensor validator based on corresponding sensor data from a sensor coupled to an autonomous vehicle, and each output indicates whether the corresponding sensor data is associated with an event. The method also includes mutating, at the computing device, particular sensor data to generate mutated sensor data that is associated with a particular event. The method further includes determining, at the computing device, a performance metric associated with the sensor validator based on a particular output generated by the sensor validator. The particular output is based on the mutated sensor data.