Autonomous Control Software Virtual Testing for Sensor-Impaired Conditions
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Autonomous and semi-autonomous vehicles face challenges in safely operating in unusual environmental conditions and with impaired sensors, leading to increased risks, as existing systems may not function properly in all environments and are prone to malfunctions.
Innovation Solution
A computer-implemented method for evaluating autonomous vehicle control software using simulated sensor data and an emulator program to mimic the vehicle's operating system, generating a quality metric for the autonomous operation feature, and determining risk levels associated with the software's performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If autonomous vehicles operate in unusual environmental conditions with impaired sensors, then the system must handle diverse and challenging scenarios, but the reliability and safety of operation deteriorate due to system malfunctions and improper functioning
Solution Approach 1:
The system performs preliminary virtual testing of autonomous control software in simulated unusual environmental conditions and sensor impairment scenarios before actual deployment. This advance testing identifies potential malfunctions and allows system improvements to be made beforehand, ensuring reliability when operating in challenging real-world conditions.
Solution Approach 2:
The system creates virtual copies of the autonomous control software and operating system in a simulated environment that replicates unusual environmental conditions and sensor impairments. This copying allows exhaustive testing of system behavior in challenging scenarios without risking actual vehicle safety, while identifying reliability issues that can be addressed in the real system.
2Measurement precision
If virtual testing with emulators and simulated sensor data is implemented, then the assessment capability and safety improvement are enhanced, but the device complexity and computational resources required increase
Solution Approach 1:
The system introduces an emulator as an intermediary layer between the autonomous control software and the actual vehicle operating system. This emulator virtualizes the operating system environment, allowing precise testing of software performance and interactions without requiring complex physical test setups or modifying the real vehicle systems extensively.
Solution Approach 2:
The system replaces physical testing infrastructure with virtualized computing environments and simulated sensor data streams. Instead of requiring complex mechanical test rigs, physical mockups, and extensive safety infrastructure, the solution uses software-based emulation and simulation to achieve precise measurement of software performance with reduced physical complexity.
Data Source
AI summary
Methods and systems for assessing, detecting, and responding to malfunctions involving components of autonomous vehicles and/or smart homes are described herein. Autonomous operation features and related components can be assessed using direct or indirect data regarding operation. Such assessment may be performed to determine the robustness of autonomous systems, including the use of virtual assessment of software components within a simulated environment. To this end, a server may retrieve one or more routines associated with autonomous operation. The server may also generate a set of test data associated with test conditions. The server may also execute an emulator that virtually simulates autonomous environment. The test data may be presented to the routines executing in the emulator to generate output data. The server may then analyze the output data to determine a quality metric.