Autonomous Vehicle Monitoring for Control Status Assessment
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Solution Overview
Problem
As vehicles become increasingly complex with automated operation components, there is a need for systems that can autonomously monitor and assess control status in highly automated aircraft operations to provide supervisory redundancy and ensure safe and efficient decision-making, especially in complex and unexpected circumstances.
Innovation Solution
A monitoring system that receives sub-system data, contextual data, and control data from autonomous vehicles, analyzes this information to determine a control result, and provides an assessment to a management system, leveraging AI and ML to mimic human pilot monitoring functions and provide recommendations for decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If automated operation components and control systems are added to vehicles, then productivity and automation level are improved, but device complexity increases and reliability may deteriorate in unexpected circumstances
Solution Approach 1:
A monitoring system acts as an intermediary between the automated control system and the vehicle operations. This monitoring system receives data from multiple vehicle sub-systems, analyzes control decisions, and provides supervisory feedback without directly interfering with the automated control functions, thereby managing complexity while maintaining high automation levels
Solution Approach 2:
The patent implements a feedback mechanism where the monitoring system continuously receives control data and sub-system data, analyzes the control results, and provides assessments back to the control system. This closed-loop feedback enables the system to adapt and respond to unexpected circumstances while maintaining automated operation
2Ease of operation
If automated control systems are used to mimic human decision-making, then ease of operation is improved, but reliability deteriorates when systems cannot adequately respond to complex and unexpected circumstances
Solution Approach 1:
The monitoring system performs preliminary analysis of control decisions before they are executed, assessing whether the automated control system's intended actions are appropriate given the current vehicle state and contextual data. This preliminary check enhances reliability by catching potential errors before they manifest
Solution Approach 2:
The monitoring system serves as a supervisory intermediary that does not replace the automated control system but provides an additional layer of oversight. It analyzes control results and can alert operators or trigger corrective actions when the automated system's decisions are questionable, thereby improving reliability without compromising ease of operation
3Reliability
If multiple data sources and analysis layers are added to monitor autonomous vehicle operations, then reliability and safety are improved, but device complexity and processing requirements increase
Solution Approach 1:
The monitoring system is segmented into distinct functional modules: a data reception module that collects sub-system data and control data, an analysis module that processes the control results, and an assessment module that generates monitoring outputs. This segmentation manages complexity by organizing the monitoring functions into manageable, independent components
Solution Approach 2:
The monitoring system is designed as a universal platform that can monitor multiple vehicle sub-systems and control functions through a common architecture. By creating a multi-functional monitoring system that handles various data types and analysis requirements through unified processes, the patent reduces overall system complexity compared to having separate monitoring systems for each function
Data Source
AI summary
Systems and methods are disclosed for monitoring operations of an autonomous vehicle. For instance, a monitoring device receives sub-system data from one or more sub-systems of the autonomous vehicle. The device receives contextual data of the vehicle that comprises one or more situational circumstances of the vehicle during operation. The device receives control data from a control system of the vehicle and analyzes the sub-system data, the contextual data, and the control data to determine a control result. The device provides an assessment to a management system of the overall control status of the vehicle.