Autonomous Vehicle Predictive Maintenance for Component Life Cycle
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Solution Overview
Problem
Current methods for maintaining autonomous vehicles require human intervention, which is time-consuming, error-prone, and inefficient, especially as fleets grow, and do not account for the state of functioning components likely to fail soon.
Innovation Solution
Autonomous vehicles are equipped with self-monitoring and predictive maintenance systems that analyze diagnostic data to determine component health, predict failures, and autonomously route themselves for maintenance, reducing the need for human intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If human intervention is used for maintaining autonomous vehicles, then maintenance can be performed, but it is time-consuming, error-prone, and inefficient
Solution Approach 1:
The autonomous vehicle performs self-diagnosis and self-maintenance by autonomously navigating to maintenance facilities when diagnostic data indicates component issues, eliminating the need for human operators to manually monitor and dispatch vehicles for maintenance
Solution Approach 2:
The system continuously monitors diagnostic data from vehicle components and uses this feedback to determine when maintenance is needed, creating a closed-loop system that automatically responds to component degradation without human intervention
2Productivity
If human operators monitor and manage fleet maintenance, then maintenance decisions can be made, but the process is inefficient and does not account for component state
Solution Approach 1:
The system performs preliminary diagnosis by continuously analyzing diagnostic data to identify component issues before they cause failures, allowing maintenance to be scheduled proactively rather than reactively, which improves fleet efficiency by preventing breakdowns
Solution Approach 2:
The patent replaces human operator decision-making with an automated system that analyzes diagnostic data and makes maintenance decisions based on component health metrics, eliminating information loss associated with human monitoring
3Reliability
If traditional maintenance schedules are used, then maintenance can be performed, but it does not account for the state of functioning components likely to fail soon
Solution Approach 1:
The system transitions from fixed-time maintenance schedules to condition-based maintenance by monitoring diagnostic parameters such as component performance metrics and degradation patterns, allowing maintenance to be performed based on actual component state rather than predetermined intervals
Data Source
AI summary
Aspects of the disclosed technology encompass solutions for automatically managing autonomous vehicle (AV) operating and maintenance tasks, such as implementing an alternative operating mode or ordering replacement parts for an AV components. In some aspects, a process of the disclosed technology can include steps for receiving diagnostic data corresponding with an AV component, determining an estimated life cycle of the AV component, and determining whether to generate an action to implement an alternative operating mode or an order request for one or more replacement parts of the AV component, based on the estimated life cycle of the AV component. Systems and machine-readable media are also provided.