Autonomous Vehicle Self-Diagnosis for Maintenance Routing
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Solution Overview
Problem
Current autonomous rideshare vehicle maintenance requires constant human intervention for monitoring and directing vehicles to repair shops, leading to inefficiencies and potential errors as fleets grow in size or area of operation.
Innovation Solution
Autonomous vehicles equipped with sensor systems and internal computing capabilities can analyze diagnostic data to determine maintenance needs, dynamically route themselves for service, and communicate with remote computing systems to schedule maintenance without human intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If human operators constantly monitor and direct autonomous vehicles for maintenance, then maintenance decisions can be made based on quantitative and qualitative values, but human intervention becomes time-consuming and error-prone as fleet size increases
Solution Approach 1:
The autonomous vehicle performs self-diagnosis and self-directed maintenance routing. The vehicle's own computing system analyzes sensor data to determine maintenance needs and autonomously navigates to service locations, eliminating the need for continuous human monitoring and direction.
Solution Approach 2:
The vehicle continuously monitors its own operational parameters through sensor systems and uses this feedback to automatically determine when maintenance is needed. The system processes real-time data from multiple sensors to assess vehicle health and trigger maintenance procedures autonomously.
2Ease of repair
If human operators monitor and direct autonomous vehicles to repair shops, then maintenance can be performed, but the process becomes increasingly complex and resource-intensive as fleet size and area of operation expand
Solution Approach 1:
The autonomous vehicle independently manages its own maintenance by monitoring its health status, determining when service is needed, and autonomously navigating to appropriate service locations. This self-service capability eliminates the need for complex centralized fleet management systems.
Solution Approach 2:
The maintenance management function is segmented and distributed to individual vehicles rather than centralized in a fleet management system. Each vehicle independently handles its own maintenance decisions and execution, simplifying the overall system architecture.
3Extent of automation
If autonomous vehicles can dynamically route themselves for service, then human intervention is reduced, but the vehicle requires advanced navigation and communication capabilities
Solution Approach 1:
The autonomous vehicle's existing navigation and communication systems, originally designed for ride-sharing operations, are repurposed to also handle maintenance routing and service location navigation. This multi-functionality avoids adding dedicated maintenance-specific hardware or software systems.
Solution Approach 2:
The maintenance management functions are merged with the vehicle's existing autonomous driving and fleet communication infrastructure. The same sensors, processors, and communication modules used for navigation and ride operations are utilized for maintenance routing decisions.
Data Source
AI summary
Aspects of the disclosed technology encompass solutions for automatically requesting a backup vehicle for passengers of an autonomous vehicle provisioned ride-hailing service. In some aspects, a process of the disclosed technology includes steps for collecting diagnostic data relating to at least one AV operation, and analyzing the diagnostic data to determine if the AV needs maintenance. Moreover, in response to a determination that the AV needs maintenance, the process can include steps for automatically requesting a backup service for a passenger of the AV. Systems and machine-readable media are also provided.