In-Cabin Drone Inspection for Autonomous Vehicle Cleanliness
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing vehicle inspection systems are inadequate in ensuring the interior cleanliness of autonomous vehicles between passenger pickups, as they lack efficient methods to detect and address stains, dirt, and trash left behind by previous passengers.
Innovation Solution
A vehicle control system incorporating an unmanned aircraft with interior cameras and image processing capabilities, which captures images of the vehicle interior, compares them to clean images, and adjusts its flight path to identify and classify stains, dirt, and trash, while communicating with a vehicle inspection system to determine necessary cleaning actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual inspection methods are used to check vehicle interior cleanliness, then the inspection process is simple to implement, but the inspection efficiency and accuracy are insufficient to detect all stains, dirt, and trash
Solution Approach 1:
The patent replaces manual mechanical inspection with an automated inspection system comprising cameras, processors, and classification algorithms. The system captures images of the vehicle interior, processes them through machine learning models to detect stains, dirt, and trash, and classifies them by type and location, thereby substituting human visual inspection with automated optical and computational systems to achieve higher precision and efficiency
Solution Approach 2:
The system creates digital copies (images) of the vehicle interior surfaces and analyzes these copies to detect contaminants. By capturing and processing visual representations of seats, floors, and other surfaces, the system can inspect the interior without physical contact, enabling repeated inspections and detailed analysis that would be difficult or time-consuming with manual methods
2Productivity
If the vehicle operates continuously without inspection, then productivity is maintained, but the passenger experience deteriorates due to poor cleanliness
Solution Approach 1:
The inspection system performs cleanliness assessment before the vehicle is dispatched to ensure it meets quality standards. By conducting inspections proactively during idle periods or between trips, the system prevents vehicles with poor cleanliness from serving passengers, thereby maintaining reliability without significantly impacting productivity through real-time monitoring and rapid classification capabilities
Solution Approach 2:
The system provides feedback on vehicle cleanliness status to operators and maintenance personnel, enabling data-driven decisions about when cleaning is required. The classification of contaminants by type, location, and severity allows for prioritized cleaning schedules that optimize both productivity and cleanliness quality, ensuring vehicles are cleaned based on actual need rather than fixed intervals
3Measurement precision
If comprehensive inspection of all vehicle surfaces is performed, then detection accuracy improves, but inspection time increases
Solution Approach 1:
The inspection system divides the vehicle interior into multiple zones or surfaces (seats, floors, windows, etc.) and inspects them systematically. The classification algorithm processes different regions independently and prioritizes areas with detected contaminants, allowing comprehensive coverage while reducing overall inspection time through parallel processing and selective focus on problematic areas
Solution Approach 2:
The system performs rapid initial scanning of all surfaces to identify areas requiring detailed inspection, then focuses computational resources on those specific regions. By conducting a preliminary partial inspection followed by targeted detailed analysis only where needed, the system achieves high detection accuracy for contaminants while minimizing total inspection time through efficient resource allocation
Data Source
AI summary
In one implementation, a method activates an unmanned aircraft inside a vehicle to capture images of the vehicle interior. The method accesses a flight path for the unmanned aircraft and receives data associated with the vehicle's current movement. The method adjusts the flight path of the unmanned aircraft to compensate for the vehicle's current movement.