Vehicle Window Ejection Detection Using Computer Vision
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Solution Overview
Problem
The challenge in maintaining clean shared vehicles is that occupants often eject waste and debris while in motion, leading to litter and increased cleanup costs, which existing systems fail to effectively address through incentives or detection methods.
Innovation Solution
A vehicle-mounted system using computer vision to detect objects ejected through windows, generating image data to identify and associate ejected objects with the occupant, and generate littering event data to deter such behavior by alerting the occupant and enabling appropriate follow-up actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If occupants eject waste from the vehicle while in motion, then the vehicle cabin remains clean and free of debris, but litter increases along roadways and in neighborhoods
Solution Approach 1:
The system uses cameras to detect objects ejected from the vehicle, processes the video data to identify littering events, and provides feedback to fleet operators who can then assess service charges against the occupants. This feedback loop changes the consequences of ejection behavior without altering the ease of disposal.
Solution Approach 2:
The patent introduces an intermediary detection system between the occupant's ejection action and the environmental consequence. The camera system and processing unit act as intermediaries that monitor and record ejection events, enabling fleet operators to enforce penalties and thereby address the littering problem.
2Device complexity
If the vehicle operates without an ejection detection system, then the system complexity remains low, but the ability to identify and penalize littering occupants is insufficient
Solution Approach 1:
The patent extracts only the essential detection functionality needed to identify ejection events - using existing camera systems and applying specific image processing algorithms to detect objects leaving the vehicle. This extraction approach adds minimal complexity while achieving reliable detection of littering behavior.
Solution Approach 2:
The system uses video image data as a copy of the ejection event to identify and penalize occupants. By processing visual copies of the events rather than requiring direct physical intervention, the system achieves reliable detection with relatively simple equipment.
Data Source
AI summary
A method for detecting objects ejected from a cabin of a vehicle includes generating window image data of a vehicle window opening of the vehicle with a camera mounted on the vehicle; and processing the window image data with a controller operably connected to the camera to generate ejected object data corresponding to at least one object ejected from the cabin through the vehicle window opening. The method further includes associating the ejected object data with occupant data of an occupant of the vehicle with the controller.