Autonomous Vehicle Fleet Visibility Assessment
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Solution Overview
Problem
Existing methods for ensuring the visibility of roadside objects, such as signs, are inefficient and prone to missed periods of reduced visibility due to changing conditions like foliage growth or new structures, requiring frequent manual inspections.
Innovation Solution
A fleet of autonomous vehicles equipped with cameras and sensors continuously assess the visibility of target objects by comparing captured images to expected images, aggregating data on visibility and conditions, and identifying when objects do not meet a threshold visibility level.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual inspection methods are used to ensure visibility of roadside objects, then visibility can be assessed, but the inspection frequency must be high which reduces efficiency
Solution Approach 1:
The system uses autonomous vehicles that automatically capture images and assess visibility of roadside objects without human intervention. The vehicles themselves perform the inspection task, eliminating the need for separate manual inspection operations and enabling continuous monitoring.
Solution Approach 2:
The patent replaces manual mechanical inspection with an automated optical system using cameras mounted on autonomous vehicles. The system captures images and uses image processing to assess visibility, substituting human inspectors with technological automation.
2Productivity
If inspection frequency is reduced to improve efficiency, then resource consumption decreases, but visibility changes may be missed reducing reliability
Solution Approach 1:
The system enables continuous visibility assessment by having autonomous vehicles regularly capture images of roadside objects during their normal operations. This continuous monitoring ensures that visibility changes are detected promptly while maintaining high inspection efficiency through automated processes.
Solution Approach 2:
The system proactively captures images and assesses visibility before problems arise. By continuously monitoring roadside objects, the system can detect visibility issues early and alert relevant parties before they become critical, maintaining both reliability and efficiency.
3Adaptability or versatility
If multiple roadside objects are monitored to improve comprehensive visibility assessment, then coverage increases, but system complexity increases
Solution Approach 1:
The system uses a universal platform - autonomous vehicles with cameras - that can monitor multiple types of roadside objects (signs, signals, markers) simultaneously. The same hardware and software infrastructure handles diverse monitoring tasks, avoiding the need for separate specialized systems for each object type.
Solution Approach 2:
The patent combines multiple monitoring functions into a single integrated system. The autonomous vehicle platform merges navigation, image capture, image processing, and visibility assessment into one unified system that handles multiple roadside objects concurrently, reducing overall system complexity.
Data Source
AI summary
A system uses a fleet of AVs to assess visibility of target objects. Each AV has a camera for capturing images of target objects. AVs provide the captured images, or visibility data derived from the captured images, to a remote system, which aggregates visibility data describing images captured across the fleet of AVs. The AVs also provide condition data describing conditions under which the images were captured, and the remote system aggregates the condition data. The remote system processes the aggregated visibility data and condition data to determine conditions under which a target object does not meet a visibility threshold.