Autonomous Vehicle Turn Signal Detection via Image Differencing
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Solution Overview
Problem
Autonomous vehicles face challenges in detecting turn signals of adjacent vehicles, which is crucial for safe navigation and lane change prediction, due to misalignment and occlusion issues in camera imagery.
Innovation Solution
A method and system that utilize image differencing and filtering to detect turn signals by aligning images, identifying changes in color and brightness, and determining temporal characteristics to indicate active turn signals, allowing for modified vehicle control strategies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image differencing is used to detect turn signals, then detection accuracy is improved, but false detections from misalignment and occlusion increase
Solution Approach 1:
The patent divides the image processing task into multiple stages: initial image differencing to identify candidate regions, followed by temporal filtering to separate true turn signals from false detections. This segmentation of the detection process allows each stage to focus on specific aspects, improving overall reliability while maintaining accuracy.
Solution Approach 2:
The patent applies temporal filtering as a preliminary action before final detection confirmation. By analyzing the temporal characteristics of brightness changes across multiple frames beforehand, the system pre-processes the data to eliminate false detections from misalignment and occlusion, ensuring that only reliable signals proceed to the detection stage.
2Reliability
If temporal filtering is applied to reduce false detections, then detection reliability is improved, but processing time increases
Solution Approach 1:
The patent applies partial temporal filtering by focusing computational resources only on candidate regions identified in the initial differencing stage, rather than processing the entire image sequence. This partial action approach maintains detection reliability while significantly reducing the overall processing time by avoiding unnecessary computations in non-candidate areas.
3Measurement precision
If multiple image processing operations are performed, then detection accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent implements dynamic processing where the level of filtering and analysis applied adapts based on the confidence level of initial detections and the characteristics of the candidate regions. This dynamic approach allows the system to maintain high detection accuracy while reducing computational complexity in scenarios where full processing is unnecessary, such as when detections are already highly confident or when processing resources are constrained.
Data Source
AI summary
Methods and systems for detecting a vehicle signal through image differencing and filtering are described. A computing device may be configured to receive a sequence of images of an identified vehicle in a vicinity of a given vehicle. The computing device may be configured to determine, based on a comparison of a first image of a pair of images of the sequence of images to a second image of the pair of images, a portion of image data exhibiting a change in color and a change in brightness between the first image and the second image of the pair of images. The computing device may be configured to determine that the portion indicates a light signal for the identified vehicle; and provide instructions to control the given vehicle based on the light signal of the identified vehicle.