Vehicle Motion Detection via Wheel Angular Displacement
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Solution Overview
Problem
Existing autonomous vehicle perception systems face challenges in accurately detecting the motion of slow-moving vehicles, particularly in complex environments, due to susceptibility to signal noise and difficulties in distinguishing motion from static objects.
Innovation Solution
A method and system that analyze the movement of a vehicle's wheel by tracking image features over time, calculating the angular distance between initial and subsequent wheel positions, and generating a signal to indicate vehicle motion, using sensors like cameras and computing devices to enhance detection accuracy and safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional perception systems are used to detect vehicle motion, then the system can operate with standard sensors, but the detection accuracy for slow-moving vehicles deteriorates due to signal noise and inability to distinguish motion from static objects
Solution Approach 1:
The patent segments the wheel into multiple distinguishable portions or features (such as spokes, tire treads, or other characteristic elements) and tracks the movement of these segmented features individually. By analyzing the angular displacement of specific wheel portions between sequential images, the system can accurately detect slow-moving vehicles even in the presence of signal noise, as the segmented approach allows for more precise measurement of small rotational changes.
2Device complexity
If standard motion detection methods are used, then the system implementation remains simple, but the ability to distinguish motion from static objects deteriorates in complex environments
Solution Approach 1:
The patent introduces an intermediary analysis step that focuses specifically on the wheel portion's angular position as a mediator between the raw image data and the motion detection conclusion. By calculating the angular distance of a specific wheel portion between sequential images, the system creates an intermediate measurement that clearly indicates motion when the vehicle moves, while remaining objects show no angular change. This intermediary approach enhances motion distinction accuracy without significantly increasing overall system complexity.
Data Source
AI summary
Aspects of the disclosure relate to detecting vehicle movement. For example, one or more computing devices may receive first image data representative of a vehicle's wheel and second image data representative of the wheel captured subsequent to the capture of the first image data. The one or more computing devices may determine a first location of a first portion of the wheel based on the first image data, and a second location of the first portion of the wheel based on the second image data. The one or more computing devices may calculate a value based on the angular distance between the first location and the second location of the first portion, and based on the value, determine whether the vehicle is in motion. Upon determining the vehicle is in motion the one or more computing devices may provide a signal that the vehicle is in motion.