Vehicle Boundary Detection via Edge-Based Dimension Updates
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Solution Overview
Problem
Existing autonomous driving technologies, such as automatic parking programs, rely on preprogrammed vehicle dimensions which become inaccurate when customers affix objects like bicycle racks, leading to a need for a method to accurately and automatically update vehicle dimensions.
Innovation Solution
A vehicle equipped with a camera and processor that records images, identifies edges by comparing pixels to a threshold, and updates dimensions based on these edges, enabling an automatic parking routine using the updated dimensions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If preprogrammed vehicle dimensions are used at manufacturing, then the autonomous driving system can operate with simple and reliable data, but the dimensions become inaccurate when customers affix objects like bicycle racks to the vehicle
Solution Approach 1:
The system dynamically updates vehicle dimensions by capturing images at different times and comparing them to detect changes. The processor identifies edges in captured images, calculates vehicle dimensions from these edges, and updates the stored dimension data when changes are detected, allowing the system to adapt to affixed objects while maintaining operational simplicity
Solution Approach 2:
The system uses image capture and comparison as a feedback mechanism to continuously monitor and update vehicle dimensions. By capturing images, identifying edges, calculating dimensions, and comparing with stored data, the system receives feedback about dimension changes and automatically updates its data, ensuring accuracy without requiring manual intervention
2Measurement precision
If manual updates of vehicle dimensions are performed, then accuracy can be maintained, but the system becomes more complex and requires user intervention
Solution Approach 1:
The system performs self-updating of vehicle dimensions by automatically capturing images, processing them to identify edges, calculating dimensions, and updating stored data without user intervention. The processor autonomously detects dimension changes and updates the vehicle dimension data, eliminating the need for manual measurement and input while maintaining high precision
Solution Approach 2:
The system replaces manual mechanical measurement methods with automated image processing. Instead of requiring physical measurement tools and user input, the system uses image capture devices and computational algorithms to automatically determine vehicle dimensions, reducing system complexity from the user perspective while maintaining measurement accuracy
3Measurement precision
If image processing is used to detect edges and update dimensions, then accurate real-time dimension detection is achieved, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by capturing multiple images over time and storing them for later processing. By accumulating images and only processing them when dimension updates are needed, the system reduces immediate processing time while maintaining accuracy. The comparator only processes images when changes are detected, avoiding unnecessary computation
Solution Approach 2:
The system applies partial processing by only analyzing images when dimension changes are detected rather than continuously processing all captured images. The comparator identifies whether changes exist before full dimension calculation is performed, reducing computational overhead while maintaining measurement precision when updates are actually needed
Data Source
AI summary
A vehicle includes a camera and processor(s) configured to: record images via the camera; combine the recorded images; identify edges in the combined image by comparing each pixel of the combined image to a threshold; update dimensions of the vehicle based on the identified edges; execute an automatic parking routine based on the updated dimensions.