ADAS Target Verification via Camera Image Analysis
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Solution Overview
Problem
Existing vehicle advanced driver assistance system (ADAS) sensor inspection and calibration processes rely on operator guidance, which can lead to incorrect target selection and placement, potentially resulting in failed or inaccurate sensor alignments.
Innovation Solution
A vehicle service system that includes cameras and an optical projection system to guide target placement, coupled with a processing system that accesses a database of vehicle-specific information to verify the correct selection and placement of ADAS targets and fixtures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If operator guidance is provided for target selection, then ease of operation is improved, but reliability deteriorates due to potential operator error
Solution Approach 1:
The system captures images of the placed target using cameras, processes the images to identify target features, and compares the identified target against the expected target for the specific vehicle. This feedback loop automatically verifies correct target selection, eliminating reliance on operator judgment while maintaining ease of operation through automated validation.
Solution Approach 2:
The system performs self-verification by automatically capturing, processing, and validating target selection without requiring operator intervention for verification. The automated image processing and comparison systems serve themselves to ensure accuracy, removing the human error component from target selection validation.
2Reliability
If automated verification is implemented, then reliability is improved, but device complexity increases
Solution Approach 1:
The camera system serves multiple functions: it captures images for target verification, documents the calibration process, and provides visual records for quality assurance. This multi-functionality reduces the need for separate verification devices, minimizing added complexity while improving reliability.
Solution Approach 2:
The system replaces manual verification processes with automated image processing and computer vision algorithms. This substitution eliminates the need for complex mechanical verification devices while achieving reliable automated target selection verification through software-based solutions.
3Adaptability or versatility
If multiple vehicle-specific targets are maintained, then adaptability is improved, but loss of substance increases due to inventory requirements
Solution Approach 1:
The system uses digital copies and image representations of targets for verification purposes. Instead of requiring physical inventory of all possible vehicle-specific targets, the system captures images of the actual target and compares it against digital reference data, significantly reducing physical inventory requirements while maintaining adaptability across vehicle types.
Solution Approach 2:
The system adapts to different vehicle-specific targets by changing verification parameters and comparison criteria based on the detected target type. Rather than requiring separate verification systems for each target, the system modifies its verification approach dynamically, maintaining versatility without increasing physical inventory.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Ensures accurate selection and placement of vehicle-specific ADAS targets and fixtures, reducing the risk of operator error and ensuring the integrity of ADAS sensor alignments, while also generating records for warranty approval and audits.
Implementation Method 1
an optical projection system configured to project visible indicia, such as points or lines, onto surfaces in proximity to the structure to guide relative placement of targets and/or service fixtures
Implementation Method 2
a camera system to capture images of the placed target and/or fixture
Data Source
AI summary
A vehicle service system including a set of cameras and a processing system configured to access a database of vehicle-specific information, which includes data identifying vehicle-specific targets and/or service fixtures. The processing system is configured with a user interface to convey instructions to an operator, including the identification of vehicle-specific targets and/or service fixtures required to carry out a selected vehicle service. The processing system subsequently evaluates images acquired from the set of cameras to identify features present within the images, including placed vehicle-specific targets, from which identification of, and verification of correctly selected, vehicle-specific targets is made.