Image-Based Vehicle Configuration for Accurate Automated Setup
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Solution Overview
Problem
Vehicle configuration is a time-consuming process that requires skilled personnel and is not efficiently automated, especially with the increasing complexity and variability of vehicle systems due to model, year, trim line, factory options, and connectivity features.
Innovation Solution
A vehicle configurator system using image recognition technology to capture, compare, and implement configuration settings based on vehicle images, enabling automatic configuration through networking, storage, and processing to identify and update vehicle systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual configuration process is used with skilled personnel, then configuration accuracy is maintained, but time consumption and labor requirements increase significantly
Solution Approach 1:
The vehicle configuration system performs self-identification through image capture and processing. The system automatically captures images of the vehicle, processes them through neural networks to identify vehicle features and configuration status, and applies appropriate configurations without requiring external skilled personnel intervention throughout the process.
Solution Approach 2:
The patent replaces manual mechanical inspection and configuration processes with an optical-based image recognition system. Cameras capture vehicle images, which are then processed by neural networks to automatically identify vehicle features and determine configuration status, substituting human expertise with automated visual inspection and AI analysis.
2Productivity
If automated image recognition system is implemented, then time efficiency and productivity improve, but system complexity and implementation difficulty increase
Solution Approach 1:
The neural network system is designed to handle multiple vehicle types, models, and configuration scenarios through a single unified platform. The system can identify various vehicle features (roof racks, spoilers, exhaust systems, etc.) and apply different configuration rules based on detected features, making the complex system universally applicable across diverse vehicle configurations.
Solution Approach 2:
The patent introduces an external computing device as an intermediary that handles the complex neural network processing and configuration decision-making. The vehicle itself contains minimal processing hardware (camera and basic processor), while the complex AI analysis is performed externally, reducing the complexity burden on the vehicle system while maintaining high automation capabilities.
3Adaptability or versatility
If comprehensive vehicle configuration options are supported, then system versatility and adaptability improve, but configuration management complexity increases
Solution Approach 1:
The system manages configuration complexity by dynamically adjusting processing parameters based on detected vehicle features. When specific features are identified (such as roof racks, spoilers, or exhaust systems), the system activates only the relevant configuration rules and parameters associated with those features, rather than processing all possible configuration options for every vehicle.
Solution Approach 2:
The patent applies different configuration rules and processing depths to different vehicle regions and features. Instead of uniformly processing the entire vehicle with the same level of detail, the system identifies specific features (local regions) and applies targeted configuration rules appropriate to each feature type, reducing overall management complexity while maintaining comprehensive versatility.
Data Source
AI summary
A system for vehicle systems configuration based on image recognition is disclosed. The system includes an image capturing device for obtaining images of a vehicle, networking circuitry for transmitting the images to network connected storage, and a processor for comparing the obtained images with stored images of possible vehicle configurations. Based on this comparison, the system selects a configuration setting for a vehicle system and implements this setting. The system can be used in various settings, including at the factory end-of-line, at a dealership, or by the end user of the vehicle.