Vehicular Vision Road Contour Detection for Pothole Alerts
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Solution Overview
Problem
Current vehicle vision systems lack effective detection of potholes and other road hazards, which can lead to vehicle damage and safety issues, and do not efficiently utilize image data from cameras and sensors to provide real-time alerts or control systems for driver assistance.
Innovation Solution
A vehicle vision system that uses CMOS cameras and image processors to detect potholes and other road hazards by analyzing the movement of leading vehicles' wheels and providing alerts or controlling suspension systems, while also incorporating thermal cameras for climate control and hazard detection, and integrating with other sensors for comprehensive data processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If vehicle vision systems use standard cameras and image processors, then basic image capture and processing is achieved, but detection of potholes and road hazards is ineffective
Solution Approach 1:
The system segments the detection task into multiple specialized components: a forward-facing camera captures road surface images, an image processor analyzes wheel movement patterns, and a separate control system integrates data from multiple sensors including thermal cameras. This segmentation allows each component to be optimized for its specific function, improving pothole detection accuracy without requiring complete system redesign.
Solution Approach 2:
The vision system is designed with multi-functionality to detect various road hazards including potholes, speed bumps, and uneven surfaces using the same camera and image processing infrastructure. The system can also detect leading vehicle wheel movements and integrate thermal camera data for comprehensive hazard detection, allowing one system to serve multiple detection purposes.
2Adaptability or versatility
If the system integrates multiple sensors and processors, then comprehensive hazard detection is achieved, but device complexity increases
Solution Approach 1:
The system merges data from multiple sensors including forward-facing cameras, thermal cameras, and image processors into a unified hazard detection framework. The control system integrates these diverse data sources to comprehensively detect various road hazards, achieving versatile detection capability through consolidation rather than separate independent systems.
Solution Approach 2:
The image processor acts as an intermediary between the camera sensors and the control system, pre-processing image data and extracting relevant features such as wheel movement patterns before passing them to the control system. This intermediary layer simplifies the integration complexity by standardizing data formats and filtering information before final hazard determination.
3Speed
If real-time image processing is performed, then real-time hazard alerts are provided, but energy consumption increases
Solution Approach 1:
The image processor operates using periodic action by capturing images at specific intervals rather than continuous processing, and by triggering intensive analysis only when potential hazards are detected in preliminary screen shots. This approach provides real-time alerts when needed while reducing overall energy consumption during normal driving conditions.
Solution Approach 2:
The system applies partial action by processing only the most critical aspects of the captured images in real-time, such as detecting wheel movement patterns and obvious road surface anomalies, while deferring less critical analysis. This selective processing maintains alert response time for hazards while minimizing energy consumption on non-urgent processing tasks.
Data Source
AI summary
A vehicular driving assist system includes a camera disposed at a vehicle equipped with the vehicular driving assist system and viewing forward of the vehicle, the camera capturing image data. An electronic control unit (ECU) includes electronic circuitry and associated software. The electronic circuitry of the ECU includes an image processor for processing image data captured by the camera. The ECU, responsive to processing by the image processor of image data captured by the camera, determines presence of a leading vehicle traveling in front of the equipped vehicle and in the same traffic lane as the equipped vehicle. The ECU, responsive to determining presence of the leading vehicle, determines presence of a pothole in front of the vehicle and in the same traffic lane as the equipped vehicle.