Road Surface Detection From Aligned Camera Images for Vehicle Control
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Solution Overview
Problem
Autonomous vehicles face challenges in adjusting their systems to accommodate varying road surface characteristics, which can impact safety and comfort during navigation.
Innovation Solution
A system that uses cameras to analyze road surface characteristics and provides control information to adjust vehicle settings, such as suspension and control systems, by processing images and sensor data to determine the road surface conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the autonomous vehicle uses standard vehicle control systems without road surface detection, then the device complexity is reduced, but the reliability and safety of navigation deteriorates due to inability to adapt to varying road conditions
Solution Approach 1:
The system performs preliminary detection of road surface characteristics using cameras and trained systems before the vehicle encounters problematic sections. By analyzing images of the road ahead and identifying characteristics such as ice, snow, or wet conditions in advance, the control systems can be proactively adjusted to maintain safety and stability during navigation.
Solution Approach 2:
The patent introduces an intermediary processing system that includes trained systems (machine learning models) and processing devices. This intermediary layer receives images from cameras, determines road surface characteristics, and translates this information into control adjustments for the vehicle systems, bridging the gap between visual detection and physical control responses.
2Adaptability or versatility
If the vehicle system continuously monitors and adjusts based on real-time road surface analysis, then the adaptability to road conditions improves, but the use of energy increases due to continuous camera operation and image processing
Solution Approach 1:
Instead of continuous monitoring, the system employs periodic detection by capturing images at specific intervals or when certain conditions are triggered. The trained system processes these periodic image inputs to determine road surface characteristics, allowing the vehicle to adapt to changing conditions while minimizing continuous energy consumption from cameras and processors.
Solution Approach 2:
The trained system automatically determines road surface characteristics from captured images without requiring constant human intervention or additional sensor inputs. The system serves itself by using the camera data to autonomously adjust control parameters, reducing the need for redundant sensing and processing that would increase energy consumption.
3Measurement precision
If the system processes multiple images with color information and aligns them using estimated motion, then the measurement precision of road surface characteristics improves, but the loss of time increases due to additional processing steps
Solution Approach 1:
The system performs preliminary alignment of multiple images using estimated motion parameters before feeding them to the trained system for characteristic determination. By pre-aligning the images based on predicted vehicle motion, the processing time required for accurate road surface analysis is reduced, as the trained system receives pre-processed, geometrically consistent inputs rather than raw sequential images.
4Ease of operation
If the autonomous vehicle implements comprehensive vehicle control system adjustments based on road surface characteristics, then the ride comfort improves, but the device complexity increases due to multiple control systems requiring coordination
Solution Approach 1:
The patent applies a universal approach where the trained system and processing device serve multiple functions: they analyze road surface characteristics, determine appropriate control adjustments, and interface with various vehicle control systems (steering, suspension, powertrain, braking). This multi-functional processing core reduces overall system complexity by consolidating the intelligence required for coordinating multiple control systems into a single integrated decision-making platform.
Data Source
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AI summary
Systems and methods are provided for determining a road surface characteristic. In one implementation, a system includes at least one processing device programmed to receive, from at least one camera, at least two images representative of an environment of a vehicle; align at least a portion of the at least two images using estimated motion of the vehicle; provide, to a trained system configured to determine a characteristic of the road surface, at least the aligned portions of the at least two images; receive, from the trained system, the determined characteristic of the road surface; and provide, to a vehicle control system, based on at least the determined characteristic of the road surface, control information for changing at least one setting of the vehicle control system.