Vehicle Imaging Control Device for Rough Road Blur Reduction
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Solution Overview
Problem
Existing imaging devices in vehicles face challenges in capturing clear images due to sudden changes in vehicle position on rough roads, leading to blurring and distortion, which complicates object recognition.
Innovation Solution
An imaging control device that estimates the future travel location of the vehicle using velocity and route data, adjusts the shutter speed and sensitivity of the imaging device based on road surface conditions, and performs imaging at the optimal time to minimize blurring and distortion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the imaging device captures images continuously on rough roads, then more images are available for analysis, but image quality deteriorates due to vehicle position changes causing blurring and distortion
Solution Approach 1:
The system performs preliminary estimation of future vehicle travel location using velocity vector and route data before capturing images. By predicting where the vehicle will be and what the road surface conditions will be, the system can pre-adjust imaging parameters and select optimal timing, thereby capturing clear images even on rough roads without sacrificing imaging frequency
Solution Approach 2:
The system dynamically adjusts imaging parameters (shutter speed, sensitivity) based on real-time road surface conditions and predicted vehicle position. The control unit modifies parameters according to the estimated rate of change in road surface height, making the imaging system adaptive to changing conditions rather than using fixed parameters
2Manufacturing precision
If the shutter speed is increased to reduce blurring from vehicle motion, then image clarity improves, but the exposure time increases causing motion blur for moving objects
Solution Approach 1:
The system changes multiple imaging parameters in combination rather than adjusting shutter speed alone. By modifying both shutter speed and sensitivity based on road surface conditions and vehicle velocity, the system achieves clear images with appropriate exposure times, compensating for the trade-off between these parameters
3Device complexity
If the imaging device uses fixed imaging parameters, then the device complexity is reduced, but the object recognition accuracy deteriorates on varying road surfaces
Solution Approach 1:
The system performs preliminary estimation of future travel location and road surface conditions before imaging. This advance preparation allows the control unit to select optimal parameters in advance, achieving high recognition accuracy without requiring complex real-time parameter adjustment mechanisms during actual imaging
Solution Approach 2:
The system uses feedback from velocity vector data, route data, and sensor-based road surface information to continuously adjust imaging parameters. The control unit modifies parameters according to the estimated rate of change in road surface height, creating a closed-loop system that maintains high recognition accuracy
Data Source
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AI summary
An imaging control device includes: a first location estimator that estimates a future location of a vehicle using an advancing direction, velocity vector, or route data of the vehicle; a surface estimator that estimates a rate of change in the road surface height in the advancing direction or the road surface state at the future location, using surface information for estimating the road surface shape or state at the future location, detected by a sensor, or an image of the road surface at the future location, captured by an imaging device; a modifier that modifies a parameter of the imaging device according to the rate of change in the road surface height in the advancing direction or the road surface state; and a controller that causes the imaging device of the vehicle to perform imaging using the modified parameter, at a timing at which the vehicle passes the future location.