Vehicle Periphery Monitoring Parallax Variation Rate Distance Calculation
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Solution Overview
Problem
Existing vehicle periphery monitoring devices face errors in calculating distances to target objects due to parallax offsets caused by vehicle vibrations and mounting inaccuracies, which deteriorate the accuracy of determining contact possibilities, especially at longer distances.
Innovation Solution
A vehicle periphery monitoring device that calculates distance based on parallax variation rates and vehicular velocity, using a first distance calculating unit to eliminate parallax offsets and a second unit to validate distances, with reliability determination to stop monitoring when significant offsets occur, ensuring precise distance calculation and preventing false alarms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If distance calculation is performed using parallax between image sections from two cameras, then distance measurement capability is provided, but measurement precision deteriorates due to parallax offsets caused by vehicle vibrations and mounting inaccuracies
Solution Approach 1:
The patent transitions from using static parallax values to dynamic parallax variation rates. By calculating how parallax changes over time (parallax variation rate), the system can distinguish between actual distance changes and spurious variations caused by vibrations or mounting errors, thereby improving measurement precision while maintaining reliability.
Solution Approach 2:
The system uses the parallax variation rate as a feedback mechanism to validate distance calculations. By continuously monitoring how parallax changes and comparing it against expected motion models, the system can detect and correct erroneous distance measurements caused by vibrations or mounting inaccuracies, thus improving both precision and reliability.
2Measurement precision
If parallax offset correction is implemented using parallax variation rates, then distance calculation accuracy is improved, but device complexity increases due to additional calculation units and processing steps
Solution Approach 1:
The parallax variation rate calculation unit serves multiple functions: it calculates the rate of change of parallax, validates distance measurements, detects vehicle motion state, and determines when to trust raw parallax data versus corrected data. This multi-functionality reduces the need for separate dedicated units, thereby limiting the increase in device complexity while achieving improved accuracy.
Solution Approach 2:
The system changes the parameter used for distance calculation from static parallax value to dynamic parallax variation rate. This parameter transformation allows the same calculation unit to handle both raw distance measurement and vibration correction without requiring entirely separate processing paths, thus improving accuracy with moderate complexity increase.
3Productivity
If monitoring continues when parallax offsets occur, then continuous monitoring capability is maintained, but false alarms increase due to inaccurate distance measurements
Solution Approach 1:
The reliability determination unit uses feedback from the parallax variation rate calculation to dynamically adjust monitoring behavior. When parallax variation rates indicate vibration or mounting error conditions, the system suspends contact possibility determination to avoid false alarms, while resuming normal monitoring when parallax data becomes reliable, thus maintaining both continuity and accuracy.
Solution Approach 2:
The system dynamically adjusts the monitoring state based on real-time parallax characteristics. Rather than continuous rigid monitoring, the system transitions between active monitoring and suspended monitoring based on whether parallax offsets are detected, allowing continuous operational capability while preventing false alarms during unreliable measurement conditions.
Data Source
AI summary
A vehicle periphery monitoring device includes: a parallax calculating unit which extracts a first image section that contains a target object in real space from a first image imaged by a first imaging unit at a predetermined time and extracts a second image section correlated to the first image section from a second image imaged by a second imaging unit at the predetermined time, and then calculates the parallax between the first image section and the second image section; a parallax gradient calculating unit for calculating a parallax gradient based on a time series calculation of the parallax of the identical target object in real space by the parallax calculating unit; and a first distance calculating unit for calculating the distance from the vehicle to the target object on the basis of the parallax gradient and the velocity of the vehicle.