Vehicle Camera Pitch Estimation for Rapid Orientation Changes
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Solution Overview
Problem
Existing methods for dynamically estimating the pitch and roll of a camera on a vehicle, such as those used in advanced driver assistance systems, fail to accurately follow rapid changes in orientation, especially during events like crossing a humpback bridge or driving over speed cushions, leading to potential errors in object localization and limited functionality.
Innovation Solution
A method that combines two pitch estimation techniques, one integrating a drift-avoidance coefficient and another based on line-marking recognition, with refinement steps to improve estimation accuracy by adjusting the drift-avoidance coefficient and considering quality thresholds, to enhance the dynamic estimation of pitch angles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a single pitch estimation method integrating drift-avoidance coefficient is used, then drift in pitch estimation is reduced, but accuracy during rapid orientation changes deteriorates
Solution Approach 1:
The patent combines two different pitch estimation methods: a first method integrating drift-avoidance coefficient for stability, and a second method using line-marking recognition for accuracy during dynamic changes. The system merges these methods by comparing their results and selecting the more reliable one based on validation conditions, thereby resolving the contradiction between drift reduction and accuracy during rapid orientation changes.
Solution Approach 2:
The system implements feedback by continuously comparing the pitch estimates from both methods and validating them against each other. When the second method's estimate deviates significantly from the first method's estimate, the system detects this discrepancy and adjusts accordingly, using the feedback loop to maintain accuracy while preserving stability.
2Productivity
If pitch estimation is performed without validation against multiple methods, then computational cost is reduced, but estimation reliability deteriorates
Solution Approach 1:
The patent applies partial validation by not always performing full cross-validation between both methods. Instead, it uses the first method as the primary estimator and only invokes the second method and comparison when specific conditions are met (e.g., when drift is detected or during dynamic events), thereby maintaining reliability while controlling computational cost through selective validation.
3Device complexity
If drift-avoidance coefficient is kept constant, then system complexity is reduced, but adaptability to different driving conditions deteriorates
Solution Approach 1:
The patent makes the drift-avoidance coefficient dynamic by adjusting it based on vehicle acceleration and relative movement detected between consecutive images. When rapid changes are detected, the coefficient is reduced to allow more aggressive pitch estimation; when conditions are stable, the coefficient is increased to prioritize drift avoidance. This dynamic adjustment maintains adaptability while managing system complexity through condition-based logic.
Data Source
AI summary
A method for estimating the pitch of a motor vehicle by an image-acquiring sensor that is located on board the motor vehicle. The method includes at least a first estimating step consisting in estimating a first pitch angle of the sensor using a first estimating method that integrates a drift-avoidance coefficient aiming to limit drift of the estimation of the first pitch angle, a second estimating step that consists in estimating a second pitch angle of the sensor, using a second estimating method, and a fourth step that consists in refining said first pitch angle by increasing the drift-avoidance coefficient to obtain a refined first pitch angle considered as output angle, if at least one first condition is validated.