Memory Parking Assist Path Generation With Error Compensation
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Solution Overview
Problem
Wide-angle cameras used in Surround View Monitors (SVM) for parking assistance systems introduce perception and positioning errors, leading to inaccurate vehicle positioning and increased risk of collisions in parking lots due to narrow roads and obstacles.
Innovation Solution
A method and apparatus that generates a safe Memory Parking Assist path by considering perception and positioning errors, using SVM wide-angle cameras to detect obstacles, predict collisions, and design avoidance and convergence paths using a detailed vehicle margin and clothoid paths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If SVM wide-angle cameras are used to capture the driving environment, then the field of view is widened and the number of cameras is reduced, but perception and positioning errors occur due to lens distortion
Solution Approach 1:
The system dynamically adjusts the vehicle margin parameter based on the curvature of the memory path. When the path curvature exceeds a threshold, the vehicle margin is increased to compensate for positioning errors caused by wide-angle lens distortion. This parameter adaptation allows the system to maintain safe parking assistance operation despite the inherent inaccuracy of wide-angle camera positioning.
2Productivity
If the vehicle follows the memory path directly, then the parking operation is simple and fast, but the vehicle may collide with obstacles due to positioning errors
Solution Approach 1:
The system performs preliminary collision prediction by comparing the memory path with detected obstacles before the vehicle executes the parking maneuver. If a potential collision is predicted based on the memory path and obstacle positions, the system proactively generates an avoidance path that deviates from the original memory path, ensuring safe operation while maintaining efficient parking completion.
Solution Approach 2:
The system continuously monitors the vehicle's actual position during parking execution and compares it with the memory path. When positioning errors cause the vehicle to deviate from the planned path or when obstacles are detected, the system provides feedback by generating real-time avoidance paths, allowing dynamic adjustment to maintain both safety and efficiency.
3Reliability
If the vehicle margin is increased to avoid collisions, then collision risk is reduced, but the path curvature requirement increases and path updates become frequent
Solution Approach 1:
The vehicle margin is implemented as a dynamic parameter that adapts to the specific parking situation. Rather than using a fixed large margin that would cause frequent path updates, the system adjusts the margin size based on path curvature and obstacle proximity. This dynamic adjustment maintains adequate collision avoidance while minimizing unnecessary path recalculations and system complexity.
Data Source
AI summary
A method and an apparatus for generating a safe Memory Parking Assist path by considering perception and positioning errors due to distortion of an SVM wide-angle camera are disclosed. The method for generating a parking path includes obtaining images around a vehicle by cameras; obtaining position of the vehicle and obstacles around the vehicle by using images; activating a Memory Parking Assist (MPA) in response to a determination that the vehicle approaches a memory path; predicting whether the vehicle collides with any of the obstacles if the vehicle tracks the memory path; determining whether the obstacles are avoidable in response to a determination that the vehicle is predicted to collide with the obstacle; and generating an avoidance path for the vehicle to avoid the obstacle and a convergence path for the vehicle to converge to the memory path.