Autonomous Parking Trajectory Tracking for Obstacle-Free Slot Selection
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Solution Overview
Problem
Existing autonomous parking systems face challenges in accurately tracking and navigating to designated parking spaces due to deviations in parking trajectory, obstacles, and environmental complexities, leading to failed parking attempts and potential vehicle damage.
Innovation Solution
An automatic parking method and apparatus that utilizes GPS, computer vision, and three-dimensional reconstruction to determine a target parking start point, select obstacle-free candidate parking points, and track a target parking trajectory based on user-collected data, ensuring precise parking by adjusting vehicle posture and steering angles in real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If autonomous parking systems use fixed trajectory navigation, then parking automation is achieved, but trajectory deviations cause parking failures and potential vehicle damage
Solution Approach 1:
The system continuously captures real-time images of the parking environment, detects obstacles and trajectory deviations, and dynamically adjusts the navigation path. This closed-loop feedback mechanism allows the autonomous parking system to correct trajectory errors during execution, resolving the contradiction between automation and reliability by enabling adaptive response to environmental changes.
Solution Approach 2:
The parking trajectory is transformed from a static pre-planned path to a dynamic adaptive path that adjusts in real-time based on detected obstacles and environmental conditions. The system modifies navigation parameters during execution, allowing the autonomous parking system to maintain reliability while preserving automation by responding flexibly to changing conditions.
2Adaptability or versatility
If the system selects from multiple candidate parking points, then parking flexibility increases, but obstacle detection complexity increases
Solution Approach 1:
The system divides the parking environment into multiple candidate parking points and evaluates each independently using image processing. By segmenting the detection task into discrete parking point evaluations, the system manages obstacle detection complexity while maintaining high adaptability in selecting the optimal parking location.
Solution Approach 2:
The system performs comprehensive obstacle detection across multiple candidate parking points beyond what a single-point system would require. This excessive detection approach ensures thorough safety verification for each candidate, enabling flexible parking point selection while managing complexity through systematic evaluation of each location.
3Manufacturing precision
If real-time trajectory tracking is implemented, then parking precision improves, but system complexity increases
Solution Approach 1:
The system replaces complex mechanical trajectory tracking mechanisms with computer vision-based image processing and digital image correlation techniques. By substituting physical tracking hardware with software-based image analysis, the system achieves high parking precision while reducing overall system complexity through the use of optical and computational methods.
Solution Approach 2:
The system creates a digital copy of the parking trajectory through image capture and processing, using visual information to guide navigation. This copying approach allows real-time trajectory tracking with high precision while avoiding the complexity of direct mechanical measurement systems, as the trajectory is represented and manipulated as digital image data.
Data Source
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AI summary
An automatic parking method and apparatus is disclosed. The method includes: obtaining a location point with a distance from a current location of a vehicle less than a preset distance and determining the location point as a target parking start point of the vehicle; obtaining at least one candidate parking point related to the target parking start point based on the target parking start point; selecting a target parking point without obstacles from the at least one candidate parking point, and obtaining a target parking trajectory traveling from the target parking start point to the target parking point and controlling the vehicle to track the target parking trajectory so as to park into the target parking point in accordance with the target parking trajectory.