Vehicle Camera Priority Control for Autonomous Parking
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Solution Overview
Problem
Current autonomous driving technologies, such as remote smart parking assist, rely solely on ultrasonic sensors for parking space recognition, which limits their ability to recognize lane types and provide complete parking space information, necessitating a more advanced image recognition system for efficient autonomous parking.
Innovation Solution
A vehicle equipped with a camera system having multiple channels, an ultrasonic sensor for distance information, and a controller that matches images with masks to form map information, determines control points, and adjusts camera priority based on parking type, enabling efficient autonomous parking by converting images to a vehicle coordinate system and learning the surrounding environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If only ultrasonic sensors are used for parking space recognition, then the device complexity is reduced, but the measurement precision and completeness of parking space information deteriorates
Solution Approach 1:
The patent combines ultrasonic sensors with a multi-channel camera system to create a hybrid recognition system. The camera system includes front, rear, and side channels that work together with ultrasonic distance information to achieve complete parking space recognition, resolving the contradiction between device simplicity and measurement precision.
Solution Approach 2:
The camera system serves multiple functions: it captures images for parking space recognition, identifies lane types, provides distance information, and supports various parking modes (longitudinal, reverse diagonal, forward diagonal, rear parking). This multi-functionality improves measurement precision without proportionally increasing device complexity.
2Measurement precision
If a multi-channel camera system is used to recognize lane types and provide complete parking information, then the measurement precision improves, but the device complexity increases
Solution Approach 1:
The system dynamically adjusts camera channel priorities based on the determined parking type. The controller assigns different priorities to front, rear, and side channels depending on whether longitudinal, reverse diagonal, forward diagonal, or rear parking is being performed. This dynamic adaptation reduces the effective complexity by activating only the necessary channels for each parking scenario.
Solution Approach 2:
Different camera channels focus on specific local areas relevant to each parking type. For example, side channels prioritize recognition on the side of the vehicle for longitudinal parking, while front channels prioritize the area in front for reverse diagonal parking. This localized quality approach optimizes the system without requiring all channels to operate at full capacity simultaneously.
3Productivity
If camera priority is adjusted in real-time based on parking type, then the productivity and efficiency of autonomous parking improves, but the device complexity increases
Solution Approach 1:
The controller changes the operational parameters of the camera system by adjusting channel priorities based on the determined parking type. This parameter change allows the system to optimize its performance for different parking scenarios, improving productivity while managing complexity through software-based control rather than hardware reconfiguration.
4Measurement precision
If the recognition area of the camera is changed according to parking type, then the measurement precision improves, but the loss of information increases
Solution Approach 1:
The system performs preliminary recognition of the surrounding environment using all camera channels before determining the parking type. This preliminary action ensures that complete information is captured initially, and then the system selectively prioritizes relevant channels for the specific parking task, minimizing information loss while maintaining precision.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables efficient autonomous parking by dynamically adjusting camera recognition areas and priorities in real-time, improving parking accuracy and completeness by utilizing both visual and distance information to determine optimal control points and display boundary lines for different parking scenarios.
Implementation Method 1
a sensing device including an ultrasonic sensor and configured to obtain distance information between an object and the vehicle
Data Source
AI summary
A vehicle includes a camera unit disposed in the vehicle to have a plurality of channels and configured to obtain an image around the vehicle, the camera unit including one or more cameras, a sensing device including an ultrasonic sensor, the sensing device configured to obtain distance information between an object and the vehicle, and a controller configured to match a part of the image around the vehicle with at least one mask, form map information based on the at least one mask and the distance information, determine at least one control point based on the map information, and obtain the image around the vehicle based on a priority of the camera unit corresponding to a surrounding type of the vehicle determined based on the control point.