Automated Parking Trajectory Display With Stored Camera Map Views
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Solution Overview
Problem
Existing automated parking systems provide limited and unclear representations of the vehicle's environment, making it difficult for drivers to understand the trajectory and potential obstacles, especially in hidden or non-capturable areas, leading to potential collisions and inefficient parking maneuvers.
Innovation Solution
A method and system that uses cameras to capture and display a real-time, bird's eye view of the vehicle's environment, allowing for a comprehensive overview map with real images of the trajectory and obstacles, enabling users to adjust the path and share the data across devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If only currently captured environment objects are displayed to the driver, then the display device shows real-time sensor data, but the driver cannot see obstacles in hidden viewing ranges or understand the complete trajectory environment
Solution Approach 1:
The system performs preliminary capture and storage of environment image data before the vehicle reaches certain trajectory points. This allows the display device to show pre-captured images of obstacles or environment features that are not yet in the current sensor range, giving the driver advance information about upcoming conditions without requiring real-time sensing of those areas.
Solution Approach 2:
The system transitions from displaying only current 2D sensor capture to showing a temporal sequence of images that reconstructs the 3D trajectory environment. By combining multiple images taken at different positions along the trajectory, the system creates a comprehensive environmental view that spans beyond the immediate sensor range, effectively adding a temporal dimension to the spatial display.
2Loss of information
If the trajectory is displayed on a display device, then the driver can see the path, but the current representation does not clearly indicate which objects are non-traversable or traversable
Solution Approach 1:
The system uses color coding to differentiate between traversable and non-traversable objects in the displayed images. By assigning specific colors or color intensities to different object types, the driver can quickly identify which areas of the trajectory environment are safe to pass through and which should be avoided, without requiring detailed analysis of each image.
Solution Approach 2:
The system creates simplified graphical representations or overlays that copy essential information from the complex image data. Instead of showing raw images alone, the system generates annotated versions that highlight key features such as obstacles, drivable paths, and important environmental markers, making the trajectory information more actionable for the driver.
3Loss of information
If multiple camera images are captured and stored for the trajectory, then comprehensive environment coverage is achieved, but data storage requirements and processing complexity increase
Solution Approach 1:
The system extracts only the essential and relevant information from captured camera images for storage and display. Instead of storing complete high-resolution images for all trajectory points, the system identifies and extracts key features such as obstacle locations, drivable area boundaries, and important environmental markers, storing only this extracted information to reduce data volume while maintaining trajectory understanding.
Solution Approach 2:
The trajectory environment is divided into multiple segments or zones, with image data captured and stored selectively for each segment. This segmentation allows the system to manage large amounts of environmental data by organizing it into manageable portions, storing detailed information only where necessary while using simplified representations for less critical areas.
Data Source
AI summary
A method and a system for the at least partially automated parking of a motor vehicle, wherein a trajectory is provided, the motor vehicle is driven in an at least partially automated manner along the trajectory, and the trajectory is displayed on a display device with an overview map of an environment. Furthermore, by at least one camera, environment regions of the environment are captured as respective image data, at least some of which are saved allocated to the related environment regions, wherein at the time of display of the overview map, all of the image data saved up until this point in time are displayed in corresponding display regions on the overview map.