Adaptive Parking Trajectory Tolerance Control
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Solution Overview
Problem
Current semi-automatic and automatic parking systems have limited adaptability and reliability when navigating to predetermined parking spaces, as they rely on fixed tolerance values that do not account for variations in driver behavior or environmental changes, leading to potential collisions with obstacles.
Innovation Solution
A method and control unit for a transportation vehicle that dynamically adjusts tolerance values based on multiple instances of manual travel, allowing for increased deviation from a learned trajectory, thereby expanding the allowed corridor and improving path planning and reliability for automatic parking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If fixed tolerance values are used for trajectory deviation in automatic parking systems, then the system structure remains simple, but the reliability of automatic parking is reduced due to inability to account for driver behavior variations and environmental changes
Solution Approach 1:
The patent applies dynamics by transforming fixed tolerance values into dynamic, adaptive tolerance values that automatically adjust based on detected trajectory deviations from multiple manual travel instances. The control unit learns from historical data and dynamically modifies the allowed deviation corridor, enabling the system to adapt to different driver behaviors and environmental conditions without manual intervention.
Solution Approach 2:
The patent implements feedback by continuously detecting the actual trajectory during manual travel, comparing it with the stored reference trajectory, and using the detected deviations to update and expand the tolerance values for future automatic parking operations. This closed-loop feedback mechanism enables the system to learn and improve its performance over time.
2Adaptability or versatility
If multiple instances of manual travel are recorded and analyzed, then the adaptability to different driving styles improves, but the loss of time for data collection and processing increases
Solution Approach 1:
The patent applies preliminary action by pre-recording trajectory data during manual travel instances and storing it for later analysis. The system prepares the data structure and accumulates trajectory information in advance, so that when automatic parking is activated, the learned tolerance values are already available, minimizing real-time processing delays.
Solution Approach 2:
The system performs self-service by automatically detecting, storing, and analyzing trajectory deviations without requiring manual input or configuration from the driver. The control unit autonomously learns from the recorded data and adjusts the tolerance values, eliminating the need for manual system calibration or driver intervention in the learning process.
3Reliability
If tolerance values are expanded based on detected deviations, then the catch area and reliability improve, but the manufacturing precision of the parking position decreases due to increased allowed deviation
Solution Approach 1:
The patent applies local quality by implementing different tolerance values at different locations along the trajectory and in different spatial dimensions. The system expands the tolerance corridor selectively based on detected deviations, allowing greater flexibility in areas where variation is acceptable while maintaining stricter precision requirements in critical zones where accurate parking positioning is essential.
Data Source
AI summary
A method for operating a transportation vehicle, in particular, for driving the transportation vehicle into a predefined parking space, wherein a first trajectory for automated travel of the transportation vehicle into the predefined parking space is stored in a vehicle-side memory device, which trajectory has been detected during manual travel of the transportation vehicle into the predefined parking space and the first trajectory is assigned tolerance values for a deviation from the first trajectory, which is the maximum deviation by which the transportation vehicle deviates from the first trajectory during automated travel into the predefined parking space, wherein, in the case of at least one further instance of manual travel of the transportation vehicle into the predefined parking space, the further trajectory which is travelled along is detected automatically and the first trajectory and the further trajectory are compared with one another.