Parking Intention Detection via Steering and Area Data
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Solution Overview
Problem
Existing driver assistance systems for parking require manual activation and struggle to reliably detect a driver's intention to park, often relying on incomplete or misleading input variables.
Innovation Solution
A method that uses a combination of parking area information, steering input data, and situation-dependent weighting criteria to determine a parking intention probability value, automatically activating the driver assistance system when the probability exceeds a set limit.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual activation of driver assistance system is required, then system complexity is reduced, but ease of operation deteriorates
Solution Approach 1:
The driver assistance system automatically detects parking intention through analyzing driving behavior patterns (steering movements, speed changes, gear shifts) and activates itself without requiring manual input from the driver. The system serves itself by monitoring its own operational context and making autonomous activation decisions based on detected parking scenarios.
2Reliability
If simple parking intention detection is used, then device complexity is reduced, but reliability deteriorates
Solution Approach 1:
The system combines multiple detection parameters including steering angle variations, vehicle speed changes, gear shift patterns, and temporal sequences of these inputs to determine parking intention. By merging these diverse data streams and analyzing their correlations, the system achieves high reliability in detecting true parking intentions while filtering out false signals from normal driving maneuvers.
3Measurement precision
If multiple input variables are analyzed, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The detection process is segmented into distinct evaluation stages: first detecting individual driving parameters (steering, speed, gear), then analyzing temporal patterns of these parameters, and finally synthesizing a comprehensive parking intention probability. This segmented approach allows precise measurement of each parameter while managing system complexity through hierarchical processing.
4Productivity
If automatic activation is implemented, then productivity is improved, but loss of information increases
Solution Approach 1:
The system continuously monitors driving parameters and provides feedback to the activation decision algorithm. By analyzing the temporal evolution of steering movements, speed changes, and gear shifts, the system gains contextual information about driver intent. This feedback mechanism ensures that automatic activation occurs only when the accumulated information confirms a genuine parking intention, preventing premature or erroneous system activation.
Data Source
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AI summary
The invention relates to a method for assisting the parking of a motor vehicle (1) and to a motor vehicle (1) for carrying out the method. The method comprises providing (S1) at least one parking area information (20) that describes an unoccupied parking area (18) in the vicinity (14) of the motor vehicle (1), and acquiring (S2) at least one parking signal information (21) that describes an indication of the motor vehicle (1) parking in the unoccupied parking area (18). The parking signal information (21) includes steering input information (22) that describes a steering input by a driver (13) of the motor vehicle (1). Applying a situation-dependent weighting criterion (51) to the parking signal information (21), and taking into account the parking area information (20), a parking intention probability value (50) is determined (S4).If the determined parking intention probability value (50) is greater than a probability limit (52) (S4), a driver assistance system (6) is automatically activated or offered to activate (S5) to assist the parking of the motor vehicle (1) in the unoccupied parking area (18).