Adaptive Vehicle Parking Control for Risk-Based Constraint Switching
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Solution Overview
Problem
Current autonomous driving parking technologies face limitations due to environmental factors and sensor constraints, restricting their application range and user convenience.
Innovation Solution
A method and apparatus that adaptively control the parking mode based on risk levels in the parking environment by acquiring and analyzing parking environment data and historical data, selecting appropriate constraint sets to adjust the usage mode, ensuring safety and convenience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If low-cost vision sensor and ultrasonic radar are used for memory parking, then cost is reduced, but the system cannot cope with all working conditions during parking
Solution Approach 1:
The patent implements dynamic adjustment of parking modes based on real-time environmental risk assessment. The system transitions between different parking modes (first mode with full automation, second mode with manual intervention) according to the detected risk level, making the system adaptable to varying working conditions while maintaining cost-effective sensor configuration.
Solution Approach 2:
The system changes operational parameters by adjusting the level of automation and user involvement based on environmental risk factors. When risk is low, the system operates in high-automation mode; when risk is high, it switches to manual mode, thereby adapting to different working conditions without hardware changes.
2Adaptability or versatility
If adaptive risk-based parking mode control is implemented, then application scenarios are widened, but system complexity increases
Solution Approach 1:
The patent segments the parking system into distinct operational modes (first parking mode and second parking mode) with clear boundaries and transition conditions. This segmentation manages complexity by creating discrete, well-defined states rather than continuous complex control logic.
Solution Approach 2:
The system employs feedback mechanisms by continuously monitoring environmental data and historical parking data to assess risk levels, then adjusting the parking mode accordingly. This feedback loop enables adaptive behavior while maintaining manageable system complexity through structured decision-making based on predefined risk assessments.
Data Source
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AI summary
A method and an apparatus for parking a vehicle and a medium are provided. The method comprises: acquiring parking environment data of a parking environment related to a vehicle and historical parking data in the parking environment; selecting, according to the parking environment data and the historical parking data, a constraint set for parking the vehicle from a plurality of constraint sets, the plurality of constraint sets corresponding to a corresponding parking risk level; and controlling the vehicle to park according to the selected constraint set. According to the solution of the present disclosure, the usage mode of the parking can be adaptively controlled for a risk level of the parking environment, thereby expanding the application scenarios of the parking technology.