Adaptive Memory Parking Constraints for Variable-Risk Environments
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Solution Overview
Problem
Current memory parking systems face limitations in working conditions due to the dominance of low-cost vision sensors and ultrasonic radar, making it difficult to cope with all environmental factors during parking, thereby limiting their application.
Innovation Solution
A method and apparatus for adaptive vehicle parking that involves acquiring parking environment data and historical parking data to select a constraint set based on the parking risk level, allowing the vehicle to park according to the selected constraint set, thereby adjusting the usage mode of the parking technology to suit different risk levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If low-cost vision sensors and ultrasonic radar are used, then cost is reduced, but the ability to cope with all working conditions during parking is limited
Solution Approach 1:
The system dynamically adjusts the sensor configuration based on parking risk levels. For high-risk scenarios, additional sensors are activated or supplementary detection methods are employed, while for low-risk scenarios, the basic low-cost sensor suite suffices. This dynamic adaptation resolves the contradiction by making the sensor system flexible rather than fixed.
Solution Approach 2:
The patent changes the operational parameters of the sensing system by adjusting detection thresholds, sampling frequencies, and sensor activation states based on environmental conditions and risk assessments. This allows the same hardware to perform differently across various working conditions, enhancing adaptability without increasing hardware cost.
2Device complexity
If memory parking system uses limited sensor scheme, then device complexity is reduced, but application scenarios are limited
Solution Approach 1:
The patent makes the parking control system universal by introducing a risk-level-based constraint selection mechanism that can handle diverse parking scenarios (garage parking, open lot parking, narrow space parking, etc.) using the same underlying sensor suite. The system selects appropriate constraint sets based on detected risk levels, enabling one system to serve multiple application scenarios.
Solution Approach 2:
The patent segments the parking control into multiple constraint sets (first constraint set for high risk, second constraint set for low risk), each optimized for specific working conditions. This segmentation allows the system to apply appropriate constraints for each scenario without requiring completely different sensor configurations, thus maintaining low device complexity while expanding application versatility.
Data Source
AI summary
The present disclosure provides a method for parking a vehicle, an electronic device and a medium. 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.