Automatic Parking Fault-Code Data Capture for Real-Time Diagnosis
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Solution Overview
Problem
Existing methods for collecting fault data in automatic parking systems are limited, making real-time diagnosis and optimization challenging due to indirect and incomplete user feedback, and the lack of comprehensive data collection across diverse user environments.
Innovation Solution
An abnormal data collecting method that automatically triggers data collection based on pre-configured fault codes, using a matching module to determine a data collecting strategy that includes data type, format, and duration, allowing for the collection of high-quality data before and after fault occurrence, without user interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If users remotely feedback fault information through online channels, then fault reporting is enabled, but the data is indirect and lacks first-hand information for effective diagnosis and optimization
Solution Approach 1:
The system pre-configures fault codes and data collecting strategies before faults occur. When a fault is detected, the corresponding data collection strategy is automatically executed, ensuring high-quality first-hand data is captured immediately without requiring user action or manual data gathering procedures.
Solution Approach 2:
The automatic parking system performs self-diagnosis by monitoring its own fault codes and automatically collects relevant data according to pre-configured strategies. This eliminates the need for users to manually report faults and ensures the system gathers its own diagnostic data directly from the source.
2Measurement precision
If comprehensive fault data collection is implemented across diverse user environments, then diagnostic accuracy improves, but the system complexity and implementation difficulty increase
Solution Approach 1:
The data collection system is segmented into modular components: fault code monitoring modules, data collecting strategies, and execution modules. Each module handles specific aspects of data collection, making the overall system manageable despite its comprehensiveness. The segmentation allows the system to collect diverse data without becoming unmanageably complex.
Solution Approach 2:
The data collection system is designed with universal data collecting strategies that can handle multiple fault types and diverse user environments through a unified framework. The pre-configured fault codes and strategies provide a multi-functional solution that works across different scenarios without requiring separate complex systems for each case.
3Loss of time
If real-time data collection is performed during automatic parking, then fault detection timeliness improves, but the risk of user interference and data quality degradation increases
Solution Approach 1:
The system performs automatic self-monitoring and self-data-collection during automatic parking operations. The system independently detects fault codes and executes data collection without user involvement, eliminating user interference while maintaining real-time detection capability and data quality.
Solution Approach 2:
The system implements automatic feedback loops where fault codes are continuously monitored and trigger corresponding data collection strategies in real-time. This closed-loop feedback mechanism ensures timely fault detection and automatic data capture without requiring user intervention, maintaining both speed and reliability.
Data Source
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AI summary
The present application discloses an abnormal data collecting method for automatic parking, an apparatus, a storage medium and a product, and relates to automatic driving technology and automatic parking technology in computer technology. A specific implementation is: in response to monitoring that a target vehicle generates a fault code during an automatic parking process, matching (S201) the fault code with at least one pre-configured fault code to be collected; in response to determining that the fault code matches the fault code to be collected, determining (S202) a data collecting strategy corresponding to the fault code to be collected; and performing (S203) a data collecting operation on abnormal data corresponding to the fault code according to the data collecting strategy. Therefore, the effect of automatically triggering the collection of various abnormal data under the automatic parking function can be realized without interference and burden on the user, which greatly improves the efficiency of data collection.