Dynamic Vehicle Data Acquisition Frequency Control
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Solution Overview
Problem
Acquiring and analyzing real driving scene data and driver behavior data in various driving scenes is challenging due to the complexity of scenes, high redundancy, and resource-intensive storage and transmission requirements.
Innovation Solution
A method and apparatus that determine a stable driving condition based on acquired data, adjusting the sampling frequency of driving scene and behavior data acquisition accordingly, reducing redundancy and optimizing resource usage by acquiring data at lower frequencies during stable conditions and higher frequencies during unstable conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is acquired continuously at high sampling frequency to capture all driving scenes, then data completeness is improved, but data redundancy increases and storage resources are consumed
Solution Approach 1:
The patent applies dynamic sampling frequency adjustment by changing the data acquisition frequency from a fixed high value to a variable value that adapts to driving conditions. The system switches between first sampling frequency (stable conditions) and second sampling frequency (unstable conditions), making the acquisition process dynamic rather than static, thus reducing redundancy while maintaining completeness
Solution Approach 2:
The patent changes the parameter of sampling frequency based on driving condition stability. By monitoring driving parameters (speed, acceleration, steering angle) and determining stability, the system adjusts the sampling frequency parameter dynamically - using lower frequency for stable conditions and higher frequency for unstable conditions, thereby resolving the contradiction between completeness and redundancy
2Measurement precision
If data is acquired at high sampling frequency to ensure data quality, then analysis precision is improved, but storage resources and transmission resources are consumed
Solution Approach 1:
The system dynamically adjusts sampling frequency based on driving condition stability determination. During stable driving conditions, it uses a lower first sampling frequency to conserve storage and transmission resources. During unstable conditions requiring higher analysis precision, it switches to a higher second sampling frequency, thus dynamically optimizing the balance between precision and resource consumption
Solution Approach 2:
The patent implements periodic evaluation of driving condition stability and adjusts sampling frequency accordingly. The system periodically monitors driving parameters, determines stability, and switches between sampling frequencies in periodic cycles, ensuring high precision is maintained only when necessary while conserving resources during stable periods
3Reliability
If multiple sensors and devices are deployed to capture comprehensive driving data, then data coverage is improved, but device complexity increases
Solution Approach 1:
The patent applies dynamic activation of data acquisition based on driving condition stability. Instead of continuously activating all sensors at full capacity, the system dynamically adjusts which sensors are active and at what sampling rates based on whether driving conditions are stable or unstable, thereby maintaining comprehensive coverage while reducing overall system complexity
Solution Approach 2:
The patent segments the data acquisition process into different modes (stable condition mode and unstable condition mode) with different sampling frequencies. By dividing the acquisition process into distinct operational segments, the system manages complexity through structured organization of sensor activation and data collection strategies
Data Source
AI summary
The present disclosure provides a data acquisition method, apparatus, device and computer readable storage medium. According to the embodiments of the present disclosure, determination is made as to whether a preset stable driving condition is met based on acquired driving scene data of the driving scene where the vehicle is currently located, and acquired driving behavior data; if the preset stable driving condition is met, the driving scene data and the driving behavior data are acquired at a frequency lower than a preset sampling frequency. As a result, it is possible to reduce data redundancy in similar scenes and similar diving modes, reduce the amount of data, reduce occupation of the storage resources and transmission resources and facilitate subsequent analysis, and it is possible to implement the dynamic acquisition of driving scene data and driving behavior data by scenes and modes.