UAV Aerial Survey Data Processing for Autonomous Vehicle Safety Testing
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Solution Overview
Problem
Current methods for surveying traffic scenarios, such as using test vehicles or infrastructure-mounted sensors, suffer from limitations in accuracy and comprehensiveness, which hampers the safety testing and verification of autonomous vehicles.
Innovation Solution
A data processing method employing an unmanned aerial vehicle (UAV) to collect aerial survey data over target road segments, using sensors to monitor traffic flows and environmental changes, and marking relevant data fragments based on movement information to improve the accuracy of safety testing for autonomous vehicles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If test vehicles or infrastructure-mounted sensors are used for surveying traffic scenarios, then the surveying system can be implemented, but the accuracy and comprehensiveness of the survey data are limited
Solution Approach 1:
The patent transitions from ground-based surveying (2D plane) to aerial surveying using UAVs (3D space), enabling comprehensive coverage of traffic scenarios from multiple angles and heights. This dimensional change allows the system to capture complete vehicle trajectories, environmental contexts, and traffic participant behaviors that ground-based sensors cannot observe, thereby simultaneously improving both measurement precision and survey comprehensiveness.
2Measurement precision
If aerial survey data is collected to improve survey accuracy and comprehensiveness, then safety testing data quality improves, but data processing complexity increases
Solution Approach 1:
The patent segments the aerial survey data processing into distinct components: trajectory extraction modules that separate vehicle paths from background, behavior recognition modules that identify specific traffic actions, and annotation modules that categorize data fragments. This segmentation reduces processing complexity by handling different aspects of data independently while maintaining high accuracy in safety testing verification.
3Reliability
If detailed marking of target data fragments is performed to enhance safety testing verification, then testing accuracy improves, but processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary actions by pre-extracting vehicle trajectories and pre-recognizing traffic participant behaviors during data collection, before the actual safety testing verification begins. This preliminary processing organizes raw aerial survey data into structured formats with pre-identified key elements, reducing the computational burden and processing time required during the verification stage while maintaining high reliability in testing results.
Data Source
AI summary
A data processing method includes obtaining location information of a target path, generating a control instruction according to the location information to instruct a mobile platform to move to above the target path, obtaining survey data of the target path collected by a sensor of the mobile platform and determining status information of one or more traffic participants on the target path based on the survey data, and marking a target data fragment in the survey data according to the status information of the one or more traffic participants. Status information of the one or more traffic participants in the target data fragment satisfies a preset status information condition.