Autonomous Driving Sensor Data Fusion and Synchronization
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Solution Overview
Problem
Existing vehicle sensor data systems struggle to effectively integrate and utilize data from various sensors in different formats to support autonomous driving operations, limiting their ability to make informed decisions about routing, speed, and control actions.
Innovation Solution
An autonomous vehicle system that includes a computing device with an autonomous driving module capable of integrating data from multiple sensors, such as GPS, RADAR, lidar, and cameras, to perform strategic, tactical, and operational tasks, using data fusion and synchronization techniques to support decision-making and control actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If multiple sensors in different formats are used to collect data, then the quantity and diversity of information is improved, but the complexity of data integration and processing increases
Solution Approach 1:
The patent combines multiple sensors (cameras, LIDAR, RADAR, GPS) into a unified sensing system that collects data simultaneously. The computing device integrates data from all these different sensor types through data fusion techniques, merging previously separate data streams into a cohesive representation of the environment for autonomous driving decisions.
Solution Approach 2:
The computing device acts as an intermediary that receives raw data from multiple sensors in different formats, processes and synchronizes this data, and produces integrated sensor data that can be used for autonomous driving. This intermediary layer handles the complexity of data integration, allowing the autonomous driving module to work with unified, processed information rather than raw heterogeneous data streams.
2Reliability
If data from various sensors in different formats is integrated, then the ability to make informed decisions is improved, but the processing time and computational requirements increase
Solution Approach 1:
The system performs preliminary synchronization and validation of sensor data before the autonomous driving module needs to make decisions. By pre-processing the data, organizing it into a consistent format, and validating its quality in advance, the system reduces the computational burden during critical decision-making moments, thereby reducing processing time while maintaining decision accuracy.
Solution Approach 2:
The sensing system operates continuously, collecting and pre-processing sensor data in real-time rather than batch-processing. This continuous operation ensures that data is always ready for immediate use by the autonomous driving module, eliminating delays associated with periodic processing and ensuring timely decision-making while maintaining high reliability through constant data availability.
3Adaptability or versatility
If sensor data is collected in various formats, then the versatility of information gathering is improved, but the difficulty of data synchronization and validation increases
Solution Approach 1:
The computing device transforms sensor data from various formats into a unified parameter set suitable for autonomous driving. It changes the parameters of raw sensor data (different coordinate systems, time formats, data structures) into a standardized form with consistent parameters, enabling easy synchronization and validation while preserving the versatility of the original multi-format data collection.
4Device complexity
If existing sensor data systems are used without integration, then the simplicity of the system is maintained, but the ability to support autonomous operations is limited
Solution Approach 1:
The integrated sensing system is designed with multi-functionality to support various autonomous driving operations. The same sensor array and processing pipeline can handle strategic routing decisions, tactical speed and lane changes, and operational control tasks. This universal system replaces multiple separate simple systems, increasing autonomous operation capability while maintaining reasonable complexity through shared infrastructure.
Data Source
AI summary
First and second sets of data are collected in a vehicle from respective data sources. Each of the first and second sets of data are provided for determinations respectively selected from first and second categories of autonomous vehicle operations. A determination is made to take an autonomous action selected from the first category of autonomous vehicle operations. Data is used from each of the first and second data sets relating respectively to the first and second categories of autonomous vehicle operations to determine the autonomous action.