Asynchronous Driving Data Synchronization Using Time Interpolation
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Solution Overview
Problem
The integration of disparate data sets from driving simulators and eye tracking systems with different time resolutions is challenging, limiting the understanding of driver reactions to in-vehicle applications, as existing synchronization methods are complex and costly, hindering widespread adoption.
Innovation Solution
A system and method for synchronizing asynchronous data from driving simulators and eye tracking systems by merging data files using interpolation based on a driving behavior analysis computer, aligning data snapshots to create a unified, synchronized dataset for analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex software-implemented solutions are used to synchronize disparate data sets, then data synchronization precision is improved, but system complexity and development cost increase
Solution Approach 1:
The patent segments the synchronization process into discrete, manageable components: (1) identifying common time references between data streams, (2) interpolating data points to align timestamps, (3) merging synchronized data into a unified data structure. This segmentation allows complex synchronization to be achieved through simpler, modular operations rather than monolithic complex software.
Solution Approach 2:
The patent introduces a time reference intermediary mechanism that acts as a mediator between disparate data streams with different timestamps. By establishing a common time reference framework and using interpolation as an intermediary transformation, the system reconciles asynchronous data without requiring complex real-time synchronization software.
2Loss of information
If real-time integration of data from multiple systems is implemented, then data availability is improved, but computational resource consumption increases
Solution Approach 1:
The patent performs data synchronization and interpolation as preliminary actions before final data analysis. By pre-processing and aligning data from multiple systems in advance, the system ensures data availability for subsequent analysis without requiring continuous real-time computational resources. The heavy lifting is done beforehand when data is collected, not during analysis.
3Adaptability or versatility
If data from systems with different time resolutions are merged, then comprehensive data coverage is improved, but data processing complexity increases
Solution Approach 1:
The patent applies parameter changes through interpolation, transforming data from one time resolution to another. By adjusting the time parameter and interpolating intermediate values, the system can merge data streams with different sampling rates (e.g., 100ms and 30ms) into a unified timeline. This parameter transformation approach handles variable time resolutions systematically rather than requiring complex adaptive processing.
Data Source
AI summary
Computer-implemented systems and methods are provided for the synchronization of data from asynchronous datasets to form a merged, synchronized data set, and more particularly to systems and methods for merging disparate and asynchronous data sets that include common dimensions, such as space and time dimensions, and more particularly space and time data relating to a driving simulation environment (such as driving simulator data and eye tracking data having disparate time data resolutions), to enable data extraction from and analysis of the merged, synchronized data set. A driving simulator system includes a driver interface having driving controls and a display and creates driving simulator data files for each driver of the driving simulator system having data entries that are captured at a first timing frequency. Likewise, an eye tracking system includes eye tracking cameras for tracking a driver's eye movements when using the driving simulator system and creates eye tracking data files for each driver of the driving simulator system having data entries that are captured at a second timing frequency that is different from the first timing frequency at which driving simulator data is captured. A driving behavior analysis computer is also provided that merges the asynchronous data embodied in each of the driving simulator data files and the eye tracking data files to form a single merged data file based upon an interpolation of data entries in those data files. The merged data files may then be further processed to enable extraction and analysis of the merged data in order to identify various driver behaviors.