Time Series Categorization of Driving Maneuvers Using Acceleration Signals
Abstract
Two methods of time series analysis were applied to naturalistic driving data. The SAX method reduces the dimensionality of the data by discretizing and quantizing it into distinct symbols. The matrix profile method works on raw data and computes a Euclidian distance measure between subsequences of the time series. Both methods can be used to search for motifs and discords (anomalies) in the data. We discuss the applications of these methods to look for driving patterns and show an example of a left turn that was identified using both methods. After comparing the methods, the matrix profile was the preferred method.
How to Cite:
Schwarz, C., (2017) “Time Series Categorization of Driving Maneuvers Using Acceleration Signals”, Driving Assessment Conference 9(2017), 270-276. doi: https://doi.org/10.17077/drivingassessment.1646
Rights: Copyright © 2017 the author(s)
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