Smartphone Placement Within Vehicles
ORE Open Research Exeter TITLE Smartphone placement within vehicles AUTHORS Wahlstrom, J; Skog, I; Handel, P; et al. JOURNAL IEEE Transactions on Intelligent Transportation Systems DEPOSITED IN ORE 22 July 2020 This version available at http://hdl.handle.net/10871/122083 COPYRIGHT AND REUSE Open Research Exeter makes this work available in accordance with publisher policies. A NOTE ON VERSIONS The version presented here may differ from the published version. If citing, you are advised to consult the published version for pagination, volume/issue and date of publication 1 Smartphone Placement within Vehicles Johan Wahlstrom,¨ Isaac Skog, Peter Handel,¨ Bill Bradley, Samuel Madden, and Hari Balakrishnan Abstract—Smartphone-based driver monitoring is quickly a) gaining ground as a feasible alternative to competing in-vehicle and aftermarket solutions. Today, the main challenges for data analysts studying smartphone-based driving data stem from the mobility of the smartphone. In this study, we use kernel-based k-means clustering to infer the placement of smartphones within vehicles. All in all, trip segments are mapped into fifteen different placement clusters. As part of the presented framework, we b) discuss practical considerations concerning e.g., trip segmenta- tion, cluster initialization, and parameter selection. The proposed method is evaluated on more than 10 000 kilometers of driving data collected from approximately 200 drivers. To validate the in- c) terpretation of the clusters, we compare the data associated with different clusters and relate the results to real world knowledge of driving behavior. The clusters associated with the label “Held by hand” are shown to display high gyroscope variances, low Fig.
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