A Visual Decision-Support System using Fingerprint Matrices applied to Cyclical Spatio-Temporal Data from Motorsports

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dc.contributor.authorStreet, Chris
dc.contributor.authorHoeber, Orland
dc.date.accessioned2021-12-24T17:32:17Z
dc.date.available2021-12-24T17:32:17Z
dc.date.issued2022-01-04
dc.description.abstractVisualizing cyclical spatio-temporal data is an important part of understanding how and why objects move in the context of motorsports, which is critical feedback for drivers to improve their performance. Current methods have problems such as occlusion and loss of context which significantly limit our ability to see and understand vehicle data. Here we demonstrate how the fingerprint matrix method (which is normally used in lexical analysis) can be applied in vehicle motion analysis to overcome these two problems. Compared to traditional methods using traction circle scatterplot displays of acceleration force data from a race car, our prototype design allows decision makers to see individual datapoints in a more concise display. We show that informative but previously-hidden anomalies and patterns become more easily recognized in the data. Our design generalizes to other cyclical spatio-temporal visualization problems involving transportation, medicine, and the natural world.
dc.format.extent9 pages
dc.identifier.doi10.24251/HICSS.2022.210
dc.identifier.isbn978-0-9981331-5-7
dc.identifier.urihttp://hdl.handle.net/10125/79542
dc.language.isoeng
dc.relation.ispartofProceedings of the 55th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectInteractive Visual Analytics and Visualization for Decision Making
dc.subjectdecision support
dc.subjectinformation visualization
dc.subjectmotorsports
dc.subjectvehicle telemetry
dc.titleA Visual Decision-Support System using Fingerprint Matrices applied to Cyclical Spatio-Temporal Data from Motorsports
dc.type.dcmitext

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