Paper Info
Title
Visual Analysis of Car Fleet Trajectories to Find Representative Routes for Automotive Research
Abstract
Testing is an important and wide spread practice in the development of automotive components. For the design of test methods two types of input data are often considered: (1) load data gathered from real life vehicle fleets, and (2) information of the driving routes based on road features. The development of new technologies is though complicated not only by the need to join those two data sources, but also by the too limited knowledge of the parameters and their useful combinations. As a result, information about representative driving profiles is needed. To address these problems we present a visual analytics approach for analyzing multivariate trajectories as a combination of vehicle's location and road elevation data. Our system combines trajectory clustering, interval-based user-driven trip segmentation, and frequent sequences analysis, supported by contingency table and interval-based Parallel Coordinates visualization and enables the expert user to find representative driving profiles for the definition of very compact test courses.
Year
DOI
Venue
2015
10.1109/iV.2015.63
International Conference on Information Visualisation
Keywords
Field
DocType
Visual Analytics, Automotive Research, Trajectory Analysis and Visualization
Computer vision,Data mining,Visualization,Segmentation,Visual analytics,Emerging technologies,Parallel coordinates,Contingency table,Artificial intelligence,Elevation,Engineering,Automotive industry
Conference
ISSN
Citations 
PageRank 
1550-6037
0
0.34
References 
Authors
16
7
Name
Order
Citations
PageRank
David Spretke100.34
Manuel Stein244.49
lyubka sharalieva351.09
Alexander Warta400.34
Valentin Licht500.34
Tobias Schreck61854123.28
Daniel A. Keim777041141.60