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GIS Mapping of Driving Behavior Based on Naturalistic Driving Data

1
Institute for Transport Planning and Systems (IVT), Swiss Federal Institute of Technology, Stefano-Franscini-Platz 5, 8093 Zürich, Switzerland
2
University Research Institute on Traffic and Road Safety (INTRAS), University of Valencia, Calle Serpis, 29, 46022 Valencia, Spain
3
Department of Cartographic Engineering, Geodesy and Photogrammetry (DICGF), Polythecnic University of Valencia, Camino de Vera, s/n., 46022 Valencia, Spain
4
CartoLAB, Departament of Civil Engineering, University of A Coruña, Campus de Elviña, 15071 A Coruña, Spain
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2019, 8(5), 226; https://doi.org/10.3390/ijgi8050226
Received: 14 March 2019 / Revised: 25 April 2019 / Accepted: 4 May 2019 / Published: 9 May 2019
(This article belongs to the Special Issue Smart Cartography for Big Data Solutions)
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Abstract

Naturalistic driving can generate huge datasets with great potential for research. However, to analyze the collected data in naturalistic driving trials is quite complex and difficult, especially if we consider that these studies are commonly conducted by research groups with somewhat limited resources. It is quite common that these studies implement strategies for thinning and/or reducing the data volumes that have been initially collected. Thus, and unfortunately, the great potential of these datasets is significantly constrained to specific situations, events, and contexts. For this, to implement appropriate strategies for the visualization of these data is becoming increasingly necessary, at any scale. Mapping naturalistic driving data with Geographic Information Systems (GIS) allows for a deeper understanding of our driving behavior, achieving a smarter and broader perspective of the whole datasets. GIS mapping allows for many of the existing drawbacks of the traditional methodologies for the analysis of naturalistic driving data to be overcome. In this article, we analyze which are the main assets related to GIS mapping of such data. These assets are dominated by the powerful interface graphics and the great operational capacity of GIS software. View Full-Text
Keywords: Big data; data visualization; driving behavior; Geographic Information Systems; kinematic (driving) data; mapping; microscopic traffic model; naturalistic driving Big data; data visualization; driving behavior; Geographic Information Systems; kinematic (driving) data; mapping; microscopic traffic model; naturalistic driving
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Balsa-Barreiro, J.; Valero-Mora, P.M.; Berné-Valero, J.L.; Varela-García, F.-A. GIS Mapping of Driving Behavior Based on Naturalistic Driving Data. ISPRS Int. J. Geo-Inf. 2019, 8, 226.

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