Mostrar o rexistro simple do ítem
GIS mapping of driving behavior based on naturalistic driving data
dc.contributor.author | Balsa-Barreiro, José | |
dc.contributor.author | Valero-Mora, Pedro | |
dc.contributor.author | Berné Valero, José Luis | |
dc.contributor.author | Varela-García, Francisco-Alberto | |
dc.date.accessioned | 2019-07-01T16:43:31Z | |
dc.date.available | 2019-07-01T16:43:31Z | |
dc.date.issued | 2019 | |
dc.identifier.citation | 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. | es_ES |
dc.identifier.uri | http://hdl.handle.net/2183/23331 | |
dc.description | Este artigo pertence ao número especial Smart Cartography for Big Data Solutions. | es_ES |
dc.description.abstract | [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. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | MDPI | es_ES |
dc.relation.uri | https://doi.org/10.3390/ijgi8050226 | es_ES |
dc.rights | Atribución 3.0 España | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ | * |
dc.subject | Big Data | es_ES |
dc.subject | Data visualization | es_ES |
dc.subject | Driving behavior | es_ES |
dc.subject | Geographic information systems | es_ES |
dc.subject | Kinematic (driving) data | es_ES |
dc.subject | Mapping | es_ES |
dc.subject | Microscopic traffic model | es_ES |
dc.subject | Naturalistic driving | es_ES |
dc.title | GIS mapping of driving behavior based on naturalistic driving data | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
UDC.journalTitle | ISPRS International Journal of Geo-Information | es_ES |
UDC.volume | 8 | es_ES |
UDC.issue | 5 | es_ES |
UDC.startPage | 1 | es_ES |
UDC.endPage | 12 | es_ES |
dc.identifier.doi | 10.3390/ijgi8050226 |