Spanish Road Fork Traffic Analysis and Modelling View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2017

AUTHORS

Irene Díaz , José Ramón Villar , Enrique de la Cal

ABSTRACT

This study focuses on the analysis of traffic data concerning road crashes, with the aim of extracting relevant knowledge in order to choose the location of intelligent road guardrails. To do so, historical data of the accidents in Spanish roads since 2011 have been gathered from the Dirección General de Tráfico and analyzed afterwards. After a preliminary stage, where association rule mining algorithms were performed, this study focuses on Decision Tree classifiers to determine the relationships among the features in the accidents yearly dataset. These relationships are related to the intrinsic connections between features. Some interesting relationships have been found, specially for the T or Y shape road fork type. Future work will deploy a severity index using both the victims and vehicles, so relationships due to conditions and severity can be extracted. As long as the extracted rule set varies for each year, it might be useful as well to determine invariants in the trees, which is led as future work. More... »

PAGES

483-493

References to SciGraph publications

Book

TITLE

Hybrid Artificial Intelligent Systems

ISBN

978-3-319-59649-5
978-3-319-59650-1

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-59650-1_41

DOI

http://dx.doi.org/10.1007/978-3-319-59650-1_41

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1086387405


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