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Detection of Road Accident Accumulation Zones with a Visual Analytics Approach.
- Source :
- Procedia Computer Science; 2015, Vol. 64, p969-976, 8p
- Publication Year :
- 2015
-
Abstract
- Nowadays, road accidents are a major public health problem, which increase is forecasted if road safety is not treated properly, dying about 1.2 million people every year around the globe. In 2012, Portugal recorded 573 fatalities in road accidents, on site, revealing the largest decreasing of the European Union for 2011, along with Denmark. Beyond the impact caused by fatalities, it was calculated that the economic and social costs of road accidents weighted about 1.17% of the Portuguese gross domestic product in 2010.Visual Analytics allows the combination of data analysis techniques with interactive visualizations, which facilitates the process of knowledge discovery in sets of large and complex data, while the Geovisual Analytics facilitates the exploration of space-time data through maps with different variables and parameters that are under analysis. In Portugal, the identification of road accident accumulation zones, in this work named black spots, has been restricted to annual fixed windows. In this work, it is presented a dynamic approach based on Visual Analytics techniques that is able to identify the displacement of black spots on sliding windows of 12 months. Moreover, with the use of different parameterizations in the formula usually used to detect black spots, it is possible to identify zones that are almost becoming black spots. Through the proposed visualizations, the study and identification of countermeasures to this social and economic problem can gain new grounds and thus the decision-making process is supported and improved. [ABSTRACT FROM AUTHOR]
- Subjects :
- TRAFFIC accidents
VISUAL analytics
PUBLIC health
ROAD safety measures
Subjects
Details
- Language :
- English
- ISSN :
- 18770509
- Volume :
- 64
- Database :
- Supplemental Index
- Journal :
- Procedia Computer Science
- Publication Type :
- Academic Journal
- Accession number :
- 109493989
- Full Text :
- https://doi.org/10.1016/j.procs.2015.08.615