An Interactive Visual Analytics Platform for Smart Intelligent Transportation Systems Management
| Autor: | Ilias Kalamaras, Dionysios D. Kehagias, Stavros Papadopoulos, Georgios Margaritis, Anastasios Drosou, Athanasios Salamanis, Alexandros Zamichos, Dimitrios Tzovaras |
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| Rok vydání: | 2018 |
| Předmět: |
Visual analytics
Computer science business.industry Mechanical Engineering 020207 software engineering 02 engineering and technology Traffic flow Computer Science Applications Visualization Data visualization Traffic congestion Analytics Human–computer interaction 11. Sustainability Automotive Engineering 0202 electrical engineering electronic engineering information engineering Data analysis 020201 artificial intelligence & image processing business Intelligent transportation system |
| Zdroj: | IEEE Transactions on Intelligent Transportation Systems. 19:487-496 |
| ISSN: | 1558-0016 1524-9050 |
| DOI: | 10.1109/tits.2017.2727143 |
| Popis: | The reduction of road congestion requires intuitive urban congestion-control platforms that can facilitate transport stakeholders in decision making. Interactive ITS visual analytics tools can be of significant assistance, through their real-time interactive visualizations, supported by advanced data analysis algorithms. In this paper, an interactive visual analytics platform is introduced that allows the exploration of historical data and the prediction of future traffic through a unified interactive interface. The platform is backed by several data analysis techniques, such as road behavioral visualization and clustering, anomaly detection, and traffic prediction, allowing the exploration of behavioral similarities between roads, the visual detection of unusual events, the testing of hypotheses, and the prediction of traffic flow after hypothetical incidents imposed by the human operator. The accuracy of the prediction algorithms is verified through benchmark comparisons, while the applicability of the proposed toolkit in facilitating decision making is demonstrated in a variety of use case scenarios, using real traffic and incident data sets. |
| Databáze: | OpenAIRE |
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