Spatio-temporal Correlations of Betweenness Centrality and Traffic Metrics
| Autor: | Nour-Eddin El Faouzi, Eugenio Zimeo, Elise Henry, Loïc Bonnetain, Angelo Furno |
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| Přispěvatelé: | Laboratoire d'Ingénierie Circulation Transport (LICIT UMR TE), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-École Nationale des Travaux Publics de l'État (ENTPE)-Université de Lyon, University of Sannio [Benevento], PROMENADE ANR-18-CE22-0008 |
| Rok vydání: | 2019 |
| Předmět: |
Computer science
DUREE DU TRAJET 0211 other engineering and technologies Vulnerability RESEAU DE TRANSPORT 02 engineering and technology CIRCULATION ROUTIERE VULNERABILITE computer.software_genre Vehicle dynamics CORRELATION ANALYSIS Betweenness centrality TRANSPORTATION NETWORKS SURVEILLANCE 0502 economics and business 11. Sustainability TRAFIC ROUTIER DYNAMIC GRAPHS TRAFFIC MONITORING Undirected graph 050210 logistics & transportation 05 social sciences 021107 urban & regional planning CALCUL D&apos RESEAU ROUTIER MODELISATION [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation CONGESTION DU TRAFIC GESTION DU TRAFIC REPRESENTATION GRAPHIQUE Travel time Sustainable city Traffic congestion 13. Climate action BETWEENNESS CENTRALITY Data mining ERREURS Centrality computer |
| Zdroj: | MT-ITS MT-ITS 2019, 6th International Conference on Models and Technologies for Intelligent Transportation Systems MT-ITS 2019, 6th International Conference on Models and Technologies for Intelligent Transportation Systems, Jun 2019, Cracovie, Poland. 10p, ⟨10.1109/MTITS.2019.8883379⟩ |
| Popis: | MT-ITS 2019, 6th International Conference on Models and Technologies for Intelligent Transportation Systems, Cracovie, POLOGNE, 05-/06/2019 - 07/06/2019; Graph-based analysis has proven to be a good approach to study topological vulnerabilities of road networks through specific metrics, such as betweenness centrality (BC). Even though BC of unweighted, undirected graphs has been widely adopted to identify critical road segments and intersections, given the very high number of potentially highly-traversed paths flowing through them, congestion and vulnerability are strongly influenced also by static and dynamic context factors, such as road capacity, speed limits, travellers' behaviors, accidents, social gatherings and maintenance operations. In this paper, we focus on the analysis of BC on dynamically weighted graphs, used as a model of a road network and associated dynamic information (e.g. travel time). The aim is to discover correlations between the centrality metric and vehicle flows, both in space and in time. The analysis proves the existence of relevant spatio-temporal correlations that provide useful information about the characteristics of road networks and the behavior of drivers. In particular, we identify the existence of anti-correlations that point out forecasting properties of BC when computed on dynamic graphs.These properties justify the usage of the metric for the implementation of next-generation proactive, data-driven urban monitoring systems. These systems are expected to empower urban planners and traffic operators with novel intelligent solutions to reduce traffic congestion and vulnerability risks, therefore contributing to implement the vision of a more resilient and sustainable city. |
| Databáze: | OpenAIRE |
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