In the traffic network, the betweenness centrality helps in identification of the most occupied roads and crossroads. Usually, the main roads have the highest betweenness centrality score, given their importance in the traffic flow. The side roads’ score is generally lower and it never takes into account what is happening on the main road. In a case of unusual event happening in the city, the betweenness score of the main road can increase multiplicatively, while the score of the side road is increased only slightly. Thus, we propose an extension to the original betweenness centrality score algorithm that enables the propagation of the betweenness centrality score from the main road to the side roads, allowing us better description of the current traffic situation. This is the continuation of our work on better refinement of the BC score for the purpose of the traffic modelling and the traffic flow control.
CITATION STYLE
Hanzelka, J., Běloch, M., Křenek, J., Martinovič, J., & Slaninová, K. (2018). Betweenness propagation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11127 LNCS, pp. 279–287). Springer Verlag. https://doi.org/10.1007/978-3-319-99954-8_24
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