Mainly based on Li Li's Ph. D. dissertation: University of Arizona, Tucson, 2005. / Includes bibliographical references and index.

Thesis (M. S. in Computer Science)--Vanderbilt University, May 2009. / Title from title screen. Includes bibliographical references.

Mainly based on Li Li's Ph. D. dissertation: University of Arizona, Tucson, 2005. / Includes bibliographical references and index. Also available in print.

Mainly based on Li Li's Ph. D. dissertation: University of Arizona, Tucson, 2005. / Includes bibliographical references and index.

Thesis (Ph.D.)--University of Melbourne, Dept. of Computer Science and Software Engineering, 2010. / Typescript. Includes bibliographical references (p. 153-167)

Mainly based on Li Li's Ph. D. dissertation: University of Arizona, Tucson, 2005. / Includes bibliographical references and index. Also available in print.

Mainly based on Li Li's Ph. D. dissertation: University of Arizona, Tucson, 2005. / Includes bibliographical references and index.

Thesis (Master of Engineering in Electrical Engineering and Computer Science)--Massachusetts Institute of Technology, 2000. / Cover title. Also available online via the MIT website (www.media.mit.edu). Includes bibliographical references (leaves 36-38).

Thesis (Ph. D.)--Ohio State University, 2007. / Title from first page of PDF file. Includes bibliographical references (p. 171-182).

Esse trabalho consiste em um estudo sobre a aplicabilidade da medida de centralidade de intermediação (betweenness centrality) combinada com demandas de tráfego em redes viárias com o objetivo de identificar os principais pontos dessas redes. Como principais pontos refere-se aqui aos que aparecem com maior frequência entre os caminhos utilizados pelos motoristas que se deslocam pela rede viária. Trata-se de um estudo exploratório, que se inicia com a aplicação da centralidade de intermediação sobre redes simples, estendendo-se até simulações sobre redes baseadas em mapas reais. Nesse trabalho é analisado o comportamento da medida de centralidade sobre a topologia da rede - i.e. tanto sem considerar uma demanda, como considerando demandas de diversas magnitudes. Para ilustrar a proposta, os resultados são confrontados com valores de centralidade de intermediação calculados sobre as taxas de ocupação das vias extraídas de simulação microscópica. Ao final, foram apresentadas evidências de que o método proposto consegue explicar os fluxos de tráfego com melhor desempenho do que a centralidade de intermediação original. No entanto, o método mostrou-se muito sensível à função de custo utilizada na atribuição da demanda de tráfego ao grafo da rede. Os melhores resultados demonstrados pela abordagem proposta foram obtidos em experimentos sobre redes não regulares e com demandas de tráfego não uniformes. No caso de redes regulares com demanda uniforme, o melhor desempenho foi obtido pelo cálculo da centralidade sem considerar a demanda, mas atribuindo-se o custo unitário às arestas do grafo representativo da rede. / This work consists of a study of applicability of betweenness centrality combined with traffic demands in road networks with the objective of identifying their central points. By central points we refer to those which appear with high frequency among the paths used by drivers that move along the road network. It is an exploratory study, which begins with the application of the betweenness centrality on simple networks, extending to simulations on networks based on real maps. In this study we have analyzed the behavior of the metric over the network topology - i.e. without considering demand, as well as experiments considering demands with several magnitudes. To illustrate the proposed method, the results are compared with betweenness centrality values calculated over roadways occupation rates extracted from microscopic simulation. At the end, evidence that the proposed method can explain traffic flows with better performance than the original betweenness centrality were presented. However, the proposed method was shown to be very sensitive to the cost function used in the allocation of the graph network traffic demand. The best results demonstrated by the proposed approach were obtained in experiments on nonregular networks and non-uniform traffic demands. In the case of regular networks with uniform demand, the best performance was obtained by calculating the betweenness centrality without considering the demand, but assigning the unitary cost to the edges of the network graph.