| Texto completo | |
| Autor(es): |
Domingues, Augusto C. S. A.
;
Silva, Fabricio A.
;
Loureiro, Antonio A. F.
;
IEEE
Número total de Autores: 4
|
| Tipo de documento: | Artigo Científico |
| Fonte: | 2018 IEEE SYMPOSIUM ON COMPUTERS AND COMMUNICATIONS (ISCC); v. N/A, p. 6-pg., 2018-01-01. |
| Resumo | |
The feasibility of vehicular networks is directly related to the understanding of mobility patterns, which is a necessary knowledge for the elaboration and application of novel algorithms and technologies for such networks. Thereupon, mobility traces have an important role in the exploration of mobility patterns. Since mobility traces represent the movement of entities in real-life situations, their comprehensive study is a great opportunity to characterize mobility behaviors, which can then be applied to improve the design of mobile networks. In this work, we perform a thorough characterization of a taxi dataset regarding spatial and temporal characteristics, to better understand how these factors affect traffic conditions. To this end, we define a new metric, called path optimality, that represents the rate of trips that follow the shortest path between two points. We use this metric to understand what are the conditions that affect the mobility pattern of drivers on a large city. (AU) | |
| Processo FAPESP: | 15/24494-8 - Comunicação e processamento de big data em nuvens e névoas computacionais |
| Beneficiário: | Nelson Luis Saldanha da Fonseca |
| Modalidade de apoio: | Auxílio à Pesquisa - Temático |