Context-aware Vehicle Route Recommendation Platform: Exploring Open and Crowdsourced Data

Autor(es)

Santos, Frances A. ; Rodrigues, Diego O. ; Silva, Thiago H. ; Loureiro, Antonio A. F. ; Pazzi, Richard W. ; Villas, Leandro A. ; IEEE

• Tipo de documento: Artigo Científico
• Fonte: 2018 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC); v. N/A, p. 7-pg., 2018-01-01.

Resumo

An increasing number of users have been adopting route recommendation systems, mostly motivated by the convenience that those systems bring to their traffic experiences. Usually, those systems observe the historical and current traffic conditions in order to evaluate and recommend the fastest routes. However, besides mobility aspects, more contextual information such as unplanned street events and neighborhood safety, are not taken into account in the recommendation process. With this in mind, we propose a platform to support context-aware route recommendation systems. The proposed platform aims to improve existing recommendation algorithms or enable the proposal of new ones. To assess it, we use datasets of routes suggested by Google Maps in the city of Curitiba, Brazil, official open data provided by the city and also data generated voluntarily by citizens in a participatory sensing fashion. Our results show the existence of an opportunity for route planners to provide personalized services to users, which is an important step towards the development of context-aware vehicular networks. Besides, these results illustrate how publicly available big data can be explored to improve context-aware route recommendations. (AU)

• Processo FAPESP: 15/07538-1 - Desenvolvimento de Serviços Inteligentes de nova Geração e Aplicações para Cidades Inteligentes
• Beneficiário: Leandro Aparecido Villas
• Modalidade de apoio: Auxílio à Pesquisa - Regular