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Solutions for intelligent and cooperative transportation systems based on urban computing


An intelligent transportation system integrates information, communication, and computing to solve common problems in the traditional transportation system, such as traffic jams, accidents, and road capacity. Thus, an efficient solution for this system should be able to consider data from sensors, information about traffic as well as information from the internet and social networks. Urban Computing is a computer science area that provides solutions to the problems faced by cities using information and communication technologies. Urban computing studies the processes of collecting, analyzing and managing data from different sources of urban spaces, including data generated by humans through the participatory sensing networks. This project aims to advance the state of the art by providing solutions for intelligent transportation systems integrating urban data from the web and vehicular networks. Based on these considerations, the project will investigate mechanisms for collecting and analyzing large volumes of data from different sources and to propose mechanisms for information dissemination and control considering applications in intelligent transportation systems. (AU)

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Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
RODRIGUES, DIEGO O.; MAIA, GUILHERME; BRAUN, TORSTEN; LOUREIRO, ANTONIO A. F.; PEIXOTO, MAYCON L. M.; VILLAS, LEANDRO A. Exploring Hybrid-Multimodal Routing to Improve User Experience in Urban Trips. APPLIED SCIENCES-BASEL, v. 11, n. 10 MAY 2021. Web of Science Citations: 0.
DE SOUZA, ALLAN M.; BRAUN, TORSTEN; BOTEGA, LEONARDO C.; VILLAS, LEANDRO A.; LOUREIRO, ANTONIO A. F. Safe and Sound: Driver Safety-Aware Vehicle Re-Routing Based on Spatiotemporal Information. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, v. 21, n. 9, p. 3973-3989, SEPT 2020. Web of Science Citations: 0.
GOMIDES, THIAGO S.; DE GRANDE, ROBSON E.; DE SOUZA, ALLAN M.; SOUZA, FERNANDA S. H.; VILLAS, LEANDRO A.; GUIDONI, DANIEL L. An adaptive and Distributed Traffic Management System using Vehicular Ad-hoc Networks. COMPUTER COMMUNICATIONS, v. 159, p. 317-330, JUN 1 2020. Web of Science Citations: 0.

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