Solutions for intelligent and cooperative transportation systems based on urban computing

• Grant number: 18/19639-5
• Support Opportunities: Regular Research Grants
• Duration: November 01, 2019 - October 31, 2021
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computer Systems
• Principal Investigator: Leandro Aparecido Villas
• Grantee: Leandro Aparecido Villas
• Host Institution: Instituto de Computação (IC). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Associated researchers: Antonio Alfredo Ferreira Loureiro ; Daniel Ludovico Guidoni ; Edmundo Roberto Mauro Madeira ; Luiz Fernando Bittencourt ; Nelson Luis Saldanha da Fonseca
• Associated scholarship(s): 20/11485-9 - Solutions for Intelligent and Cooperative Transportation Systems based on Urban Computing, BP.TT; 19/24937-8 - Solutions for Intelligent and Cooperative Transportation Systems based on Urban Computing, BP.TT; 20/03123-0 - Solutions for Intelligent and Cooperative Transportation Systems based on Urban Computing, BP.TT

Abstract

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)

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)

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. (18/19639-5)

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. (19/24937-8, 18/19639-5)

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. (18/23064-8, 18/23126-3, 18/19639-5, 18/12447-3, 15/24494-8, 20/11259-9)