title: Increasing Intelligence in Inter-Vehicle Communications to Reduce Traffic Congestions: Experiments in Urban and Highway Environments.
abstract: Intelligent Transportation Systems (ITS) rely on Inter-Vehicle Communication (IVC) to streamline the operation of vehicles by managing vehicle traffic, assisting drivers with safety and sharing information, as well as providing appropriate services for passengers. Traffic congestion is an urban mobility problem, which causes stress to drivers and economic losses. In this context, this work proposes a solution for the detection, dissemination and control of congested roads based on inter-vehicle communication, called INCIDEnT. The main goal of the proposed solution is to reduce the average trip time, CO emissions and fuel consumption by allowing motorists to avoid congested roads. The simulation results show that our proposed solution leads to short delays and a low overhead. Moreover, it is efficient with regard to the coverage of the event and the distance to which the information can be propagated. The findings of the investigation show that the proposed solution leads to (i) high hit rate in the classification of the level of congestion, (ii) a reduction in average trip time, (iii) a reduction in fuel consumption, and (iv) reduced CO emissions.
authors.affiliation: University of Ottawa, Ottawa, Ontario, Canada.|Federal Institute of São Paulo (IFSP), Catanduva, São Paulo, Brazil.
authors.forename: Rodolfo I
authors.identifier: http://orcid.org/0000-0003-2982-4006
authors.initials: RI
authors.lastname: Meneguette
authors.affiliation: Institute of Mathematics and Computer Sciences (ICMC), University of São Paulo (USP), São Carlos, Brazil.
authors.forename: Geraldo P R
authors.initials: GP
authors.lastname: Filho
authors.affiliation: Computer Science Department, Federal University of Sao Joao del-Rei, Sao Joao del-Rei, Brazil.
authors.forename: Daniel L
authors.initials: DL
authors.lastname: Guidoni
authors.affiliation: Applied Computing Lab, Vale Institute of Technology, Belem, Para, Brazil.
authors.forename: Gustavo
authors.initials: G
authors.lastname: Pessin
authors.affiliation: Institute of Computing (IC), University of Campinas (UNICAMP), Campinas, Sao Paulo, Brazil.
authors.forename: Leandro A
authors.initials: LA
authors.lastname: Villas
authors.affiliation: Institute of Mathematics and Computer Sciences (ICMC), University of São Paulo (USP), São Carlos, Brazil.|Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, United States of America.
authors.forename: Jó
authors.initials: J
authors.lastname: Ueyama
mesh_terms: D000397:Air Pollution / Q000517:prevention & control; D001185:Artificial Intelligence; D001336:Automobiles; D002947:Cities; D003142:Communication; D001335:Vehicle Emissions / Q000517:prevention & control
chemical_list: D001335:Vehicle Emissions