Urban Mobility Challenges – An Exploratory Analysis of Public Transportation Data in Curitiba

Juan Jose Rodriguez Vila, Nádia Puchalski Kozievitch, Tatiana M. C. Gadda, Keiko Fonseca, Marcelo O Rosa, Luiz C. Gomes-jr, Monika Akbar


Smart transportation systems have been generating a large amount of data overtime (bus routes, users data, bus schedules, etc.). Such data provide a number of opportunities to identify various facets of user behavior, transportation needs, and traffic trends. In this paper we address some of the urban mobility challenges (addressed by the Brazilian Computer Society), from a number of different perspectives, including (i) pattern discovery, (ii) statistical analysis, (iii) data integration, and (iv) open and connected data. In particular, we present an exploratory data analysis with GIS for public transportation toward a case study in Curitiba, Brazil, using different data sources.

Texto completo:



R. Souza, I. P. Oliveira, F. Junior, L. Sales, and F. Ferraz. Beyond efficiency: How to use geolocation applications to improve citizens well-being. In The Fourth International Conference on Smart Systems, Devices and Technologies, páginas 37 – 40, 2015.

A. Monteiro. Frota de veículos cresce mais rápido que a estrutura viária no país. http://www1.folha.uol.com.br/cotidiano/2014/08/1503030-frota-de-veiculos-cresce-mais-rapido-que-a-estrutura-viaria-no-pais.shtml, Mar. 2015.

A. C. Salgado, C. L. R. da Motta, F. M. Santoro. Grandes Desafios da Computação no Brasil – Relatos do 3º Seminário. http://www.sbc.org.br/documentos-da-sbc/send/141-grandes-desafios/802-grandesdesafiosdacomputaonobrasil, Mar. 2015.

Instituto Brasileiro de Geografia e Estatística. http://www.ibge.gov.br, Mai. 2015.

J. Kotkin. The World’s Smartest Cities. http://www.forbes.com/2009/12/03/infrastructure-economy-urban-opinions-columnists-smart-cities-09-joel-kotkin.html, Abr. 2015.

C40 Cities. http://www.c40.org, Mai. 2015.

F. Duarte, T. Gadda, C. A. M. Luna and F. T. Souza. What to expect from the future leaders of bogotá and curitiba in terms of public transport: Opinions and practices among university students. Transportation Research Part F: Traffic Psychology and Behaviour, 38, páginas 7 – 21, 2016.

M. T. Sebastiani, R. Luders and K. V. O. Fonseca. Evaluating electric bus operation for a real-world brt public transportation using simulation optimization. IEEE Transactions on Intelligent Transportation Systems, PP(99), páginas 1–10, 2016.

IPPUC - Instituto de Pesquisa Planejamento Urbano de Curitiba. http://ippuc.org.br/, Mar. 2015.

Portal da Prefeitura de Curitiba – Dados Abertos. http://www.curitiba.pr.gov.br/DADOSABERTOS/, Mai. 2015.

P. H. T. Zannin, F. B. Diniz and W. A. Barbosa. Environmental noise pollution in the city of Curitiba, Brazil. Applied Acoustics, 63(4), páginas 351 – 358, 2012.

A. Calixto, F. B. Diniz, and P. Zannin. The statistical modeling of road traffic noise in an urban setting. Cities, 20, páginas 1–74, 2016.

P. H. T. Zannin, A. Calixto, F. B. Diniz and J. A. C. Ferreira. A survey of urban noise annoyance in a large Brazilian city: the importance of a subjective analysis in conjunction with an objective analysis. Environmental Impact Assessment Review, 23, páginas 245–255, 2003.

D. C. Suresh, B. Agrawal, J. Yang and W. Najjar. Energy-efficient encoding techniques for off-chip data buses. ACM Transactions on Embed. Computing Systems, 8(2), páginas 9:1–9:23, 2009.

Park, H.-S. and Kim, J.-D. (2011). Modeling and Analysis of DTN in Metropolitan Bus Network. In ICUIMC ’11, páginas 20:1–20:10, 2011.

NIST/SEMATECH. E-Handbook of Statistical Methods. http://www.itl.nist.gov/div898/handbook/, Set. 2016.

F. Hartwig and B Dearing. Exploratory Data Analysis. 07. SAGE Publications. 1979.

W. Martinez, A. Martinez, and J. Solka. Exploratory Data Analysis with MATLAB, Second Edition. Chapman & Hall/CRC Computer Science & Data Analysis. Taylor & Francis, 2010.

L. Stenneth, O. Wolfson, P. S. Yu and B. Xu. Transportation mode detection using mobile phones and gis information. In GIS ’11, páginas 54–63, New York, ACM, 2011.

J. Mennis and D. Guo. Spatial data mining and geographic knowledge discovery - an introduction. Computers, Environment and Urban Systems, 33(6), páginas 403 – 408, 2009.

J. A. Butler. Designing Geodatabases for Transportation, Esri Press, 2008.

G. Arampatzis, C. Kiranoudis, P. Scaloubacas and D. Assimacopoulos. A gis-based decision support system for planning urban transportation policies. European Journal of Operational Research, 152(2), páginas 465 – 475, 2004.

T. H. M. de Oliveira, M. Painho and R. Henriques. A spatial decision support system for the Portuguese public transportation sector. In IWGS ’12, páginas 84–90, 2012.

CTA Bus Tracker. http://www.ctabustracker.com/, Abr. 2016.

Chicago Transit Authority (CTA). http://www.transitchicago.com/about/facts.aspx, Abr. 2016.

M. F. Goodchild. Gis and transportation: Status and challenges. Geoinformatica, 4(2), páginas 127–139, 2000.

J. Castillo. Smart cities: 5 security areas CIOs should watch. http://business.inquirer.net/208811/smart-cities-5-security-areas-cios-should-watch, Abr. 2015.

I. Vilajosana, J. Llosa, B. Martinez, M. Domingo-Prieto, A. Angles and X. Vilajosana. Bootstrapping smart cities through a self-sustainable model based on big data flows. IEEE Communications Magazine, 51(6), páginas 128–134, 2013.

http://br.okfn.org/category/dados-abertos/, Abr. 2016.

http://smartcitiesforumbrasil.com.br/, Abr. 2016.

Redes Inteligentes Brasil. http://redesinteligentesbrasil.org.br/o-projeto.html, Abr. 2015.

H. Chourabi, T. Nam, S. Walker, J. R. Gil-Garcia, S. Mellouli, K. Nahon, T. A. Pardo and H. J. Scholl. Understanding smart cities: An integrative framework. In System Science (HICSS), 45th Hawaii International Conference on, páginas 2289–2297, 2012.

Open Street Map. http://www.openstreetmap.org, Mai. 2015.

Urbanização de Curitiba. https://www.urbs.curitiba.pr.gov.br/ Abr. 2016.

L. da F. Costa, F. A. Rodrigues, G. Travieso and P. R. V Boas. Characterization of complex networks: A survey of measurements. Advances in Physics, 56(1), páginas 167–242, 2007.

G. L. Barczyszyn. Integração de dados geográficos para planejamento urbano da cidade de Curitiba. Trabalho de Conclusão de Curso, Universidade Tecnológica Federal do Paraná, 2015

PostGIS. http://www.postgis.net, Mai. 2014.

Portal de Dados Abertos da Prefeitura de São Paulo. http://dados.prefeitura.sp.gov.br/, Jun. 2015.

Portal de Dados Abertos da Prefeitura de Recife. http://dados.recife.pe.gov.br/dataset, Mai 2015.

Portal de Dados Geográficos Abertos da Cidade do Rio de Janeiro. http://portalgeo.pcrj.opendata.arcgis.com/, Mai. 2015.

Política de Dados Abertos. http://multimidia.curitiba.pr.gov.br/2014/00147194.pdf, Abr. 2015.

Hackathon Curitiba. http://hackathon.curitiba.pr.gov.br, Mai. 2015.

http://www.curitiba.pr.gov.br/noticias/curitiba-e-holanda-vao-trabalhar-juntas-em-projetos-de-ciclomobilidade-para-a-cidade/37601, Abr. 2016.

MoU between Brazilian and Swedish Institutions to promote sustainable urban development in Curitiba. http://multimidia.curitiba.pr.gov.br/2015/00166636.pdf, Abr. 2016.

URBS. https://www.urbs.curitiba.pr.gov.br/ Apr. 2016.

E. L. C. Silva, N. P. Kozievitch, K. Fonseca, M. Rosa, R. Luders. Combining K-means Method and Complex Network Analysis to Evaluate City Mobility. In Proceedings of 19th IEEE International Conference on Intelligent Transportation Systems, 2016.

Marker Clusterer Algorithm. https://developers.google.com/maps/articles/toomanymarkers Apr. 2016.

MTA. http://web.mta.info/developers/developer-data-terms.html#data Apr. 2016.

N. P. Kozievitch, T. M. C. Gadda, K. Fonseca, M. Rosa, L. C. Gomez-Jr, M. Akbar. Exploratory Analysis of Public Transportation Data in Curitiba. In: 43o Seminário Integrado de Software e Hardware, Porto Alegre, páginas 1656-1666, 2016.

LeafletJS http://leafletjs.com/ Apr. 2016.

HeatMap https://developers.google.com/maps/documentation/javascript/heatmaplayer Apr. 2016.

O. R. Zaiane, A. Foss, C. Lee, C., W. Wang, On Data Clustering AnalysisL Scalability. Constraints, and Validations. Advances in Knowledge Discovery and Data Mining, London: Springer-Verlag. Páginas: .28-39, 2002.

DOI: https://doi.org/10.13037/ras.vol12n1.145


  • Não há apontamentos.

Revista de Informática Aplicada - USCS/UFABC


Indexadores que a RIA faz parte: