Estimativa do volume de passageiros ao longo de uma linha de transporte público por ônibus a partir da geoestatística
DOI:
https://doi.org/10.14295/transportes.v27i3.2007Keywords:
Spatial statistics, Boarding/Alighting survey, Kriging, Transit demand.Abstract
The classical travel demand modeling overlooks an important aspect normally found in the variables of interest: spatial autocorrelation. Recent researches recognize and include this characteristic in travel demand forecasting, but there are limitations regarding the basic elements of treatment used in the approaches. In order to overcome some of the problems and constraints associated with previous researches, the present study relied on spatial dependence between Boarding and Alighting observations, per bus stop, and Loading on sections along a public transport line to generate estimates of these variables in stops and sections that would not be sampled during the passenger Boarding and Alighting survey. This prediction was made by applying Ordinary Kriging to a bus line in the city of São Paulo, Brazil. The results confirmed the feasibility of applying Geostatistics to the estimation of travel demand variables along a bus line.Downloads
References
Anselin, L. (2004) Exploring spatial data with GeoDaTM: a workbook. Urbana, vol. 51, n. 61801. Disponível em: http://www.csiss.org/clearinghouse/GeoDa/geodaworkbook.pdf. Acesso em: ago. 2019.
Anselin, L., I. Syabri e Y. Kho (2005) GeoDa : An Introduction to Spatial Data Analysis. Geographical Analysis, vol. 38, n. 1, p. 5–22. DOI:10.1111/j.0016-7363.2005.00671.x
Bagchi, M. e P. R. White (2005) The potential of public transport smart card data. Transport Policy, v. 12, n. 5, p. 464–474, 2005. DOI:https://doi.org/10.1016/j.tranpol.2005.06.008
Barbosa, H. M., C. M. P. Braga, J. A. P. Coelho, T. Arruda e F. G. Jota (2006) Sistema Automático de Monitoração da Movimentação de Passageiros do Transporte Coletivo por Ônibus - Um Projeto Integrado de Ensino e Desenvolvimento Tecnológico. XX Congresso Nacional de Pesquisa em Transporte da Anpet. Disponível em: https://www.researchgate.net/publication/281441109_Sistema_Automatico_de_Monitoracao_da_Movimentacao_de_Passageiros_do_Transporte_Coletivo_por_Onibus. Acesso em: ago. 2019.
Bartlett, M. S. (1947) The Use of Transformations. Biometrics, vol. 3, n. 1, p. 39–52. DOI:10.2307/3001536
Bayraktar, H. e F. S. Turalioglu (2005) A Kriging-based approach for locating a sampling site in the assessment of air quality. Stochastic Environmental Research and Risk Assessment, vol. 19, n. 4, p. 301–305. DOI:https://doi.org/10.1007/s00477-005-0234-8
Box, G. E. P. e D. R. Cox (1964) An Analysis of Transformations. Journal of the Royal Statistical Society. Series B (Methodological), vol. 26, n. 2, p. 211–252. Disponível em: https://www.jstor.org/stable/2984418. Acesso em: ago. 2019.
Ceder, A. (2007) Public transit planning and operation: modeling, practice and behavior. CRC press.
Chi, G., e Zheng, Y. (2013) Estimating Transport Footprint along Highways at Local Levels: A Combination of Network Analysis and Kriging Methods. International Journal of Sustainable Transportation, vol. 7, n. 3, p. 261–273. DOI:10.1080/15568318.2013.710150
Cressie, N. (1993) Statistics for spatial data. John Wiley & Sons, Inc.
Cressie, N. (1985) Fitting variogram models by weighted least squares. Journal of the International Association for Mathematical Geology, vol. 17, n. 5, p. 563–586. DOI:10.1007/BF01032109
Cressie, N. e D. M. Hawkins (1980). Robust estimation of the variogram. I. Journal of the International Association for Mathematical Geology, vol. 12, n. 2, p. 115-125. DOI:https:// doi.org/10.1007/BF01035243
Eom, J. I. N. K. I., S. I. K. P. Man, T.-Y. Heo e L. F. Huntsinger (2006) Improving the prediction of annual average daily traffic for nonfreeway facilities by applying a spatial statistical method. Transportation Research Record, n. 1968, p. 22–29. DOI:10.3141/1968-03
ESRI (2010) Geostatistical Analyst Tutorial. Environmental Systems Research Institute. Disponível em: < http://help.arcgis.com/en/arcgisdesktop/10.0/pdf/geostatistical-analyst-tutorial.pdf> Acesso em: mai. 2018.
Ferraz, A. C. P. e I. G. E. Torres (2004) Transporte público urbano. (2o ed). RiMa Editora.
Gomes, M. M., C. S. Pitombo, A. Pirdavani e T. Brijs (2018) Geostatistical approach to estimate car occupant fatalities in traffic accidents. Revista Brasileira de Cartografia, vol. 70, n. 4, p. 1231–1256. DOI: 10.14393/rbcv70n4-46140
Gomes, V. A., C. S. Pitombo, S. S. Rocha e A. R. Salgueiro (2016) Kriging Geostatistical Methods for Travel Mode Choice: A Spatial Data Analysis to Travel Demand Forecasting. Open Journal of Statistics, vol. 6, n. 3, p. 514–527. DOI:10.4236/ojs.2016.63044
Goovaerts, P. (2008) Kriging and Semivariogram Deconvolution in the Presence of Irregular Geographical Units. Mathematical geology, vol. 40, n. 1, p. 101–128. Disponível em: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2518693/pdf/nihms-36655.pdf. Acesso em: ago. 2019.
Goovaerts, P. (2012) Geostatistical Analysis of Health Data with Different Levels of Spatial Aggregation. Spatial and Spatio-Temporal Epidemiology, vol. 3, n. 1, p. 83–92. DOI:10.1016/j.sste.2012.02.008
Gundogdu, I. B. (2014) Risk governance for traffic accidents by Geostatistical Analyst methods. International Journal of Research in Engineering and Science, v. 2, n. 9. p. 35-40. Disponível em: http://www.ijres.org/papers/Volume%202/v2-i9/D293540.pdf. Acesso em: ago. 2019.
Hollander, Y. e R. Liu (2008) The principles of calibrating traffic microsimulation models. Transportation, vol. 35, n. 3, p. 347–362. DOI:10.1007/s11116-007-9156-2
IBGE (2018) São Paulo. IBGE Cidades, Instituto Brasileiro de Geografia e Estatística. Disponível em: <https://cidades.ibge.gov.br/brasil/sp/sao-paulo/panorama>. Acesso em: mai. 2018.
IBM (2016) IBM SPSS Statistics 24 Core System User's Guide. International Business Machines. Disponível em: <ftp://public.dhe.ibm.com/software/analytics/spss/documentation/statistics/24.0/en/client/Manuals/IBM_SPSS_Statistics_Core_System_User_Guide.pdf> Acesso em: mai. 2018.
Klatko, T. J., T. U. Saeed, M. Volovski, S. Labi, J. D. Fricker e K. C. Sinha (2017) Addressing the Local-Road VMT Estimation Problem Using Spatial Interpolation Techniques. Journal of Transportation Engineering, Part A: Systems, vol. 143, n. 8. DOI:10.1061/JTEPBS.0000064
Krige, D. G. (1951) A statistical approach to some basic mine valuation problems on the Witwatersrand. Journal of the Southern African Institute of Mining and Metallurgy, vol. 52, n. 6, p. 119–139. Disponível em: https://journals.co.za/docserver/fulltext/saimm/52/6/4823.pdf?expires=1566996803&id=id&accname=guest&checksum=FF6F1BA4B54466840936B8253F9710CA. Acesso em: ago. 2019.
Landim, P. M. B. (2006) Sobre geoestatística e mapas. Terrae Didatica, vol. 2, n. 1, p. 19–33. DOI:https://doi.org/10.20396/td.v2i1.8637463
Lindner, A. e C. S. Pitombo (2017) A Conjoint Approach of Spatial Statistics and a Traditional Method for Travel Mode Choice Issues. Journal of Geovisualization and Spatial Analysis, vol. 2, n. 1. DOI:https://doi.org/10.1007/s41651-017-0008-0
Lindner, A., C. S. Pitombo, S. S. Rocha e J. A. Quintanilha (2016) Estimation of transit trip production using Factorial Kriging with External Drift: an aggregated data case study. Geo-spatial Information Science, vol. 19, n. 4, p. 245–254. DOI:10.1080/10095020.2016.1260811
Majumdar, A., R. B. Noland e W. Y. Ochieng (2004) A spatial and temporal analysis of safety-belt usage and safety-belt laws. Accident Analysis & Prevention, vol. 36, n. 4, p. 551–560. DOI:https://doi.org/10.1016/S0001-4575(03)00061-7
Manepalli, U. R. R. e G. H. Bham (2011) Crash prediction: evaluation of empirical Bayes and kriging Methods. 3rd International Conference on Road Safety and Simulation. Disponível em: http://onlinepubs.trb.org/onlinepubs/conferences/2011/RSS/1/Manepalli,U.pdf. Acesso em: ago. 2019.
Marques, S. F. (2019) Estimativa do volume de passageiros ao longo de uma linha de transporte público por ônibus a partir da Geoestatística. 98 p. Dissertação (Mestrado) – Escola de Engenharia de São Carlos, Universidade de São Paulo, São Carlos, 2019. DOI:https://doi.org/10.11606/D.18.2019.tde-26042019-110232.
Matheron, G. (1971) The Theory of Regionalized Variables and Its Applications. Les Cahiers du Centre de Morphologie Mathematique in Fontainebleu, Paris.
Millard, S. P. (2013) EnvStats. (Springer, Ed)Springer eBooks. vol. 2.
Moran, P. A. P. (1948) The interpretation of statistical maps. Journal of the Royal Statistical Society. Series B (Methodological), vol. 10, n. 2, p. 243–251.Disponível em: https://www.jstor.org/stable/2983777. Acesso em: ago. 2019.
Olea, R. A. (2006) A six-step practical approach to semivariogram modeling. Stochastic Environmental Research and Risk Assessment, vol. 20, n. 5, p. 307–318. DOI:10.1007/s00477-005-0026-1
Oliver, M. A. e R. Webster (1986) Combining Nested and Linear Sampling for Determining the Scale and Form of Spatial Variation of Regionalized Variables. Geographical Analysis, vol. 18, n. 3, p. 227–242. DOI:https://doi.org/10.1111/j.1538-4632.1986.tb00095.x
Oliver, M. A. e R. Webster (2015) Basic steps in geostatistics: the variogram and kriging. Springer.
Pitombo, C. S., A. R. Salgueiro, A. S. G. da Costa e C. A. Isler (2015) A two-step method for mode choice estimation with socioeconomic and spatial information. Spatial Statistics, vol. 11, p. 45–64. DOI:https://doi.org/10.1016/j.spasta.2014.12.002
R Core Team (2018) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
Rocha, S. S., A. Lindner e C. S. Pitombo (2017) Proposal of a Geostatistical Procedure for Transportation Planning Field . Boletim de Ciências Geodésicas, v. 23, n. 4, p. 636–653. DOI:10.1590/s1982-21702017000400042.
São Paulo (2015) Plano de Mobilidade de São Paulo. Prefeitura do Município de São Paulo, Secretaria Municipal de Transportes. Disponível em: < http://www.prefeitura.sp.gov.br/cidade/secretarias/upload/chamadas/planmobsp_v072__1455546429.pdf>. Acesso em: mai. 2018.
Selby, B. e K. M. Kockelman (2013) Spatial prediction of traffic levels in unmeasured locations: Applications of universal kriging and geographically weighted regression. Journal of Transport Geography, vol. 29, p. 24–32. DOI:10.1016/j.jtrangeo.2012.12.009
Shamo, B., Asa, E., e Membah, J. (2015) Linear Spatial Interpolation and Analysis of Annual Average Daily Traffic Data. Journal of Computing in Civil Engineering, vol. 29, n. 1, 4014022. DOI:10.1061/(ASCE)CP.1943-5487.0000281
Shapiro, S. S., e Wilk, M. B. (1965) An analysis of variance test for normality (complete samples). Biometrika, vol. 52, n. 3–4, p. 591–611. Obtido de http://dx.doi.org/10.1093/biomet/52.3-4.591.
SPTrans (2018) Dados SPTrans 2017. São Paulo Transporte S.A.
Subhadip, B., C. Souvik, C. Satish e G. Indrajit (2017) Kriging-Based Approach for Estimation of Vehicular Speed and Passenger Car Units on an Urban Arterial. Journal of Transportation Engineering, Part A: Systems, vol. 143, n. 3. DOI:10.1061/JTEPBS.0000031
Vogel, R. M. (1986) The Probability Plot Correlation Coefficient Test for the Normal, Lognormal, and Gumbel Distributional Hypotheses. Water Resources Research, vol. 22, n. 4, p. 587–590. DOI:https://doi.org/10.1029/WR022i004p00587
Vuchic, V. R. (2005) Urban Transit: Operations, Planning, and Economics. John Wiley & Sons.
Wang, X. e K. Kockelman (2009) Forecasting Network Data. Transportation Research Record: Journal of the Transportation Research Board, vol. 2105, p. 100–108. DOI:10.3141/2105-13
Yamamoto, J. K. e P. M. B. Landim (2015) Geoestatística: conceitos e aplicações. Oficina de textos.
Zhang, D. e X. C. Wang (2014) Transit ridership estimation with network Kriging: A case study of Second Avenue Subway, NYC. Journal of Transport Geography, vol. 41, p. 107–115. DOI:10.1016/j.jtrangeo.2014.08.021
Zimmerman, D. A., G. de Marsily, C. A. Gotway, M. G. Marietta, C. L. Axness, R. L. Beauheim, R. L. Bras, J. Carrera, G. Dagan e P. B. Davies (1998) A comparison of seven geostatistically based inverse approaches to estimate transmissivities for modeling advective transport by groundwater flow. Water Resources Research, vol. 34, n. 6, p. 1373–1413. DOI:doi.org/10.1029/98WR00003
Downloads
Published
How to Cite
Issue
Section
License
Authors who submit papers for publication by TRANSPORTES agree to the following terms:
- Authors retain copyright and grant TRANSPORTES the right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors may enter into separate, additional contractual arrangements for the non-exclusive distribution of this journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in TRANSPORTES.
- Authors are allowed and encouraged to post their work online (e.g., in institutional repositories or on their website) after publication of the article. Authors are encouraged to use links to TRANSPORTES (e.g., DOIs or direct links) when posting the article online, as TRANSPORTES is freely available to all readers.
- Authors have secured all necessary clearances and written permissions to published the work and grant copyright under the terms of this agreement. Furthermore, the authors assume full responsibility for any copyright infringements related to the article, exonerating ANPET and TRANSPORTES of any responsibility regarding copyright infringement.
- Authors assume full responsibility for the contents of the article submitted for review, including all necessary clearances for divulgation of data and results, exonerating ANPET and TRANSPORTES of any responsibility regarding to this aspect.
