Analyzing pedestrian behavior when crossing urban roads by combining RP and SP data

Considering the high crash rates involving pedestrians on urban roads, it is highly relevant to understanding pedestrian crossing behavior. This paper is the first to combine stated preference (SP) and revealed preference (RP) data to evaluate the impact that individual attributes, trip characterist...

Full description

Autores:
Arellana, Julian
Fernández, Stephanie
Figueroa, Miguel
Cantillo, Víctor
Tipo de recurso:
Article of journal
Fecha de publicación:
2022
Institución:
Corporación Universidad de la Costa
Repositorio:
REDICUC - Repositorio CUC
Idioma:
eng
OAI Identifier:
oai:repositorio.cuc.edu.co:11323/9080
Acceso en línea:
https://hdl.handle.net/11323/9080
https://doi.org/10.1016/j.trf.2022.01.012
https://repositorio.cuc.edu.co/
Palabra clave:
Vulnerable road users
Pedestrian crossing behavior
Choice models
RP-SP data
Rights
embargoedAccess
License
© 2022 Elsevier Ltd. All rights reserved.
id RCUC2_a452c02a08c7f47e58195b218f66c56b
oai_identifier_str oai:repositorio.cuc.edu.co:11323/9080
network_acronym_str RCUC2
network_name_str REDICUC - Repositorio CUC
repository_id_str
dc.title.eng.fl_str_mv Analyzing pedestrian behavior when crossing urban roads by combining RP and SP data
title Analyzing pedestrian behavior when crossing urban roads by combining RP and SP data
spellingShingle Analyzing pedestrian behavior when crossing urban roads by combining RP and SP data
Vulnerable road users
Pedestrian crossing behavior
Choice models
RP-SP data
title_short Analyzing pedestrian behavior when crossing urban roads by combining RP and SP data
title_full Analyzing pedestrian behavior when crossing urban roads by combining RP and SP data
title_fullStr Analyzing pedestrian behavior when crossing urban roads by combining RP and SP data
title_full_unstemmed Analyzing pedestrian behavior when crossing urban roads by combining RP and SP data
title_sort Analyzing pedestrian behavior when crossing urban roads by combining RP and SP data
dc.creator.fl_str_mv Arellana, Julian
Fernández, Stephanie
Figueroa, Miguel
Cantillo, Víctor
dc.contributor.author.spa.fl_str_mv Arellana, Julian
Fernández, Stephanie
Figueroa, Miguel
Cantillo, Víctor
dc.subject.proposal.eng.fl_str_mv Vulnerable road users
Pedestrian crossing behavior
Choice models
RP-SP data
topic Vulnerable road users
Pedestrian crossing behavior
Choice models
RP-SP data
description Considering the high crash rates involving pedestrians on urban roads, it is highly relevant to understanding pedestrian crossing behavior. This paper is the first to combine stated preference (SP) and revealed preference (RP) data to evaluate the impact that individual attributes, trip characteristics, built environment, strategies to prevent unauthorized crossing, and traffic flows have on pedestrians crossing decisions in an urban context. SP and RP surveys were designed and collected in Barranquilla (Colombia) near pedestrian bridges or signalized intersections where direct crossings and a high concentration of pedestrian fatalities related to traffic accidents exist. A logit model was estimated using the data enrichment paradigm. Results show that pedestrians weigh risks and costs when choosing how to cross the road. The trajectories observed in the RP component suggest that people prefer direct crossings; nevertheless, pedestrian bridges and signalized intersections can be attractive alternatives if their location matches the origin or destination of the crossing, and no detour is needed to use them. Waiting time; safety; the fine imposed for jaywalking; personal security, and previous decisions are also variables that influence pedestrian behavior when crossing urban roads. These results can be helpful to urban planners and decision-makers interested in proposing appropriate pedestrian infrastructure. The data pooling technique and the inclusion of a cost-related variable (i.e., fine) allowed computing the willingness to pay and marginal substitution rates for attributes of the built environment and other characteristics associated with the crossing decision. Also, the inclusion of several crossing alternatives and situations allowed assessing pedestrian crossing preferences under different scenarios.
publishDate 2022
dc.date.accessioned.none.fl_str_mv 2022-03-16T21:00:27Z
dc.date.available.none.fl_str_mv 2022-03-16T21:00:27Z
2024
dc.date.issued.none.fl_str_mv 2022
dc.type.spa.fl_str_mv Artículo de revista
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_2df8fbb1
dc.type.coar.spa.fl_str_mv http://purl.org/coar/resource_type/c_6501
dc.type.content.spa.fl_str_mv Text
dc.type.driver.spa.fl_str_mv info:eu-repo/semantics/article
dc.type.redcol.spa.fl_str_mv http://purl.org/redcol/resource_type/ART
dc.type.version.spa.fl_str_mv info:eu-repo/semantics/acceptedVersion
format http://purl.org/coar/resource_type/c_6501
status_str acceptedVersion
dc.identifier.issn.spa.fl_str_mv 0048-9697
dc.identifier.uri.spa.fl_str_mv https://hdl.handle.net/11323/9080
dc.identifier.url.spa.fl_str_mv https://doi.org/10.1016/j.trf.2022.01.012
dc.identifier.doi.spa.fl_str_mv 10.1016/j.trf.2022.01.012
dc.identifier.eissn.spa.fl_str_mv 1879-1026
dc.identifier.instname.spa.fl_str_mv Corporación Universidad de la Costa
dc.identifier.reponame.spa.fl_str_mv REDICUC - Repositorio CUC
dc.identifier.repourl.spa.fl_str_mv https://repositorio.cuc.edu.co/
identifier_str_mv 0048-9697
10.1016/j.trf.2022.01.012
1879-1026
Corporación Universidad de la Costa
REDICUC - Repositorio CUC
url https://hdl.handle.net/11323/9080
https://doi.org/10.1016/j.trf.2022.01.012
https://repositorio.cuc.edu.co/
dc.language.iso.none.fl_str_mv eng
language eng
dc.relation.ispartofjournal.spa.fl_str_mv Science of the Total Environment
dc.relation.references.spa.fl_str_mv Anciaes and Jones, 2018 P.R. Anciaes, P. Jones Estimating preferences for different types of pedestrian crossing facilities Transportation Research Part F: Traffic Psychology and Behaviour, 52 (2018), pp. 222-237, 10.1016/j.trf.2017.11.025
Arellana et al., 2021 J. Arellana, V. Alvarez, D. Oviedo, L.A. Guzman Walk this way: Pedestrian accessibility and equity in Barranquilla and Soledad Colombia. Research in Transportation Economics, 86 (2021), p. 2020, 10.1016/j.retrec.2020.101024
Arellana et al., 2012 J. Arellana, A. Daly, S. Hess, J. de Dios Ortúzar, L.I. Rizzi Development of Surveys for Study of Departure Time Choice: Two-Stage Approach to Efficient Design Transportation Research Record, 2303 (1) (2012), pp. 9-18, 10.3141/2303-02
Arellana et al., 2020 J. Arellana, L. Garzón, J. Estrada, V. Cantillo On the use of virtual immersive reality for discrete choice experiments to modelling pedestrian behaviour Journal of Choice Modelling, 37 (March) (2020), pp. 1-18, 10.1016/j.jocm.2020.100251
Arellana et al., 2020 J. Arellana, M. Saltarín, A.M. Larrañaga, V. Alvarez, C.A. Henao Urban walkability considering pedestrians' perceptions of the built environment: A 10-year review and a case study in a medium-sized city in Latin America Transport Reviews, 40 (2) (2020), pp. 183-203
Bendak et al., 2021 S. Bendak, A.M. Alnaqbi, M.Y. Alzarooni, S.M. Aljanaahi, S.J. Alsuwaidi Factors affecting pedestrian behaviors at signalized crosswalks: An empirical study Journal of Safety Research (2021), 10.1016/j.jsr.2020.12.019
Bertulis and Dulaski, 2014 T. Bertulis, D.M. Dulaski Driver Approach Speed and Its Impact on Driver Yielding to Pedestrian Behavior at Unsignalized Crosswalks Transportation Research Record, 2464 (1) (2014), pp. 46-51, 10.3141/2464-06
Cantillo-García et al., 2019 Cantillo-García, V., Guzman, L. A., & Arellana, J. (2019). Socioeconomic strata as proxy variable for household income in transportation research. Evaluation for Bogotá, Medellín, Cali and Barranquilla. DYNA (Colombia), 86(211), 258–267. doi: 10.15446/dyna.v86n211.81821.
Cantillo et al., 2015 V. Cantillo, J. Arellana, M. Rolong Modelling pedestrian crossing behaviour in urban roads: A latent variable approach Transportation Research Part F: Traffic Psychology and Behaviour, 32 (2015), pp. 56-67, 10.1016/j.trf.2015.04.008
Cantillo et al., 2020 V. Cantillo, L. Márquez, C.J. Díaz An exploratory analysis of factors associated with traffic crashes severity in Cartagena Colombia. Accident Analysis and Prevention, 146 (September) (2020), 10.1016/j.aap.2020.105749
Cantillo et al., 2007 Cantillo, V., Ortúzar, JdD, J., & Williams, H. C. W. L. (2007). Modeling discrete choices in the presence of inertia and serial correlation. Transportation Science, 41(2), 195–205. doi: 10.1287/trsc.1060.0178.
Dada et al., 2019 M. Dada, M. Zuidgeest, S. Hess Modelling pedestrian crossing choice on Cape Town's freeways: Caught between a rock and a hard place? Transportation Research Part F: Traffic Psychology and Behaviour, 60 (2019), pp. 245-261, 10.1016/j.trf.2018.10.005
Dane, 2018 DANE. (2018). Resultados censo nacional de población y viviendas. Retrieved from https://www.dane.gov.co/files/censo2018/informacion-tecnica/presentaciones-territorio/180719-CNPV-presentacion-Atlantico.pdf.
Demiroz et al., 2015 Y.I. Demiroz, P. Onelcin, Y. Alver Illegal road crossing behavior of pedestrians at overpass locations: Factors affecting gap acceptance, crossing times and overpass use Accident Analysis and Prevention, 80 (2015), pp. 220-228, 10.1016/j.aap.2015.04.018
Guzman et al., 2021 Guzman, L. A., Arellana, J., & Camargo, J. P. (2021). A hybrid discrete choice model to understand the effect of public policy on fare evasion discouragement in Bogotá's Bus Rapid Transit. Transportation Research Part A: Policy and Practice, 151(November 2020), 140–153. doi: 10.1016/j.tra.2021.07.009.
Han and Chang, 2021 S. Han, J.S. Chang Identifying Priority Crosswalk Locations in Urban Road Networks Journal of Urban Planning and Development, 147 (2) (2021), p. 04021014, 10.1061/(asce)up.1943-5444.0000679
Hasan and Napiah, 2018 R. Hasan, M. Napiah The perception of Malaysian pedestrians toward the use of footbridges Traffic Injury Prevention, 19 (3) (2018), pp. 29 2-297, 10.1080/15389588.2017.1373768
Hasan et al., 2020 R. Hasan, O. Oviedo-Trespalacios, M. Napiah An intercept study of footbridge users and non-users in Malaysia Transportation Research Part F: Traffic Psychology and Behaviour, 73 (2020), pp. 66-79, 10.1016/j.trf.2020.05.011
Hensher et al., 2011 Hensher, D. A., Rose, J. M., Ortúzar, J. de D., & Rizzi, L. I. (2011). Estimating the Value of Risk Reduction for Pedestrians in the Road Environment: An Exploratory Analysis. Journal of Choice Modelling, 4(2), 70–94. doi: 10.1016/S1755-5345(13)70058-7.
Hensher et al., 1998 D. Hensher, J. Louviere, J. Swait Combining sources of preference data Journal of Econometrics, 89 (1–2) (1998), pp. 197-221, 10.1016/S0304-4076(98)00061-X
Holland and Hill, 2007 C. Holland, R. Hill The effect of age, gender and driver status on pedestrians' intentions to cross the road in risky situations Accident Analysis & Prevention, 39 (2) (2007), pp. 224-237, 10.1016/j.aap.2006.07.003
Nacional and de Medicina Legal y Ciencias Forenses, , 2020 Instituto Nacional de Medicina Legal y Ciencias Forenses. (2020). Forensis. Retrieved from https://www.medicinalegal.gov.co/cifras-estadisticas/forensis.
Jha et al., 2017 A. Jha, G. Tiwari, D. Mohan, S. Mukherjee, S. Banerjee Analysis of pedestrian movement on Delhi roads by using naturalistic observation techniques Transportation Research Record, 2634 (2634) (2017), pp. 95-100, 10.3141/2634-14
Lam and Xie, 2002 S.H. Lam, F. Xie Transit path-choice models that use revealed preference and stated preference data Transportation Research Record, 1799 (2002), pp. 58-65, 10.3141/1799-08
Larranaga et al., 2019 Larranaga, A. M., Arellana, J., Rizzi, L. I., Strambi, O., & Cybis, H. B. B. (2019). Using best–worst scaling to identify barriers to walkability: a study of Porto Alegre, Brazil. Transportation (Vol. 46). Springer US. doi: 10.1007/s11116-018-9944-x.
Larrañaga et al., 2016 A.M. Larrañaga, L.I. Rizzi, J. Arellana, O. Strambi, H.B.B. Cybis The influence of built environment and travel attitudes on walking: A case study of Porto Alegre Brazil. International Journal of Sustainable Transportation, 10 (4) (2016), pp. 332-342, 10.1080/15568318.2014.933986
Lee et al., 2021 Y.M. Lee, R. Madigan, O. Giles, L. Garach-Morcillo, G. Markkula, C. Fox, N. Merat Road users rarely use explicit communication when interacting in today's traffic: Implications for automated vehicles Cognition, Technology and Work, 23 (2) (2021), pp. 367-380, 10.1007/s10111-020-00635-y
Li et al., 2009 Li, A., Peng, Q., Zhang, L., & Huang, J. (2009). The Determinant of Pedestrian's Unsafe Behaviors in Urban Traffic System — An Empirical Analysis Based on the Theory of Planned Behavior (TPB). In International Conference on Transportation Engineering. Retrieved from http://dx.doi.org/10.1016/B978-0-12-849873-6.00001-7%0Ahttp://saber.ucv.ve/ojs/index.php/rev_venes/article/view/1112%0Ahttps://www.bps.go.id/dynamictable/2018/05/18/1337/persentase-panjang-jalan-tol-yang-beroperasi-menurut-operatornya-2014.html.
Louviere et al., 2000 J.J. Louviere, D.A. Hensher, J.D. Swait Stated choice methods: Analysis and applications Cambridge Press (2000)
Lucchesi et al., 2021 Lucchesi, S., Larranaga, A. M., Bettella Cybis, H. B., Abreu e Silva, J. A. de, & Arellana, J. A. (2021). Are people willing to pay more to live in a walking environment? A multigroup analysis of the impact of walkability on real estate values and their moderation effects in two Global South cities. Research in Transportation Economics, 86(May 2020). doi: 10.1016/j.retrec.2020.100976.
Lucchesi et al., 2020 S.T. Lucchesi, A.M. Larranaga, J.A.A. Ochoa, A.A.B. Samios, H.B.B. Cybis The role of security and walkability in subjective wellbeing: A multigroup analysis among different age cohorts Research in Transportation Business and Management (2020), p. 100559, 10.1016/j.rtbm.2020.100559
Martinez et al., 2019 Martinez, S., Sanchez, R., & Yañez-Pagans, P. (2019). Road safety: challenges and opportunities in Latin America and the Caribbean. Latin American Economic Review 2019 28:1, 28(1), 1–30. doi: 10.1186/S40503-019-0078-0.
Mcfadden, 1981 Mcfadden, D. (1981). Econometric Models of Probabilistic Choice. Structural Analysis of Discrete Data with Econometric Applications, (198272). Retrieved from https://elsa.berkeley.edu/∼mcfadden/discrete/ch5.pdf.
Mfinanga, 2014 D.A. Mfinanga Implication of pedestrians stated preference of certain attributes of crosswalks Transport Policy, 32 (2014), pp. 156-164, 10.1016/j.tranpol.2014.01.011
Obeng-atuah et al., 2017 Obeng-Atuah, D., Poku-Boansi, & M., Cobbinah, P. B. (2017). Pedestrian crossing in urban Ghana: Safety implications. Journal of Transport & Health, 5, 55-69.
Observatorio nacional de seguridad vial, 2020 Observatorio nacional de seguridad vial. (2020). Boletín estadistico Barranquilla. Retrieved from https://ansv.gov.co/observatorio/.
Oviedo-Trespalacios and Haworth, 2015 O. Oviedo-Trespalacios, N. Haworth Developing a new index for comparing road safety maturity: Case study of the ASEAN Community Journal of the Australasian College of Road Safety, 26 (4) (2015), pp. 45-53
Oviedo-Trespalacios and Scott-Parker, 2017 Oviedo-Trespalacios, O., & Scott-Parker, B. (2017). Footbridge usage in high-traffic flow highways: The intersection of safety and security in pedestrian decision-making. Transportation Research Part F: Traffic Psychology and Behaviour, 49, 177–187. doi: 10.1016/j.trf.2017.06.010.
Papadimitriou, 2012 E. Papadimitriou Theory and models of pedestrian crossing behaviour along urban trips Transportation Research Part F: Traffic Psychology and Behaviour, 15 (1) (2012), pp. 75-94, 10.1016/j.trf.2011.11.007
Papadimitriou et al., 2016 E. Papadimitriou, S. Lassarre, G. Yannis Pedestrian Risk Taking While Road Crossing: A Comparison of Observed and Declared Behaviour Transportation Research Procedia, 14 (2016), pp. 4354-4363, 10.1016/j.trpro.2016.05.357
Papadimitriou et al., 2012 E. Papadimitriou, G. Yannis, J. Golias Analysis of Pedestrian Exposure to Risk in Relation to Crossing Behavior Transportation Research Record: Journal of the Transportation Research Board, 2299 (1) (2012), pp. 79-90, 10.3141/2299-09
Patra et al., 2020 M. Patra, V. Perumal, K.V.K. Rao Modelling the effects of risk factor and time savings on pedestrians' choice of crossing facilities at signalized intersections Case Studies on Transport Policy, 8 (2) (2020), pp. 460-470, 10.1016/j.cstp.2019.10.010
Poó et al., 2018 F.M. Poó, R.D. Ledesma, R. Trujillo Pedestrian crossing behavior, an observational study in the city of Ushuaia Argentina. Traffic Injury Prevention, 19 (3) (2018), pp. 305-310, 10.1080/15389588.2017.1391380
Pursula and Weurlander, 1999 M. Pursula, M. Weurlander Modeling level-of-service factors in public transportation route choice Transport Research Record, 1669 (1) (1999), pp. 30-37
Quistberg et al., 2014 D.A. Quistberg, T.D. Koepsell, L.N. Boyle, J.J. Miranda, B.D. Johnston, B.E. Ebel Pedestrian signalization and the risk of pedestrian-motor vehicle collisions in Lima, Peru Accident Analysis & Prevention, 70 (2014), pp. 273-281, 10.1016/j.aap.2014.04.012
Rankavat and Tiwari, 2016 S. Rankavat, G. Tiwari Pedestrians perceptions for utilization of pedestrian facilities – Delhi, India Transportation Research Part F: Traffic Psychology and Behaviour, 42 (2016), pp. 495-499, 10.1016/j.trf.2016.02.005
Räsänen et al., 2007 M. Räsänen, T. Lajunen, F. Alticafarbay, C. Aydin Pedestrian self-reports of factors influencing the use of pedestrian bridges Accident Analysis and Prevention, 39 (5) (2007), pp. 969-973, 10.1016/j.aap.2007.01.004
Sinclair and Zuidgeest, 2016 M. Sinclair, M. Zuidgeest Investigations into pedestrian crossing choices on Cape Town freeways Transportation Research Part F: Traffic Psychology and Behaviour, 42 (2016), pp. 479-494, 10.1016/j.trf.2015.07.006
Sisiopiku and Akin, 2003 V.P. Sisiopiku, D. Akin Pedestrian behaviors at and perceptions towards various pedestrian facilities: An examination based on observation and survey data Transportation Research Part F: Traffic Psychology and Behaviour, 6 (4) (2003), pp. 249-274, 10.1016/j.trf.2003.06.001
Soathong et al., 2021 Soathong, A., Chowdhury, S., Wilson, D., & Ranjitkar, P. (2021). Investigating the motivation for pedestrians' risky crossing behaviour at urban mid-block road sections. Travel Behaviour and Society, 22(May 2020), 155–165. doi: 10.1016/j.tbs.2020.09.005.
Tao et al., 2009 W. Tao, S. Mehndiratta, E. Deakin Compulsory Convenience ? How large arterials and land use affect midblock crossing in Fushun, China Journal of Transport and Land Use. (2009)
Uttley and Fotios, 2017 J. Uttley, S. Fotios The effect of ambient light condition on road traffic collisions involving pedestrians on pedestrian crossings Accident Analysis and Prevention, 108 (September) (2017), pp. 189-200, 10.1016/j.aap.2017.09.005
Vallejo-Borda et al., 2020 J.A. Vallejo-Borda, V. Cantillo, A. Rodriguez-Valencia A perception-based cognitive map of the pedestrian perceived quality of service on urban sidewalks Transportation Research Part F: Traffic Psychology and Behaviour, 73 (2020), pp. 107-118, 10.1016/j.trf.2020.06.013
Victoria and Galvis, 2014 I.C. Victoria, O. Galvis Road Safety Conditions and Estimated Economic Cost of Traffic Fatalities in Medium-Size Colombian Cities Transportation Research Record, 2465 (1) (2014), pp. 40-47, 10.3141/2465-06
Villaveces et al., 2012 A. Villaveces, L.A. Nieto, D. Ortega, J.F. Ríos, J.J. Medina, M.I. Gutiérrez, D. Rodríguez Pedestrians’ perceptions of walkability and safety in relation to the built environment in Cali, Colombia, 2009–10 Injury Prevention, 18 (5) (2012), pp. 291-297, 10.1136/injuryprev-2011-040223
World Health Organization, 2019 World Health Organization. (2019). Global status report on road safety 2018. WHO. Zareharofteh et al., 2021 F. Zareharofteh, A. Hidarnia, M.A. Morowatisharifabad, M. Eslami Unsafe behaviours in Iranian adult pedestrians Journal of Transport and Health, 21 (March) (2021), 10.1016/j.jth.2021.101058
Zhang et al., 2019 Zhang, C., Chen, F., & Wei, Y. (2019). Evaluation of pedestrian crossing behavior and safety at uncontrolled mid-block crosswalks with different numbers of lanes in China. Accident Analysis and Prevention, 123(December 2018), 263–273. doi: 10.1016/j.aap.2018.12.002.
Zhang et al., 2018 C. Zhang, B. Zhou, T.Z. Qiu, S. Liu Pedestrian crossing behaviors at uncontrolled multi-lane mid-block crosswalks in developing world Journal of Safety Research, 64 (2018), pp. 145-154, 10.1016/j.jsr.2017.12.018
Zhang et al., 2016 W. Zhang, K. Wang, L. Wang, Z. Feng, Y. Du Exploring factors affecting pedestrians' red-light running behaviors at intersections in China Accident Analysis and Prevention, 96 (2016), pp. 71-78, 10.1016/j.aap.2016.07.038
Zhu and Sze, 2021 Zhu, D., & Sze, N. N. (2021). Propensities of red light running of pedestrians at the two-stage crossings with split pedestrian signal phases. Accident Analysis and Prevention, 151(September 2020). doi: 10.1016/j.aap.2020.105958.
dc.relation.citationendpage.spa.fl_str_mv 275
dc.relation.citationstartpage.spa.fl_str_mv 259
dc.relation.citationvolume.spa.fl_str_mv 85
dc.rights.spa.fl_str_mv © 2022 Elsevier Ltd. All rights reserved.
Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)
dc.rights.uri.spa.fl_str_mv https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.accessrights.spa.fl_str_mv info:eu-repo/semantics/embargoedAccess
dc.rights.coar.spa.fl_str_mv http://purl.org/coar/access_right/c_f1cf
rights_invalid_str_mv © 2022 Elsevier Ltd. All rights reserved.
Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)
https://creativecommons.org/licenses/by-nc-nd/4.0/
http://purl.org/coar/access_right/c_f1cf
eu_rights_str_mv embargoedAccess
dc.format.extent.spa.fl_str_mv 17 páginas
dc.format.mimetype.spa.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv Elsevier
dc.publisher.place.spa.fl_str_mv Netherlands
institution Corporación Universidad de la Costa
dc.source.url.spa.fl_str_mv https://www.sciencedirect.com/science/article/pii/S1369847822000183
bitstream.url.fl_str_mv https://repositorio.cuc.edu.co/bitstreams/62171275-580d-4e29-9a54-ce0cf6139f7c/download
https://repositorio.cuc.edu.co/bitstreams/ded33f53-b524-44af-ac25-6fcc7a41e7aa/download
https://repositorio.cuc.edu.co/bitstreams/a0033a69-dad9-4a75-9203-ed4193d5fe05/download
https://repositorio.cuc.edu.co/bitstreams/4ec3cc87-0229-49c1-9d56-159e96d8c1ef/download
bitstream.checksum.fl_str_mv 1588139ab3ec23b08c7d9e9d5136e9a5
e30e9215131d99561d40d6b0abbe9bad
75d695abdaad9422863c298c8c939d70
28e6d8d707231fb09d497809e9d59a25
bitstream.checksumAlgorithm.fl_str_mv MD5
MD5
MD5
MD5
repository.name.fl_str_mv Repositorio de la Universidad de la Costa CUC
repository.mail.fl_str_mv repdigital@cuc.edu.co
_version_ 1811760855151280128
spelling Arellana, JulianFernández, StephanieFigueroa, MiguelCantillo, Víctor2022-03-16T21:00:27Z20242022-03-16T21:00:27Z20220048-9697https://hdl.handle.net/11323/9080https://doi.org/10.1016/j.trf.2022.01.01210.1016/j.trf.2022.01.0121879-1026Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/Considering the high crash rates involving pedestrians on urban roads, it is highly relevant to understanding pedestrian crossing behavior. This paper is the first to combine stated preference (SP) and revealed preference (RP) data to evaluate the impact that individual attributes, trip characteristics, built environment, strategies to prevent unauthorized crossing, and traffic flows have on pedestrians crossing decisions in an urban context. SP and RP surveys were designed and collected in Barranquilla (Colombia) near pedestrian bridges or signalized intersections where direct crossings and a high concentration of pedestrian fatalities related to traffic accidents exist. A logit model was estimated using the data enrichment paradigm. Results show that pedestrians weigh risks and costs when choosing how to cross the road. The trajectories observed in the RP component suggest that people prefer direct crossings; nevertheless, pedestrian bridges and signalized intersections can be attractive alternatives if their location matches the origin or destination of the crossing, and no detour is needed to use them. Waiting time; safety; the fine imposed for jaywalking; personal security, and previous decisions are also variables that influence pedestrian behavior when crossing urban roads. These results can be helpful to urban planners and decision-makers interested in proposing appropriate pedestrian infrastructure. The data pooling technique and the inclusion of a cost-related variable (i.e., fine) allowed computing the willingness to pay and marginal substitution rates for attributes of the built environment and other characteristics associated with the crossing decision. Also, the inclusion of several crossing alternatives and situations allowed assessing pedestrian crossing preferences under different scenarios.17 páginasapplication/pdfengElsevierNetherlands© 2022 Elsevier Ltd. All rights reserved.Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)https://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/embargoedAccesshttp://purl.org/coar/access_right/c_f1cfAnalyzing pedestrian behavior when crossing urban roads by combining RP and SP dataArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/acceptedVersionhttps://www.sciencedirect.com/science/article/pii/S1369847822000183Science of the Total EnvironmentAnciaes and Jones, 2018 P.R. Anciaes, P. Jones Estimating preferences for different types of pedestrian crossing facilities Transportation Research Part F: Traffic Psychology and Behaviour, 52 (2018), pp. 222-237, 10.1016/j.trf.2017.11.025Arellana et al., 2021 J. Arellana, V. Alvarez, D. Oviedo, L.A. Guzman Walk this way: Pedestrian accessibility and equity in Barranquilla and Soledad Colombia. Research in Transportation Economics, 86 (2021), p. 2020, 10.1016/j.retrec.2020.101024Arellana et al., 2012 J. Arellana, A. Daly, S. Hess, J. de Dios Ortúzar, L.I. Rizzi Development of Surveys for Study of Departure Time Choice: Two-Stage Approach to Efficient Design Transportation Research Record, 2303 (1) (2012), pp. 9-18, 10.3141/2303-02Arellana et al., 2020 J. Arellana, L. Garzón, J. Estrada, V. Cantillo On the use of virtual immersive reality for discrete choice experiments to modelling pedestrian behaviour Journal of Choice Modelling, 37 (March) (2020), pp. 1-18, 10.1016/j.jocm.2020.100251Arellana et al., 2020 J. Arellana, M. Saltarín, A.M. Larrañaga, V. Alvarez, C.A. Henao Urban walkability considering pedestrians' perceptions of the built environment: A 10-year review and a case study in a medium-sized city in Latin America Transport Reviews, 40 (2) (2020), pp. 183-203Bendak et al., 2021 S. Bendak, A.M. Alnaqbi, M.Y. Alzarooni, S.M. Aljanaahi, S.J. Alsuwaidi Factors affecting pedestrian behaviors at signalized crosswalks: An empirical study Journal of Safety Research (2021), 10.1016/j.jsr.2020.12.019Bertulis and Dulaski, 2014 T. Bertulis, D.M. Dulaski Driver Approach Speed and Its Impact on Driver Yielding to Pedestrian Behavior at Unsignalized Crosswalks Transportation Research Record, 2464 (1) (2014), pp. 46-51, 10.3141/2464-06Cantillo-García et al., 2019 Cantillo-García, V., Guzman, L. A., & Arellana, J. (2019). Socioeconomic strata as proxy variable for household income in transportation research. Evaluation for Bogotá, Medellín, Cali and Barranquilla. DYNA (Colombia), 86(211), 258–267. doi: 10.15446/dyna.v86n211.81821.Cantillo et al., 2015 V. Cantillo, J. Arellana, M. Rolong Modelling pedestrian crossing behaviour in urban roads: A latent variable approach Transportation Research Part F: Traffic Psychology and Behaviour, 32 (2015), pp. 56-67, 10.1016/j.trf.2015.04.008Cantillo et al., 2020 V. Cantillo, L. Márquez, C.J. Díaz An exploratory analysis of factors associated with traffic crashes severity in Cartagena Colombia. Accident Analysis and Prevention, 146 (September) (2020), 10.1016/j.aap.2020.105749Cantillo et al., 2007 Cantillo, V., Ortúzar, JdD, J., & Williams, H. C. W. L. (2007). Modeling discrete choices in the presence of inertia and serial correlation. Transportation Science, 41(2), 195–205. doi: 10.1287/trsc.1060.0178.Dada et al., 2019 M. Dada, M. Zuidgeest, S. Hess Modelling pedestrian crossing choice on Cape Town's freeways: Caught between a rock and a hard place? Transportation Research Part F: Traffic Psychology and Behaviour, 60 (2019), pp. 245-261, 10.1016/j.trf.2018.10.005Dane, 2018 DANE. (2018). Resultados censo nacional de población y viviendas. Retrieved from https://www.dane.gov.co/files/censo2018/informacion-tecnica/presentaciones-territorio/180719-CNPV-presentacion-Atlantico.pdf.Demiroz et al., 2015 Y.I. Demiroz, P. Onelcin, Y. Alver Illegal road crossing behavior of pedestrians at overpass locations: Factors affecting gap acceptance, crossing times and overpass use Accident Analysis and Prevention, 80 (2015), pp. 220-228, 10.1016/j.aap.2015.04.018Guzman et al., 2021 Guzman, L. A., Arellana, J., & Camargo, J. P. (2021). A hybrid discrete choice model to understand the effect of public policy on fare evasion discouragement in Bogotá's Bus Rapid Transit. Transportation Research Part A: Policy and Practice, 151(November 2020), 140–153. doi: 10.1016/j.tra.2021.07.009.Han and Chang, 2021 S. Han, J.S. Chang Identifying Priority Crosswalk Locations in Urban Road Networks Journal of Urban Planning and Development, 147 (2) (2021), p. 04021014, 10.1061/(asce)up.1943-5444.0000679Hasan and Napiah, 2018 R. Hasan, M. Napiah The perception of Malaysian pedestrians toward the use of footbridges Traffic Injury Prevention, 19 (3) (2018), pp. 29 2-297, 10.1080/15389588.2017.1373768Hasan et al., 2020 R. Hasan, O. Oviedo-Trespalacios, M. Napiah An intercept study of footbridge users and non-users in Malaysia Transportation Research Part F: Traffic Psychology and Behaviour, 73 (2020), pp. 66-79, 10.1016/j.trf.2020.05.011Hensher et al., 2011 Hensher, D. A., Rose, J. M., Ortúzar, J. de D., & Rizzi, L. I. (2011). Estimating the Value of Risk Reduction for Pedestrians in the Road Environment: An Exploratory Analysis. Journal of Choice Modelling, 4(2), 70–94. doi: 10.1016/S1755-5345(13)70058-7.Hensher et al., 1998 D. Hensher, J. Louviere, J. Swait Combining sources of preference data Journal of Econometrics, 89 (1–2) (1998), pp. 197-221, 10.1016/S0304-4076(98)00061-XHolland and Hill, 2007 C. Holland, R. Hill The effect of age, gender and driver status on pedestrians' intentions to cross the road in risky situations Accident Analysis & Prevention, 39 (2) (2007), pp. 224-237, 10.1016/j.aap.2006.07.003Nacional and de Medicina Legal y Ciencias Forenses, , 2020 Instituto Nacional de Medicina Legal y Ciencias Forenses. (2020). Forensis. Retrieved from https://www.medicinalegal.gov.co/cifras-estadisticas/forensis.Jha et al., 2017 A. Jha, G. Tiwari, D. Mohan, S. Mukherjee, S. Banerjee Analysis of pedestrian movement on Delhi roads by using naturalistic observation techniques Transportation Research Record, 2634 (2634) (2017), pp. 95-100, 10.3141/2634-14Lam and Xie, 2002 S.H. Lam, F. Xie Transit path-choice models that use revealed preference and stated preference data Transportation Research Record, 1799 (2002), pp. 58-65, 10.3141/1799-08Larranaga et al., 2019 Larranaga, A. M., Arellana, J., Rizzi, L. I., Strambi, O., & Cybis, H. B. B. (2019). Using best–worst scaling to identify barriers to walkability: a study of Porto Alegre, Brazil. Transportation (Vol. 46). Springer US. doi: 10.1007/s11116-018-9944-x.Larrañaga et al., 2016 A.M. Larrañaga, L.I. Rizzi, J. Arellana, O. Strambi, H.B.B. Cybis The influence of built environment and travel attitudes on walking: A case study of Porto Alegre Brazil. International Journal of Sustainable Transportation, 10 (4) (2016), pp. 332-342, 10.1080/15568318.2014.933986Lee et al., 2021 Y.M. Lee, R. Madigan, O. Giles, L. Garach-Morcillo, G. Markkula, C. Fox, N. Merat Road users rarely use explicit communication when interacting in today's traffic: Implications for automated vehicles Cognition, Technology and Work, 23 (2) (2021), pp. 367-380, 10.1007/s10111-020-00635-yLi et al., 2009 Li, A., Peng, Q., Zhang, L., & Huang, J. (2009). The Determinant of Pedestrian's Unsafe Behaviors in Urban Traffic System — An Empirical Analysis Based on the Theory of Planned Behavior (TPB). In International Conference on Transportation Engineering. Retrieved from http://dx.doi.org/10.1016/B978-0-12-849873-6.00001-7%0Ahttp://saber.ucv.ve/ojs/index.php/rev_venes/article/view/1112%0Ahttps://www.bps.go.id/dynamictable/2018/05/18/1337/persentase-panjang-jalan-tol-yang-beroperasi-menurut-operatornya-2014.html.Louviere et al., 2000 J.J. Louviere, D.A. Hensher, J.D. Swait Stated choice methods: Analysis and applications Cambridge Press (2000)Lucchesi et al., 2021 Lucchesi, S., Larranaga, A. M., Bettella Cybis, H. B., Abreu e Silva, J. A. de, & Arellana, J. A. (2021). Are people willing to pay more to live in a walking environment? A multigroup analysis of the impact of walkability on real estate values and their moderation effects in two Global South cities. Research in Transportation Economics, 86(May 2020). doi: 10.1016/j.retrec.2020.100976.Lucchesi et al., 2020 S.T. Lucchesi, A.M. Larranaga, J.A.A. Ochoa, A.A.B. Samios, H.B.B. Cybis The role of security and walkability in subjective wellbeing: A multigroup analysis among different age cohorts Research in Transportation Business and Management (2020), p. 100559, 10.1016/j.rtbm.2020.100559Martinez et al., 2019 Martinez, S., Sanchez, R., & Yañez-Pagans, P. (2019). Road safety: challenges and opportunities in Latin America and the Caribbean. Latin American Economic Review 2019 28:1, 28(1), 1–30. doi: 10.1186/S40503-019-0078-0.Mcfadden, 1981 Mcfadden, D. (1981). Econometric Models of Probabilistic Choice. Structural Analysis of Discrete Data with Econometric Applications, (198272). Retrieved from https://elsa.berkeley.edu/∼mcfadden/discrete/ch5.pdf.Mfinanga, 2014 D.A. Mfinanga Implication of pedestrians stated preference of certain attributes of crosswalks Transport Policy, 32 (2014), pp. 156-164, 10.1016/j.tranpol.2014.01.011Obeng-atuah et al., 2017 Obeng-Atuah, D., Poku-Boansi, & M., Cobbinah, P. B. (2017). Pedestrian crossing in urban Ghana: Safety implications. Journal of Transport & Health, 5, 55-69.Observatorio nacional de seguridad vial, 2020 Observatorio nacional de seguridad vial. (2020). Boletín estadistico Barranquilla. Retrieved from https://ansv.gov.co/observatorio/.Oviedo-Trespalacios and Haworth, 2015 O. Oviedo-Trespalacios, N. Haworth Developing a new index for comparing road safety maturity: Case study of the ASEAN Community Journal of the Australasian College of Road Safety, 26 (4) (2015), pp. 45-53Oviedo-Trespalacios and Scott-Parker, 2017 Oviedo-Trespalacios, O., & Scott-Parker, B. (2017). Footbridge usage in high-traffic flow highways: The intersection of safety and security in pedestrian decision-making. Transportation Research Part F: Traffic Psychology and Behaviour, 49, 177–187. doi: 10.1016/j.trf.2017.06.010.Papadimitriou, 2012 E. Papadimitriou Theory and models of pedestrian crossing behaviour along urban trips Transportation Research Part F: Traffic Psychology and Behaviour, 15 (1) (2012), pp. 75-94, 10.1016/j.trf.2011.11.007Papadimitriou et al., 2016 E. Papadimitriou, S. Lassarre, G. Yannis Pedestrian Risk Taking While Road Crossing: A Comparison of Observed and Declared Behaviour Transportation Research Procedia, 14 (2016), pp. 4354-4363, 10.1016/j.trpro.2016.05.357Papadimitriou et al., 2012 E. Papadimitriou, G. Yannis, J. Golias Analysis of Pedestrian Exposure to Risk in Relation to Crossing Behavior Transportation Research Record: Journal of the Transportation Research Board, 2299 (1) (2012), pp. 79-90, 10.3141/2299-09Patra et al., 2020 M. Patra, V. Perumal, K.V.K. Rao Modelling the effects of risk factor and time savings on pedestrians' choice of crossing facilities at signalized intersections Case Studies on Transport Policy, 8 (2) (2020), pp. 460-470, 10.1016/j.cstp.2019.10.010Poó et al., 2018 F.M. Poó, R.D. Ledesma, R. Trujillo Pedestrian crossing behavior, an observational study in the city of Ushuaia Argentina. Traffic Injury Prevention, 19 (3) (2018), pp. 305-310, 10.1080/15389588.2017.1391380Pursula and Weurlander, 1999 M. Pursula, M. Weurlander Modeling level-of-service factors in public transportation route choice Transport Research Record, 1669 (1) (1999), pp. 30-37Quistberg et al., 2014 D.A. Quistberg, T.D. Koepsell, L.N. Boyle, J.J. Miranda, B.D. Johnston, B.E. Ebel Pedestrian signalization and the risk of pedestrian-motor vehicle collisions in Lima, Peru Accident Analysis & Prevention, 70 (2014), pp. 273-281, 10.1016/j.aap.2014.04.012Rankavat and Tiwari, 2016 S. Rankavat, G. Tiwari Pedestrians perceptions for utilization of pedestrian facilities – Delhi, India Transportation Research Part F: Traffic Psychology and Behaviour, 42 (2016), pp. 495-499, 10.1016/j.trf.2016.02.005Räsänen et al., 2007 M. Räsänen, T. Lajunen, F. Alticafarbay, C. Aydin Pedestrian self-reports of factors influencing the use of pedestrian bridges Accident Analysis and Prevention, 39 (5) (2007), pp. 969-973, 10.1016/j.aap.2007.01.004Sinclair and Zuidgeest, 2016 M. Sinclair, M. Zuidgeest Investigations into pedestrian crossing choices on Cape Town freeways Transportation Research Part F: Traffic Psychology and Behaviour, 42 (2016), pp. 479-494, 10.1016/j.trf.2015.07.006Sisiopiku and Akin, 2003 V.P. Sisiopiku, D. Akin Pedestrian behaviors at and perceptions towards various pedestrian facilities: An examination based on observation and survey data Transportation Research Part F: Traffic Psychology and Behaviour, 6 (4) (2003), pp. 249-274, 10.1016/j.trf.2003.06.001Soathong et al., 2021 Soathong, A., Chowdhury, S., Wilson, D., & Ranjitkar, P. (2021). Investigating the motivation for pedestrians' risky crossing behaviour at urban mid-block road sections. Travel Behaviour and Society, 22(May 2020), 155–165. doi: 10.1016/j.tbs.2020.09.005.Tao et al., 2009 W. Tao, S. Mehndiratta, E. Deakin Compulsory Convenience ? How large arterials and land use affect midblock crossing in Fushun, China Journal of Transport and Land Use. (2009)Uttley and Fotios, 2017 J. Uttley, S. Fotios The effect of ambient light condition on road traffic collisions involving pedestrians on pedestrian crossings Accident Analysis and Prevention, 108 (September) (2017), pp. 189-200, 10.1016/j.aap.2017.09.005Vallejo-Borda et al., 2020 J.A. Vallejo-Borda, V. Cantillo, A. Rodriguez-Valencia A perception-based cognitive map of the pedestrian perceived quality of service on urban sidewalks Transportation Research Part F: Traffic Psychology and Behaviour, 73 (2020), pp. 107-118, 10.1016/j.trf.2020.06.013Victoria and Galvis, 2014 I.C. Victoria, O. Galvis Road Safety Conditions and Estimated Economic Cost of Traffic Fatalities in Medium-Size Colombian Cities Transportation Research Record, 2465 (1) (2014), pp. 40-47, 10.3141/2465-06Villaveces et al., 2012 A. Villaveces, L.A. Nieto, D. Ortega, J.F. Ríos, J.J. Medina, M.I. Gutiérrez, D. Rodríguez Pedestrians’ perceptions of walkability and safety in relation to the built environment in Cali, Colombia, 2009–10 Injury Prevention, 18 (5) (2012), pp. 291-297, 10.1136/injuryprev-2011-040223World Health Organization, 2019 World Health Organization. (2019). Global status report on road safety 2018. WHO. Zareharofteh et al., 2021 F. Zareharofteh, A. Hidarnia, M.A. Morowatisharifabad, M. Eslami Unsafe behaviours in Iranian adult pedestrians Journal of Transport and Health, 21 (March) (2021), 10.1016/j.jth.2021.101058Zhang et al., 2019 Zhang, C., Chen, F., & Wei, Y. (2019). Evaluation of pedestrian crossing behavior and safety at uncontrolled mid-block crosswalks with different numbers of lanes in China. Accident Analysis and Prevention, 123(December 2018), 263–273. doi: 10.1016/j.aap.2018.12.002.Zhang et al., 2018 C. Zhang, B. Zhou, T.Z. Qiu, S. Liu Pedestrian crossing behaviors at uncontrolled multi-lane mid-block crosswalks in developing world Journal of Safety Research, 64 (2018), pp. 145-154, 10.1016/j.jsr.2017.12.018Zhang et al., 2016 W. Zhang, K. Wang, L. Wang, Z. Feng, Y. Du Exploring factors affecting pedestrians' red-light running behaviors at intersections in China Accident Analysis and Prevention, 96 (2016), pp. 71-78, 10.1016/j.aap.2016.07.038Zhu and Sze, 2021 Zhu, D., & Sze, N. N. (2021). Propensities of red light running of pedestrians at the two-stage crossings with split pedestrian signal phases. Accident Analysis and Prevention, 151(September 2020). doi: 10.1016/j.aap.2020.105958.27525985Vulnerable road usersPedestrian crossing behaviorChoice modelsRP-SP dataPublicationORIGINALAnalyzing pedestrian behavior when crossing urban roads by combining RP and SP data.pdfAnalyzing pedestrian behavior when crossing urban roads by combining RP and SP data.pdfapplication/pdf5414230https://repositorio.cuc.edu.co/bitstreams/62171275-580d-4e29-9a54-ce0cf6139f7c/download1588139ab3ec23b08c7d9e9d5136e9a5MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-83196https://repositorio.cuc.edu.co/bitstreams/ded33f53-b524-44af-ac25-6fcc7a41e7aa/downloade30e9215131d99561d40d6b0abbe9badMD52TEXTAnalyzing pedestrian behavior when crossing urban roads by combining RP and SP data.pdf.txtAnalyzing pedestrian behavior when crossing urban roads by combining RP and SP data.pdf.txttext/plain89153https://repositorio.cuc.edu.co/bitstreams/a0033a69-dad9-4a75-9203-ed4193d5fe05/download75d695abdaad9422863c298c8c939d70MD53THUMBNAILAnalyzing pedestrian behavior when crossing urban roads by combining RP and SP data.pdf.jpgAnalyzing pedestrian behavior when crossing urban roads by combining RP and SP data.pdf.jpgimage/jpeg12856https://repositorio.cuc.edu.co/bitstreams/4ec3cc87-0229-49c1-9d56-159e96d8c1ef/download28e6d8d707231fb09d497809e9d59a25MD5411323/9080oai:repositorio.cuc.edu.co:11323/90802024-09-17 14:11:50.119https://creativecommons.org/licenses/by-nc-nd/4.0/© 2022 Elsevier Ltd. All rights reserved.open.accesshttps://repositorio.cuc.edu.coRepositorio de la Universidad de la Costa CUCrepdigital@cuc.edu.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