Modelling traffic accident duration on urban roads with high traffic variability using survival models: a case study on Fortaleza arterial roads

Authors

  • Vandeyberg Nogueira de Souza Universidade Federal do Ceará, Fortaleza, Ceará, Brasil
  • Francisco Moraes de Oliveira Neto Universidade Federal do Ceará, Fortaleza, Ceará, Brasil https://orcid.org/0000-0002-7756-4619

DOI:

https://doi.org/10.58922/transportes.v31i2.2837

Keywords:

Traffic accidents, non-recurring congestion, survival analysis

Abstract

Unexpected congestions are a common problem in the lives of urban citizens who need to travel to carry out their activities. This type of congestion causes unexpected delays to drivers and has traffic accidents and their duration as the main factor for their formation. In order to contribute to this problem, this study aimed to analyze the duration of traffic accidents on arterial roads of Fortaleza, Brazil, and their relationship with their causal factors. The duration of accidents was estimated based on traffic data obtained from electronic surveillance equipment, as the accident databases did not have this information. For this purpose, we generated profiles of speed and flow proportion per lane for days with accident and typical days to differentiate the impact on traffic caused by an accident from a typical traffic variability. The method detected the duration of 316 accidents with an average duration of 71 minutes and a standard deviation of 43 minutes. Next, a set of suggested hypotheses to explain the variability of accident duration was analyzed using survival models. The calibrated model showed that the severity of the accident, the traffic conditions at the accident location, the quantity and scheduling of the traffic agents, and the number of vehicles involved can have a significant impact on accident duration.   

Downloads

Download data is not yet available.

References

Haule, H.J.; T. Sando; R. Lentz et al. (2018) Evaluating the impact and clearance duration of freeway incidents. International Journal of Transportation Science and Technology, v. 8, n. 1, p. 13-24. DOI: 10.1016/j.ijtst.2018.06.005. DOI: https://doi.org/10.1016/j.ijtst.2018.06.005

Hojati, A. T.; Ferreira, L.; Charles, P. et al. (2012) Analysing freeway traffic-incident duration using an Australian data set, Road and Transport Research, v. 21, n. 2, p. 19-31.

Hojati, A. T.; L. Ferreira; S. Washington et al. (2013) Hazard based models for freeway traffic incident duration, Accident Analysis and Prevention, v. 52, p. 171-81. DOI: 10.1016/j.aap.2012.12.037. PMid:23333698. DOI: https://doi.org/10.1016/j.aap.2012.12.037

Hojati, A. T.; L. Ferreira; S. Washington et al. (2014) Modelling total duration of traffic incidents including incident detection and recovery time, Accident Analysis and Prevention, v. 71, p. 296-305. DOI: 10.1016/j.aap.2014.06.006. DOI: https://doi.org/10.1016/j.aap.2014.06.006

Hou, L.; Y. Lao; Y. Wang et al. (2014) Time-varying effects of influential factors on incident clearance time using a nonproportional hazard-based model. Transportation Research Part A, Policy and Practice, v. 63, p. 12-24. DOI: 10.1016/j.tra.2014.02.014. DOI: https://doi.org/10.1016/j.tra.2014.02.014

IBGE (2020) Brazilian Census of 2020. Available at: <https://cidades.ibge.gov.br/brasil/ce/fortaleza/panorama> (accessed 05/25/2023).

Junhua, W.; C. Haozhe and Q. Shi (2013) Estimating freeway incident duration using accelerated failure time modeling, Safety Science, v. 54, p. 43-50. DOI: 10.1016/j.ssci.2012.11.009. DOI: https://doi.org/10.1016/j.ssci.2012.11.009

Khattak, A.J.; J. Liu; B. Wali et al. (2016) Modeling traffic incident duration using quantile regression, Transportation Research Record: Journal of the Transportation Research Board, v. 2554, n. 1, p. 139-48. DOI: 10.3141/2554-15. DOI: https://doi.org/10.3141/2554-15

Khattak, A.J.; J.L. Schofer and M. Wang (1995) A simple time sequential procedure for predicting freeway incident duration, IVHS J., v. 2, n. 2, p. 113-38. DOI: 10.1080/10248079508903820. DOI: https://doi.org/10.1080/10248079508903820

Kleinbaum, D.G. and M. Klein (2012) Survival Analysis: A Self-Learning Text (3th ed.). New York: Springer. DOI: 10.1007/978-1-4419-6646-9. DOI: https://doi.org/10.1007/978-1-4419-6646-9

Lee, J.; J. Chung and B. Son (2010) Incident clearance time analysis for Korean freeways using structural equation model, Journal of the Eastern Asia Society for Transportation Studies, v. 8, n. 1, p. 1878-91. DOI: 10.11175/eastpro.2009.0.360.0.

Li, R. (2015) Traffic incident duration analysis and prediction models based on the survival analysis approach, IET Intelligent Transport Systems, v. 9, n. 4, p. 351-8. DOI: 10.1049/iet-its.2014.0036. DOI: https://doi.org/10.1049/iet-its.2014.0036

Li, R.; F.C. Pereira and M.E. Ben-Akiva (2018) Overview of traffic incident duration analysis and prediction, European Transport Research Review, v. 10, n. 22, p. 22. DOI: 10.1186/s12544-018-0300-1. DOI: https://doi.org/10.1186/s12544-018-0300-1

Li, R.; M. Guo; H. Lu et al.(2017) Analysis of the different duration stages of accidents with hazard-based model. International Journal of Intelligent Transportation Systems Research, v. 7, n. 16, p. 7-16. DOI: 10.1007/s13177-015-0115-6. DOI: https://doi.org/10.1007/s13177-015-0115-6

Nam, D. and F. Mannering (2000) An exploratory hazard-based analysis of highway incident duration, Transportation Research Part A, Policy and Practice, v. 34, n. 2, p. 85-102. DOI: 10.1016/S0965-8564(98)00065-2. DOI: https://doi.org/10.1016/S0965-8564(98)00065-2

Shi, Y.; L. Zhang and P. Liu (2015) Survival analysis of urban traffic incident duration: a case study at shanghai expressways, Journal of Computing, v. 26, n. 1, p. 29-39. Available at: <http://www.csroc.org.tw/journal/JOC26- 1/JOC26-1-3.pdf> (accessed 05/25/2023)

Skabardonis, A.; P. Varaiya and K. Petty (2003) Measuring recurrent and nonrecurrent traffic congestion. Transportation Research Record: Journal of the Transportation Research Board, v. 1856, n. 1, p. 118-24. DOI: 10.3141/1856-12. DOI: https://doi.org/10.3141/1856-12

Souza, V.N. and F.M. Oliveira Neto (2020) Analysis of accident duration on urban arterials roads, TRANSPORTES, v. 28, n. 3, p. 266-80. DOI: 10.14295/transportes.v28i3.2142. DOI: https://doi.org/10.14295/transportes.v28i3.2142

Valenti, G.; M. Lelli and D. Cucina (2010) A comparative study of models for the incident duration prediction, European Transport Research Review, v. 2, n. 2, p. 103-11. DOI: 10.1007/s12544-010-0031-4. DOI: https://doi.org/10.1007/s12544-010-0031-4

Washington, S.P.; M.G. Karlaftis and F.L. Mannering (2003) Statistical and Econometric Methods for Transportation Data Analysis. New York: Chapman & Hall/CRC. DOI: 10.1201/9780203497111. DOI: https://doi.org/10.1201/9780203497111

Xie, K.; K. Ozbay and H. Yang (2015) Spatial analysis of highway incident durations in the context of Hurricane Sandy, Accident Analysis and Prevention, v. 74, p. 77-86. DOI: 10.1016/j.aap.2014.10.015. PMid:25463947. DOI: https://doi.org/10.1016/j.aap.2014.10.015

Zhang, H. and A.J. Khattak (2010) Analysis of cascading incident event durations on urban freeways, Transportation Research Record: Journal of the Transportation Research Board, v. 2178, n. 1, p. 30-9. DOI: 10.3141/2178-04. DOI: https://doi.org/10.3141/2178-04

Imagem da capa, volume 31, número 2

Downloads

Published

2023-07-11

How to Cite

Nogueira de Souza, V. ., & Moraes de Oliveira Neto, F. (2023). Modelling traffic accident duration on urban roads with high traffic variability using survival models: a case study on Fortaleza arterial roads. Transportes, 31(2), e2837. https://doi.org/10.58922/transportes.v31i2.2837

Issue

Vol. 31 No. 2 (2023)

Section

Articles

License

Copyright (c) 2023 Vandeyberg Nogueira de Souza, Francisco Moraes de Oliveira Neto

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Authors who submit papers for publication by TRANSPORTES agree to the following terms:

  1. The authors retain the copyright and grant Transportes the right of first publication of the manuscript, without any financial charge, and waive any other remuneration for its publication by ANPET.
  2. Upon publication by Transportes, the manuscript is automatically licensed under the Creative Commons License CC BY 4.0 license. This license permits the work to be shared with proper attribution to the authors and its original publication in this journal.
  3. Authors are authorized to enter into additional separate contracts for the non-exclusive distribution of the version of the manuscript published in this journal (e.g., publishing in an institutional repository or as a book chapter), with recognition of the initial publication in this journal, provided that such a contract does not imply an endorsement of the content of the manuscript or the new medium by ANPET.
  4. Authors are permitted and encouraged to publish and distribute their work online (e.g., in institutional repositories or on their personal websites) after the editorial process is complete. As Transportes provides open access to all published issues, authors are encouraged to use links to the DOI of their article in these cases.
  5. Authors guarantee that they have obtained the necessary authorization from their employers for the transfer of rights under this agreement, if these employers hold any copyright over the manuscript. Additionally, authors assume all responsibility for any copyright infringements by these employers, releasing ANPET and Transportes from any responsibility in this regard.
  6. Authors assume full responsibility for the content of the manuscript, including the necessary and appropriate authorizations for the disclosure of collected data and obtained results, releasing ANPET and Transportes from any responsibility in this regard.