Analysis of delays and accepted gaps in signalized crossings: a study in Fortaleza using deep learning computer vision techniques

Authors

  • Francisco Altanizio Batista de Castro Junior Universidade Federal do Ceará, Fortaleza, Ceará, Brasil https://orcid.org/0009-0001-8265-0845
  • Manoel Mendonça de Castro Neto Universidade Federal do Ceará, Fortaleza, Ceará, Brasil
  • Flávio José Craveiro Cunto Universidade Federal do Ceará, Fortaleza, Ceará, Brasil

DOI:

https://doi.org/10.58922/transportes.v31i2.2845

Keywords:

Pedestrians crossings, Delay, Accepted gap, Computer vision

Abstract

The increasing attention to active transport in developing countries has motivated studies on understanding the factors that affect its users. Delay is one of the main indicators of the level of service of pedestrian crossings and it is affected by the available gaps. This work aims to relate delays and accepted gaps in signalized crossings in Fortaleza, as well as to compare the estimated delays with those obtained by the method of the Highway Capacity Manual – 6th. edition. The data were collected by means of computer vision algorithms, in five crossing located at signalized intersections, resulting in 1642 crossing observations. The method includes a cluster analysis of delay and accepted gap. The results showed similarity of the estimated delays with those obtained with the HCM. Also, the relationship between accepted gap and delay allows an inference about the risk of pedestrian crossings.

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Published

2023-08-24

How to Cite

Batista de Castro Junior, F. A., Castro Neto, M. M. de, & Craveiro Cunto, F. J. (2023). Analysis of delays and accepted gaps in signalized crossings: a study in Fortaleza using deep learning computer vision techniques. TRANSPORTES, 31(2), e2845. https://doi.org/10.58922/transportes.v31i2.2845

Issue

Section

Artigos Vencedores do Prêmio ANPET Produção Científica