Bus bunching detection by mining sequences of headway deviations

  • Authors:

  • Luís Moreira-Matias;Carlos Ferreira;João Gama;João Mendes-Moreira;Jorge Freire de Sousa

  • Affiliations:

  • Departamento de Engenharia Informàtica, Faculdade de Engenharia, Universidade do Porto, Porto, Portugal,LIAAD-INESC Porto L.A., Porto, Portugal;LIAAD-INESC Porto L.A., Porto, Portugal,Instituto Superior de Engenharia do Porto, Instituto Politécnico do Porto, Porto, Portugal;LIAAD-INESC Porto L.A., Porto, Portugal,Faculdade de Economia, Universidade do Porto, Porto, Portugal;Departamento de Engenharia Informàtica, Faculdade de Engenharia, Universidade do Porto, Porto, Portugal,LIAAD-INESC Porto L.A., Porto, Portugal;Departamento de Engenharia Industrial e Gestão, Faculdade de Engenharia, Universidade do Porto, Porto, Portugal

  • Venue:
  • ICDM'12 Proceedings of the 12th Industrial conference on Advances in Data Mining: applications and theoretical aspects
  • Year:
  • 2012

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Abstract

In highly populated urban zones, it is common to notice headway deviations (HD) between pairs of buses. When these events occur in a bus stop, they often cause bus bunching (BB) in the following bus stops. Several proposals have been suggested to mitigate this problem. In this paper, we propose to find BBS (Bunching Black Spots) --- sequences of bus stops where systematic HD events cause the formation of BB. We run a sequence mining algorithm, named PrefixSpan, to find interesting events available in time series. We prove that we can accurately model the BB trip usual pattern like a frequent sequence mining problem. The subsequences proved to be a promising way of identify the route' schedule points to adjust in order to mitigate such events.