Bus bunching detection by mining sequences of headway deviations

• Type: Article in International Conference Proceedings Book
• Date: 2012

Authors

Luís Moreira-Matias (Author) FEUP; Carlos Ferreira (Author) Other; João Gama (Author) FEP; João Mendes-Moreira (Author) FEUP; Jorge Freire de Sousa (Author) FEUP

Conference proceedings International

Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Pages: 77-91

12th Industrial Conference on Advances in Data Mining, ICDM 2012

Berlin, 13 July 2012 through 20 July 2012

Indexing

ISI Web of Science

Scopus - 26 Citations

Scientific classification

FOS: Natural sciences > Computer and information sciences

Other information

Authenticus ID: P-008-5CA

DOI: 10.1007/978-3-642-31488-9_7

Abstract (EN): 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. © 2012 Springer-Verlag.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 15