Bus Bunching detection: A sequence mining approach

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

Authors

Moreira Matias, L (Author) Other; Ferreira, C (Author) Other; Gama, J (Author) Other; João Mendes-Moreira (Author) FEUP; De Sousa, JF (Author) FEUP

Conference proceedings International

Title: CEUR Workshop Proceedings

Pages: 13-17

Workshop on Ubiquitous Data Mining, UDM 2012 - In Conjunction with the 20th European Conference on Artificial Intelligence, ECAI 2012

27 August 2012 through 31 August 2012

Indexing

Scopus - 0 Citations

Other information

Authenticus ID: P-00G-1QT

Abstract (EN): Mining public transportation networks is a growing and explosive challenge due to the increasing number of information available. In highly populated urban zones, the vehicles can often fail the schedule. Such fails cause headway deviations (HD) between high-frequency bus pairs. In this paper, we propose to identify systematic HD which usually provokes the phenomenon known as Bus Bunching (BB). We use the PrefixSpan algorithm to accurately mine sequences of bus stops where multiple HD frequently emerges, forcing two or more buses to clump. Our results are promising: 1) we demonstrated that the BB origin can be modeled like a sequence mining problem where 2) the discovered patterns can easily identify the route schedule points to adjust in order to mitigate such events.

Language: English

Type (Professor's evaluation): Scientific