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Authors: Ankhit Pandurangi ; Clare Byrne ; Candis Anderson ; Enxi Cui and Gavin McArdle

Affiliation: School of Computer Science, University College Dublin, Belfield, Ireland

ISBN: 978-989-758-425-1

Keyword(s): Travel Time Prediction, Bus Transport, Spatial Data, Machine Learning.

Abstract: Public transportation applications today face a unique challenge: Providing easy-to-use and intuitive design, while at the same time giving the end user the most updated and accurate information possible. Applications often sacrifice one for the other, finding it hard to balance the two. Furthermore, accurately predicting travel times for public transport is a non-trivial task. Taking factors such as traffic, weather, or delays into account is a complex challenge. This paper describes a data driven analysis approach to resolve this problem by using machine learning to estimate the travel time of buses and places the results in a user-friendly application. In particular, this paper discusses a predictive model which estimates the travel time between pairs of bus stops. The approach is validated using data from the bus network in Dublin, Ireland. While the evaluation of the predictive models show that journey segment predictions are less accurate than the prediction of a bus route in fu ll, the segmented approach gives the user more flexibility in planning a journey. (More)

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Paper citation in several formats:
Pandurangi, A.; Byrne, C.; Anderson, C.; Cui, E. and McArdle, G. (2020). Design and Development of an Application for Predicting Bus Travel Times using a Segmentation Approach.In Proceedings of the 6th International Conference on Geographical Information Systems Theory, Applications and Management - Volume 1: GISTAM, ISBN 978-989-758-425-1, pages 72-80. DOI: 10.5220/0009393800720080

@conference{gistam20,
author={Ankhit Pandurangi. and Clare Byrne. and Candis Anderson. and Enxi Cui. and Gavin McArdle.},
title={Design and Development of an Application for Predicting Bus Travel Times using a Segmentation Approach},
booktitle={Proceedings of the 6th International Conference on Geographical Information Systems Theory, Applications and Management - Volume 1: GISTAM,},
year={2020},
pages={72-80},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009393800720080},
isbn={978-989-758-425-1},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Geographical Information Systems Theory, Applications and Management - Volume 1: GISTAM,
TI - Design and Development of an Application for Predicting Bus Travel Times using a Segmentation Approach
SN - 978-989-758-425-1
AU - Pandurangi, A.
AU - Byrne, C.
AU - Anderson, C.
AU - Cui, E.
AU - McArdle, G.
PY - 2020
SP - 72
EP - 80
DO - 10.5220/0009393800720080

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