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Authors: Armands Kviesis 1 ; Aleksejs Zacepins 1 ; Vitalijs Komasilovs 1 and Marcela Munizaga 2

Affiliations: 1 Latvia University of Agriculture, Latvia ; 2 Universidad de Chile, Chile

Keyword(s): Smart Public Transport, Public Buses, Arrival Time, GPS Data.

Abstract: The increase of population has intensified everyday rush. Traffic congestions are still a problem in cities and are one of the main cause for public transport delays. City residents and visitors have experienced time loss by using public transport buses, because of waiting at the bus stops and not knowing if the bus is delayed or already serviced the stop. Therefore it is valuable for people to know at what time the bus should arrive (or is it already missed) at specific bus stop. Real-time public bus tracking and management system development has been the focus of many researchers, and many studies have been done in this area. This paper focuses on bus travel time prediction comparison between linear regression and support vector regression models (SVR), when using limited data set. Data were limited in a way that only historical GPS (Global Positioning System) coordinates of bus location (recorded each 30 seconds) and driven distance were used, there were no information about arriv al/departure times, delays or dwell times. Distance between stops and delay (assumed values based on route observations by authors) were used as inputs for both models. It was concluded that SVR algorithm showed better results, but the difference was not significantly large. (More)

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Paper citation in several formats:
Kviesis, A.; Zacepins, A.; Komasilovs, V. and Munizaga, M. (2018). Bus Arrival Time Prediction with Limited Data Set using Regression Models. In Proceedings of the 4th International Conference on Vehicle Technology and Intelligent Transport Systems - RESIST; ISBN 978-989-758-293-6; ISSN 2184-495X, SciTePress, pages 643-647. DOI: 10.5220/0006816306430647

@conference{resist18,
author={Armands Kviesis. and Aleksejs Zacepins. and Vitalijs Komasilovs. and Marcela Munizaga.},
title={Bus Arrival Time Prediction with Limited Data Set using Regression Models},
booktitle={Proceedings of the 4th International Conference on Vehicle Technology and Intelligent Transport Systems - RESIST},
year={2018},
pages={643-647},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006816306430647},
isbn={978-989-758-293-6},
issn={2184-495X},
}

TY - CONF

JO - Proceedings of the 4th International Conference on Vehicle Technology and Intelligent Transport Systems - RESIST
TI - Bus Arrival Time Prediction with Limited Data Set using Regression Models
SN - 978-989-758-293-6
IS - 2184-495X
AU - Kviesis, A.
AU - Zacepins, A.
AU - Komasilovs, V.
AU - Munizaga, M.
PY - 2018
SP - 643
EP - 647
DO - 10.5220/0006816306430647
PB - SciTePress