Research Article
A Predictive Model of Arrival Times for Smart Shuttle Buses in Astana, Kazakhstan
@INPROCEEDINGS{10.1007/978-3-031-84312-9_2, author={Darya Taratynova and Assel Kassenova and Bissenbay Dauletbayev and Muammar Al-Shedivat and Eugene Pinsky}, title={A Predictive Model of Arrival Times for Smart Shuttle Buses in Astana, Kazakhstan}, proceedings={Computer Science and Education in Computer Science. 20th EAI International Conference, CSECS 2024, Sofia, Bulgaria, June 28--30, 2024, Proceedings}, proceedings_a={CSECS}, year={2025}, month={3}, keywords={ETA Prediction KNN Shuttle bus Transportation Clustering}, doi={10.1007/978-3-031-84312-9_2} }- Darya Taratynova
Assel Kassenova
Bissenbay Dauletbayev
Muammar Al-Shedivat
Eugene Pinsky
Year: 2025
A Predictive Model of Arrival Times for Smart Shuttle Buses in Astana, Kazakhstan
CSECS
Springer
DOI: 10.1007/978-3-031-84312-9_2
Abstract
Accurate prediction of the estimated time of arrival (ETA) for buses is crucial for shuttle companies aiming to enhance profitability and minimize costs. This paper proposes leveraging historical bus route data to predict estimated bus arrivals at specific stations, employing K-Nearest Neighbors (KNN) supervised machine learning (ML) techniques. We develop a simple and interpretable solution that abstains from complexity, as bus routes dynamically adapt to passenger demands.
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