Real-Time Bus Arrival Prediction: A Deep Learning Approach for Enhanced Urban Mobility

Narges Rashvand, Sanaz Hosseini, Mona Azarbayjani, Hamed Tabkhi

2024

Abstract

In urban settings, bus transit stands as a significant mode of public transportation, yet faces hurdles in delivering accurate and reliable arrival times. This discrepancy often culminates in delays and a decline in ridership, particularly in areas with a heavy reliance on bus transit. A prevalent challenge is the mismatch between actual bus arrival times and their scheduled counterparts, leading to disruptions in fixed schedules. Our study, utilizing New York City bus data, reveals an average delay of approximately eight minutes between scheduled and actual bus arrival times. This research introduces an innovative, AI-based, data-driven methodology for predicting bus arrival times at various transit points (stations), offering a collective prediction for all bus lines within large metropolitan areas. Through the deployment of a fully connected neural network, our method elevates the accuracy and efficiency of public bus transit systems. Our comprehensive evaluation encompasses over 200 bus lines and 2 million data points, showcasing an error margin of under 40 seconds for arrival time estimates. Additionally, the inference time for each data point in the validation set is recorded at below 0.006 ms, demonstrating the potential of our Neural-Net based approach in substantially enhancing the punctuality and reliability of bus transit systems.

Paper Citation

in Harvard Style

Rashvand N., Hosseini S., Azarbayjani M. and Tabkhi H. (2024). Real-Time Bus Arrival Prediction: A Deep Learning Approach for Enhanced Urban Mobility. In Proceedings of the 13th International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES; ISBN 978-989-758-681-1, SciTePress, pages 123-132. DOI: 10.5220/0012365500003639

in Bibtex Style

@conference{icores24,
author={Narges Rashvand and Sanaz Hosseini and Mona Azarbayjani and Hamed Tabkhi},
title={Real-Time Bus Arrival Prediction: A Deep Learning Approach for Enhanced Urban Mobility},
booktitle={Proceedings of the 13th International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES},
year={2024},
pages={123-132},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012365500003639},
isbn={978-989-758-681-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES
TI - Real-Time Bus Arrival Prediction: A Deep Learning Approach for Enhanced Urban Mobility
SN - 978-989-758-681-1
AU - Rashvand N.
AU - Hosseini S.
AU - Azarbayjani M.
AU - Tabkhi H.
PY - 2024
SP - 123
EP - 132
DO - 10.5220/0012365500003639
PB - SciTePress