Hybrid Framework for Real-Time Traffic Flow Estimation Using Breadth-First Search

Sajjad Mahdaviabbasabad, Ynte Vanderhoydonc, Roeland Vandenberghe, Siegfried Mercelis

2025

Abstract

Traffic flow data is essential for urban planning, logistics, transport management, and similar applications. However, achieving full sensor coverage across a road network is often infeasible due to high installation and maintenance costs. Simulation data from traffic models can help in filling this gap. However, calibrating and validating these traffic models is time-consuming. This paper presents a framework that combines real-time traffic flow predictions from sensor-equipped road segments with 24-hour static simulation data across an entire network. By applying a method based on the Breadth-First Search algorithm, this framework updates network-wide traffic flow by utilizing the data-driven predictions at sensor-equipped road segments and simulation data. Evaluation on a network with over 27000 road segments shows that this approach improves prediction accuracy over static simulation and is viable for real-time deployment.

Paper Citation

in Harvard Style

Mahdaviabbasabad S., Vanderhoydonc Y., Vandenberghe R. and Mercelis S. (2025). Hybrid Framework for Real-Time Traffic Flow Estimation Using Breadth-First Search. In Proceedings of the 11th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS; ISBN 978-989-758-745-0, SciTePress, pages 421-430. DOI: 10.5220/0013271700003941

in Bibtex Style

@conference{vehits25,
author={Sajjad Mahdaviabbasabad and Ynte Vanderhoydonc and Roeland Vandenberghe and Siegfried Mercelis},
title={Hybrid Framework for Real-Time Traffic Flow Estimation Using Breadth-First Search},
booktitle={Proceedings of the 11th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS},
year={2025},
pages={421-430},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013271700003941},
isbn={978-989-758-745-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS
TI - Hybrid Framework for Real-Time Traffic Flow Estimation Using Breadth-First Search
SN - 978-989-758-745-0
AU - Mahdaviabbasabad S.
AU - Vanderhoydonc Y.
AU - Vandenberghe R.
AU - Mercelis S.
PY - 2025
SP - 421
EP - 430
DO - 10.5220/0013271700003941
PB - SciTePress