Intersection Traffic State Estimation using Speed Transition Matrix and Fuzzy-based Systems

Željko Majstorović, Leo Tišljarić, Edouard Ivanjko, Tonči Carić

2022

Abstract

Urban traffic congestion is a significant problem for almost every city, affecting various aspects of life. Besides increasing travel time, congestion also affects air and life quality causing economic losses. The construction of infrastructure to solve congestion problems is not always feasible, and, at the end, attracts only additional traffic demand. Thus, a better approach for solving the problem of city congestion is by optimal management of the existing infrastructure. Timely detection of traffic congestion on the road level can prevent congestion formation and even improve road network capacity when used for appropriate traffic control actions. Detecting congestion is a complex process that depends on available traffic data. In this paper, for traffic state estimation, including congestion level, at the intersection level, a new method based on Speed Transition Matrix and Fuzzy-Based System is presented. The proposed method utilizes the Connected Vehicle environment. It is tested on a model of an isolated intersection made in SUMO simulation software based on real-world traffic data. The validation results confirm the successful detection of traffic state (congestion level) at intersections.

Paper Citation

in Harvard Style

Majstorović Ž., Tišljarić L., Ivanjko E. and Carić T. (2022). Intersection Traffic State Estimation using Speed Transition Matrix and Fuzzy-based Systems. In Proceedings of the 19th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-585-2, pages 193-200. DOI: 10.5220/0011275500003271

in Bibtex Style

@conference{icinco22,
author={Željko Majstorović and Leo Tišljarić and Edouard Ivanjko and Tonči Carić},
title={Intersection Traffic State Estimation using Speed Transition Matrix and Fuzzy-based Systems},
booktitle={Proceedings of the 19th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2022},
pages={193-200},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011275500003271},
isbn={978-989-758-585-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 19th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Intersection Traffic State Estimation using Speed Transition Matrix and Fuzzy-based Systems
SN - 978-989-758-585-2
AU - Majstorović Ž.
AU - Tišljarić L.
AU - Ivanjko E.
AU - Carić T.
PY - 2022
SP - 193
EP - 200
DO - 10.5220/0011275500003271