Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Traffic Flow Techniques Applied to the Modeling of the Intersection of East 53rd and East 56th Streets in Panama City: A Practical Case

Carlos Rovetto
,
Edmanuel Cruz
ORCID logo ,
Ivonne Nunez
ORCID logo ,
Keyla Santana
,
Andrzej Smolarz
ORCID logo ,
José Rangel
ORCID logo ,
Elia Esther Cano
* ORCID logo
Version 1 : Received: 4 May 2023 / Approved: 5 May 2023 / Online: 5 May 2023 (08:04:34 CEST)

A peer-reviewed article of this Preprint also exists.

Rovetto, C.; Cruz, E.; Nuñez, I.; Santana, K.; Smolarz, A.; Rangel, J.; Cano, E.E. Minimizing Intersection Waiting Time: Proposal of a Queue Network Model Using Kendall’s Notation in Panama City. Appl. Sci. 2023, 13, 10030. Rovetto, C.; Cruz, E.; Nuñez, I.; Santana, K.; Smolarz, A.; Rangel, J.; Cano, E.E. Minimizing Intersection Waiting Time: Proposal of a Queue Network Model Using Kendall’s Notation in Panama City. Appl. Sci. 2023, 13, 10030.

Abstract

Intersections within urban centers do not allow all citizens to move in a fluid manner. In this sense, this paper proposes a queuing network model based on Kendall's notation for the intersection of two urban streets (East 53rd Street and East 56th Street) in Panama City. A set of traffic lights operating under a fixed time scheme controls the vehicular flow at the intersection. The objective is to optimize the vehicular flow at the intersection by minimizing the waiting time of the vehicles using mathematical models, Linear Regressor Model, and simulations performed in MATLAB evaluating the waiting time experienced by the vehicles. Based on the results obtained, the optimal signal timing of the traffic lights is determined to minimize the waiting time for both streets.

Keywords

Vehicular traffic flow; queuing theory; optimal traffic light control; optimization; simulation; simulation

Subject

Computer Science and Mathematics, Artificial Intelligence and Machine Learning

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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