Urban Traffic Signal Control under Mixed Traffic Flows: Literature Review

Author:

Majstorović Željko1ORCID,Tišljarić Leo12ORCID,Ivanjko Edouard1ORCID,Carić Tonči1ORCID

Affiliation:

1. Faculty of Transport and Traffic Sciences, University of Zagreb, 10000 Zagreb, Croatia

2. INTIS d.o.o., Bani 73a, Buzin, 10000 Zagreb, Croatia

Abstract

Mixed traffic flows are opening up new areas for research and are seen as key drivers in the field of data and services that will make roads safer and more environmentally friendly. Understanding the effects of Connected Vehicles (CVs) and Connected Autonomous Vehicles (CAVs), as one of the vehicle components of mixed traffic flows, will make it easier to avoid traffic congestion and contribute to the creation of innovative applications and solutions. It is notable that the literature related to the analysis of the impact of mixed traffic flows on traffic signal control in urban areas rarely considers mixed traffic flow containing CVs, CAVs, and Human Driven Vehicles (HDVs). Therefore, this paper provides an overview of the relevant research papers covering the topic of urban Traffic Signal Control (TSC) and mixed traffic flows. Best practices for intersection state estimation and TSC in the case of mixed traffic flows in an urban environment are summarized and possible approaches for utilizing CVs and CAVs as mobile sensors and actuators are discussed.

Funder

Croatian Science Foundation

Science Foundation of the Faculty of Transport and Traffic Sciences

European Regional Development Fund

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

Reference72 articles.

1. Empirical Assessment of Urban Traffic Congestion;Chow;J. Adv. Transp.,2014

2. Causes of traffic congestion in urban areas. Case of Poland;Wach;SHS Web Conf.,2018

3. Centre for Economics and Business Research (2022, August 11). The Future Economic and Environmental Costs of Gridlock in 2030. Available online: https://www.ibtta.org/sites/default/files/documents/MAF/Costs-of-Congestion-INRIX-Cebr-Report%20(3).pdf.

4. Computational Intelligence in Urban Traffic Signal Control: A Survey;Zhao;IEEE Trans. Syst. Man Cybern. Part C (Appl. Rev.),2012

5. Zahid, M., Chen, Y., Jamal, A., and Memon, M.Q. (2020). Short Term Traffic State Prediction via Hyperparameter Optimization Based Classifiers. Sensors, 20.

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