CONNECTED VEHICLES VERSUS CONVENTIONAL TRAFFIC CONGESTION MITIGATION MEASURES: AN OPERATIONAL ECONOMIC ANALYSIS

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Volume 4 (2), December 2021, Pages 155-169

Mutasem Alzoubaidi¹, Adli Al-Balbissi², Abdel Rahman Alzoubaidi³, Amr Alzoubaidi⁴, Baha Azzeh⁵, Ahmed Al-Mansour⁶, Ahmed Farid⁷

¹ University of Wyoming, USA, This email address is being protected from spambots. You need JavaScript enabled to view it. 

² The University of Jordan, Jordan, This email address is being protected from spambots. You need JavaScript enabled to view it.

³ Eastern Washington University, USA, This email address is being protected from spambots. You need JavaScript enabled to view it.

⁴ Al-Sendyan Engineering Office, Jordan, This email address is being protected from spambots. You need JavaScript enabled to view it.

⁵ Omrania & Associates Architecture & Engineering Consultants, Jordan, This email address is being protected from spambots. You need JavaScript enabled to view it.

⁶ The University of Jordan, Jordan, This email address is being protected from spambots. You need JavaScript enabled to view it.

⁷ California Polytechnic State University, USA, This email address is being protected from spambots. You need JavaScript enabled to view it.

Abstract

This paper conducted an operational, economic analysis to assess alternative solutions to traffic congestion. They involved integrating adaptive traffic signal control (ATSC) with connected vehicle technology (ATSC-CV) and the application of various conventional and unconventional solutions. The studied conventional scenarios include signal timing optimization, signal actuation, and upgrading existing intersections to interchanges. There were unconventional scenarios involving converting two intersections to interchanges and the third to a continuous green-T intersection (CGTI). Different unconventional alternatives involved deploying ATSC-CV-based systems assuming varying market penetration rates (MPRs). The operational performance of each alternative was analyzed using VISSIM microsimulation software. To model the driving behavior of CVs, Python programming language was used through the COM interface in VISSIM. One-way analysis of variance (ANOVA) and post-hoc testing results indicate that implementing any suggested alternative would substantially decrease the mean vehicular travel time compared to the fixed signal control strategy currently implemented. Specifically, the ATSC-CV-based systems yielded notable travel time reductions ranging from 9.5% to 21.3%. Also, ANOVA results revealed that the highest benefit-to-cost ratio among all alternatives belonged to scenarios in which the MPRs of CVs were 100%. It was also found that ATSC-CV-based systems with MPRs of 25% and 50% would be as feasible as converting signalized intersections to underpass interchanges.

Keywords:

Connected vehicles, Adaptive traffic signal control, Traffic operations, Benefit-to-Cost ratio, Microsimulation, VISSIM.

DOI: https://doi.org/10.32010/26166127.2021.4.2.155.169

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