Evaluating the Impacts of Autonomous Vehicles’ Market Penetration on a Complex Urban Freeway during Autonomous Vehicles’ Transition Period

Mohammad A. R. Abdeen (), Ansar Yasar, Mohamed Benaida, Tarek Sheltami, Dimitrios Zavantis and Youssef El-Hansali
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Mohammad A. R. Abdeen: Department of Computers and Information Systems, The Islamic University of Madinah, Medina 42351, Saudi Arabia
Ansar Yasar: Transportation Research Institute (IMOB), Hasselt University, 3500 Hasselt, Belgium
Mohamed Benaida: Department of Computers and Information Systems, The Islamic University of Madinah, Medina 42351, Saudi Arabia
Tarek Sheltami: Computer Engineering Department, Interdisciplinary Research Center of Smart Mobility and Logistics, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia
Dimitrios Zavantis: Transportation Research Institute (IMOB), Hasselt University, 3500 Hasselt, Belgium
Youssef El-Hansali: Transportation Research Institute (IMOB), Hasselt University, 3500 Hasselt, Belgium

Sustainability, 2022, vol. 14, issue 16, 1-12

Abstract: Autonomous vehicles (AVs) have been a rapidly emerging phenomenon in recent years, with some automated features already available in vehicles. AVs are expected to potentially revolutionize the existing inefficient state of urban transportation and be a step closer to environmental sustainability. This study focuses on simulation modeling in assessing the potential effects of autonomous vehicles (AVs) and on mobility and safety by developing a framework model based on traffic microsimulation for a real network located in Al-Madinah, Saudi Arabia. The market penetration rates (MPRs) will not reach 100% in the near future; instead, penetration will progressively increase. As a result, in our study, we investigated the potential effect of AV technology in five different AV market penetration rates: 0% (baseline), 25%, 50%, 75%, and 100%. The results suggest that Avs significantly improve the network’s safety and operational performance at high penetration rates. Specifically, estimated vehicle delays decreased by 26%, 34.4%, 63.7%, and 74.2% for 25%, 50%, 75%, and 100% AV penetration rates, respectively. Finally, we think this study will help decisionmakers over in the long-term in their attempts to achieve sustainable development through the optimal integration of innovative and novel technologies.

Keywords: traffic microsimulation; road safety; Vissim; driving behaviors (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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