Modeling and Simulation of Shared Electric Automated and Connected Mobility Systems with Autonomous Repositioning: Performance Evaluation and Deployment

Taha Benarbia, Kyandoghere Kyamakya (), Fadi Al Machot and Witesyavwirwa Vianney Kambale
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Taha Benarbia: Industrial Engineering Department, Institute of Maintenance and Industrial Security, University of Oran 2, Oran 31000, Algeria
Kyandoghere Kyamakya: Institute for Smart Systems Technologies, Universitaet Klagenfurt, Universitaetsstrasse 65, 9020 Klagenfurt, Austria
Fadi Al Machot: Faculty of Science and Technology, Norwegian University of Life Sciences (NMBU), 1430 Ås, Norway
Witesyavwirwa Vianney Kambale: Institute for Smart Systems Technologies, Universitaet Klagenfurt, Universitaetsstrasse 65, 9020 Klagenfurt, Austria

Sustainability, 2023, vol. 15, issue 1, 1-23

Abstract: The boom seen in artificial intelligence in recent years has led to a revolution in the automotive industry. Numerous automakers around the world, such as Tesla, Toyota, Honda, and BMW, have achieved giant strides in the development of e-autonomous vehicles. Consequently, shared electric automated vehicle mobility (SEAVM) systems, which are a crucial part of future innovative transportation solutions, have attracted significant attention from the research community, particularly from a design perspective. However, the flexibility of shared automated mobility systems may lead to a self-operating technology issue (unequal distribution of vehicles), since users in these systems can pick up and drop off electric vehicles wherever they like. With this in mind, this paper addressed the issues of autonomous repositioning and the assignment of shared autonomous electric vehicle systems to balance a system’s network and fulfill its demand. Modeling, analysis and assessment of the system’s performance were carried out using stochastic Petri nets formalism, which included determining the average time areas were empty/congested and the number of unserved consumers, and estimating the redistribution service launch moment. Furthermore, many simulation scenarios were analyzed, including repositioning and without repositioning scenarios, in order to evaluate the efficiency of the model and to show the potential of using Petri nets as a probabilistic formalism approach for the modeling of e-automated mobility systems.

Keywords: automated shared mobility; shared electric autonomous vehicle; stochastic Petri nets; discrete event system; automated vehicles redistribution; autonomous vehicle assignment (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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