The accelerating emergence of vehicle automation and the anticipation of the advent of shared mobility through fully autonomous vehicles indicate the beginning of a new era of mobility which has the potential to reshape the future of transport in urban areas. In light of such developments, it is important that communities prepare to adapt to the changes they might entail. Therefore, in this paper, traffic flow theory, simulation-based dynamic traffic assignment, and a computer experiment using PTV Visum software were employed to study the impact of different market penetration rates of shared autonomous vehicles (SAVs) on a city-size traffic system. The city of Budapest during morning peak period was chosen as a case study, and a simulation model was created by incorporating SAV elements and their interrelationships into the existing traffic model of the case study city; three alternative future penetration rates were examined in relation to five key performance indicators (KPIs). The simulation results indicated that the implementation of the SAV system has a positive effect on traffic performance. Based on the relationships between the modeled SAV demand shares and the network’s KPIs in the designed scenarios, the overall network performance showed improvement along with an increase in the SAV demand share.
Autonomous Vehicles (AVs) are anticipated to bring forth a multitude of advantages for upcoming mobility.These potential benefits and many others vary substantially by the market share of AVs. There are several articles that investigated AV market share with a variety of methods, however, they show a huge variation depending on the market specifications. The aim of this research is to calculate private AV adoption rates over time depending on the Hungarian automobile market characteristics. The research empirically estimates, using the Gompertz function, the projected growth rates of private autonomous passenger vehicles in Hungary using historical patterns of human-driven vehicle ownership data on the basis of projected per capita GDP.The study's findings suggest that, in an optimistic and moderate scenario, the Hungarian car market is projected to become saturated due to AVs by 2067 and 2076, respectively. However, a pessimistic estimation indicates that saturation is unlikely to occur before 2100. This study’s contribution to the literature is through a mathematical approach that predicts AVs market penetration rate and saturation year, in which the assumptions and the used parameters of the model can be modified depending on different case studies, or they can be updated due to the advancement in technology and improvement in knowledge of the studied market.
Traffic and transport researchers, policymakers, and vehicle manufacturers are interested in investigating the implications and the influence of autonomous vehicles (AV) because a gradual deployment of such new technologies is expected to take place in the future. This research investigates the impacts of the AVs emergence on traffic performance for the city of Budapest in three future traffic scenarios with different AV market replacement rates for the year 2030. The network was modeled using simulation-based dynamic traffic assignment in PTV Visum software. Four traffic performance parameters were analyzed to explore the impacts of AV's emergence on the network. The results showed noticeable improvements among the four investigated traffic performance parameters.
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