Exploring the impact of shared autonomous vehicles on urban parking demand: An agent-based simulation approach

Policy and society related implications of automated driving: A review of literature and directions for future research

“…This rate dropped to around nine in a scenario of significantly increased peak hour demand. Also, Zhang, Guhathakurta, Fang, and Zhang (2015) and Boesch, Ciari, and Axhausen (2016) indicated in hypothetical and real city simulations (Zurich, Switzerland) that every shared automated vehicle could replace around ten and fourteen conventional vehicles, respectively. However, according to Chen, Kockelman, and Hanna (2016) if vehicle charging is also taken into account in the case of shared, electric, automated vehicles then the replacement rate of privately owned vehicles drops between 3.7 and 6.8.…”

“…On the other hand, reduced transportation costs because of automated vehicles would cause the city to expand and land rents to decline about 40% outside the city center. Finally, Zhang et al (2015) showed in their agent-based simulation of a hypothetical city that the longer the empty cruising of shared automated vehicles the more evenly distributed the parking demand of these vehicles would be throughout the study area. If no empty cruising is allowed then parking demand of shared automated vehicles tended to be concentrated in the center of the study area.…”

“…Yet, the reduction was only incremental or even non-existent when these researchers tested scenarios with a 50% mix between shared automated and conventional vehicles. Also, Chen, Balieu, and Kringos (2016), Boesch, Ciari, and Axhausen (2016) Kockelman (2014, 2016), Zhang et al (2015) and Spieser et al (2014) offered estimations about a replacement rate of conventional vehicles by shared automated vehicles that varies between three and fourteen. Thus, parking demand could be reduced from about 67% up to over 90%.…”

Comparing Automated Shared Taxis and Conventional Bus Transit for a Small City

“…Many current models of automated taxi systems assume that taxis rebalance to areas of high demand when not in use (Fagnant and Kockelman 2014;Zhang et al 2015a;Spieser et al 2014). This is a likely behavior that reduces average passenger wait times, but at the cost of increasing total system VKT (Zhang et al 2015a).…”

“…This is a likely behavior that reduces average passenger wait times, but at the cost of increasing total system VKT (Zhang et al 2015a). Since the focus of this study was on the environmental performance of such automated taxi systems relative to the current bus system, no vehicle repositioning was included in the model.…”