Long-term implications of automated vehicles: an introduction

About a century ago, private vehicles started being massively introduced into western societies. Several decades later preventing and/or mitigating adverse effects of this mobility technology became of critical importance for urban and transport policy. Automated driving technology is likely to bring substantial changes in future urban mobility. This Special Issue focuses on the possible long-term implications of automated vehicles (AVs). Automated driving technology involves hardware (e.g. sensors) and software (e.g. trajectory planning) systems that can assist the driver to conduct the dynamic tasks of driving (e.g. monitor the driving environment, lateral and/or longitudinal motion control). In the lower levels of vehicle automation, the driver monitors the driving environment and s/he is assisted to perform the lateral or longitudinal motion control (Society of Automotive Engineers (SAE) level 1) or both motion controls (SAE level 2). In SAE level 3, an automated driving system performs all dynamic tasks of driving but the driver should be ready to take control of the vehicle. In the highest levels of vehicle automation, an automated driving system performs all dynamic tasks of driving in certain (e.g. in highways; SAE level 4) or in all conditions (SAE level 5) either occupied or unoccupied (SAE International, 2016). The driver is not expected to be available to take control of the vehicle in SAE levels 4 and 5. Automated driving technology is still in its infancy, although early studies on development of such systems are dated back in late 50’s. Thus far, research efforts have mainly focused on the technological aspects of vehicle automation (e.g. road environment perception and motion planning). Impacts of automated driving systems on driver, traffic flow characteristics, and fuel efficiency have also been extensively studied especially during the last two decades (Milakis et al., 2017). The interest on wider social, economic and environmental implications of automated driving is growing as this technology becomes available. This interest reflects concerns that an unconditional, technology-driven introduction of AVs could be in conflict with social and environmental sustainability objectives, ignoring the fact that the transport system is a complex socio-technical system which calls for joint optimization of both the technical and societal sub-systems (e.g. Currie, 2018; Docherty et al., 2017; Lyons, 2016; Pangbourne et al., 2018; Thomopoulos and Givoni, 2015). For instance, automated driving could reduce travel cost, enhance accessibility and therefore induce new suburban development (e.g. Milakis et al., 2018; Zhang and Guhathakurta, 2018). Changes in land use and location choices, possible modal shift from public transport to AVs and travel of user groups that currently facing mobility restrictions could induce additional travel demand with significant energy and environmental implications (e.g. Rodier et al., 2018; Wadud et al., 2016). On the other hand, road capacity enhancement as well as replacement of part of the fleet by shared AVs (e.g. Boesch et al., 2016) might reduce future needs for new roads. Long-term implications for public health and social equity could also be important. Possible adverse long-term implications of AVs raise questions about the type, extent, combination and timing of policy responses as well as about the role of urban and transport planners in informing policy responses to this new mobility technology. This Special Issue brings together eight review and discussion papers that cover a wide-array of long-term implications of AVs as well as governance responses to inform deployment of AVs. The first introductory paper provides an in-depth scientometric-bibliometric review of the field. The next three papers focus on long-term travel behaviour and spatial implications of AVs. Subsequently, three papers discuss the planning implications and governance of AV deployment. The last paper explores the potential and long-term implications of automation in the shipping industry. In the next section, a brief overview of the papers is presented followed by the conclusions of this Special Issue