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Policy Implications of Autonomous Vehicles

Van Wee, Bert and Milakis, Dimitrios and Thomopoulos, Nikolas, eds. (2020) Policy Implications of Autonomous Vehicles. Advances in Transport Policy and Planning, 5. Academic Press (Elsevier). doi: 10.1016/bs.atpp.2020.06.001. ISBN 978 012820191 6. ISSN 2543-0009.

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Autonomous vehicles (AVs) constitute a contemporary key area of research and development as reflected by the significant funds currently invested globally. According to the SAE (Society of Automotive Engineers) International taxonomy, in the highest levels of vehicle automation, an automated driving system is expected to perform all dynamic tasks of driving in certain (SAE level 4) or in all conditions (SAE level 5) (SAE International, 2018). In the lower levels of vehicle automation, a human should be available to take control of the vehicle (SAE level 3) or to monitor the driving environment while one is assisted to perform the lateral or/and longitudinal motion control of the vehicle (SAE levels 1 and 2). Yet, even these standards are being revised and updated to reflect the continuous need for shared learning and adaptation based on AV trials, such as SAE-J3018™ which was originally established in 2015 and updated in late 2019 (SAE International, 2019). Large automotive companies have been envisaging vehicle automation technology for passenger transport to be available shortly after 2020, although they have indeed revised their early optimistic predictions about having fully automated vehicles on public roads by 2020 (Walker, 2020) and are currently exploring viable business models. Moreover, the COVID-19 pandemic seem to have accelerated development and use of certain forms of vehicle automation for supporting front-line health care (e.g., by delivering medical supplies to hospitals or elderly groups) and controlling the spread of the corona virus (e.g., by disinfecting public spaces), while the discussion about a significant modal shift from airplanes (i.e., short to mid-range trips) to automated vehicles has recently intensified (Rice, 2020). In this context, research focus has been, so far, predominantly on the development of the hardware (e.g., sensors) and software (e.g., path planning algorithms) technology associated with different levels of vehicle automation (Gandia et al., 2019), particularly since it has been established that the role of hardware has been declining in contrast to the role of software within the transport sector (Thomopoulos et al., 2015). Moreover, the perception that AVs will bring mainly a change to vehicle performance led researchers to explore primarily the short-term implications for traffic flow, road safety and fuel efficiency (Milakis et al., 2017). More recently, “softer” implications of AVs for travel behavior, accessibility, culture, digital divide, health, land use, and social equity have attracted the attention of the research community, acknowledging the possibility of longer term unanticipated (Mladenović, 2019) socio-technical changes because of this emerging mobility technology (Cohn et al., 2019; Curl and Fitt, 2019; Gelauff et al., 2019; Milakis, 2019; Milakis et al., 2018; Milakis and van Wee, 2019; Soteropoulos et al., 2019; Thomopoulos and Givoni, 2015; Whittle et al., 2019; Zhang and Guhathakurta, 2018). Several scholars argue for more active governance of smart mobility ensuring and enhancing public value (i.e., maximizing individual benefits such as access to opportunities, while ensuring inclusive distribution of such benefits and minimizing adverse impacts to the environment and public health) (Docherty et al., 2018; Lyons, 2018; Pangbourne et al., 2020). Research results in all fields indicate that both short- and long-term implications of AVs are expected to be significant, including possible adverse effects for social and environmental sustainability. Moreover, such implications could vary substantially among different countries because of differences in urban form and size of cities, transport networks, travel patterns, governance structures but also due to socio-demographic, cultural and climate factors (Rode et al., 2017). Despite this rather clear indication and the associated high public interest, policy developments in terms of type, extent, combination and timing of policy responses in this field are still at an early stage (Cohen and Cavoli, 2019; Fraedrich et al., 2018; Milakis, 2019). This might reflect the adoption of a technology driven deployment path for AVs associated with deep uncertainty about possible implications, leaving no or limited space for policy intervention (Taeihagh and Lim, 2019) that could steer deployment of AVs toward desirable, acceptable and sustainable transition as highlighted by WISE-ACTa outputs. Consequently, planners tend to adopt a reactionary “watch and wait” approach regarding AVs integration that could risk social and environmental sustainability (Legacy et al., 2019). According to Stayton and Stilgoe (2020), even the widely used SAE International taxonomy of AV levels (SAE International, 2018) reflects a technologically-centered approach describing the extent that an autonomous driving system can replace a human task. These researchers suggest that for policymakers and the public the technical capabilities of automated vehicles are not so important themselves, as the policies needed so that such vehicles offer safer, more equitable and effective transport system. This book volume systematically reviews policy relevant implications of AVs and the associated possible policy responses. It comprises 13 chapters discussing: (a) short-term implications of AVs for traffic flow (Chapter 1), human-automated bus systems interaction (Chapter 2), cyber-security and safety (Chapter 3), cyber-security certification and auditing (Chapter 4), non-commuting journeys (Chapter 5); (b) long-term implications of AVs for carbon dioxide (CO2) emissions and energy (Chapter 6), health and well-being (Chapter 7), data protection (Chapter 8), ethics (Chapter 9), governance (Chapter 10); (c) implications of AVs for the maritime industry (Chapter 11) and urban deliveries (Chapter 12), and (d) overall synthesis and conclusions (Chapter 13). The book has been initiated within the Action CA16222 of the European Cooperation in Science and Technology (COST) entitled “Wider Impacts and Scenario Evaluation of Autonomous and Connected Transport” (WISE-ACTa). WISE-ACT has offered a unique platform for knowledge exchange and collaboration among multiple researchers from different countries with diverse backgrounds and expertise to explore relevant policy implications of AVs and identify required policy developments at global level. In the following section, we present an overview of the 13 book chapters included in this book volume, starting with the short-term implications of AVs (Section 2.1), followed by the long-term implications of AVs (Section 2.2), the implications of AVs for the maritime and freight industry (Section 2.3) and the overall synthesis and conclusions (Section 2.4).

Item URL in elib:https://elib.dlr.de/135861/
Document Type:Book
Title:Policy Implications of Autonomous Vehicles
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In ISI Web of Science:No
EditorsEmailEditor's ORCID iDORCID Put Code
Van Wee, BertDelft University of Technology, The NetherlandsUNSPECIFIEDUNSPECIFIED
Milakis, DimitriosUNSPECIFIEDhttps://orcid.org/0000-0001-5220-4206UNSPECIFIED
Thomopoulos, NikolasUniversity of Surrey, United KingdomUNSPECIFIEDUNSPECIFIED
Publisher:Academic Press (Elsevier)
Series Name:Advances in Transport Policy and Planning
ISBN:978 012820191 6
Keywords:Autonomous vehicles; Policy implications
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Transport System
DLR - Research area:Transport
DLR - Program:V VS - Verkehrssystem
DLR - Research theme (Project):V - UrMo Digital (old)
Location: Berlin-Adlershof
Institutes and Institutions:Institute of Transport Research > Mobility and Urban Development
Deposited By: Milakis, Dr. -Ing. Dimitrios
Deposited On:28 Oct 2020 23:25
Last Modified:02 Feb 2024 08:50

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