Advancements, prospects, and impacts of automated driving systems
01 Sep 2017-International journal of transportation science and technology (Elsevier)-Vol. 6, Iss: 3, pp 208-216
TL;DR: A review of the state-of-the-art in the field of ADS and their deployment paths is reviewed and two specific use cases of ADS where the impacts can be significant are identified – personal mobility services and vehicle automation for aging society.
Abstract: Over the last decade, significant progress has been made in automated driving systems (ADS). Given the current momentum and progress, ADS can be expected to continue to advance and a variety of ADS products will become commercially available within a decade. It is envisioned that automated driving technology will lead to a paradigm shift in transportation systems in terms of user experience, mode choices, and business models. In this paper, we start with a review of the state-of-the-art in the field of ADS and their deployment paths. It is followed by a discussion of the future prospects of ADS and their effects on various aspects of the transportation field. We then identify two specific use cases of ADS where the impacts can be significant – personal mobility services and vehicle automation for aging society. A survey of impact assessment studies and the associated methodologies for evaluating ADS is given, which is followed by concluding remarks at the end of the paper.
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TL;DR: Four theory-grounded measurement models are intended for application in research aimed at understanding and predicting AV interest and adoption intentions, and user adoption decisions regarding three different AV modes: ownership, sharing and public transport.
Abstract: Autonomous Vehicles (AVs) have the potential to make motorized transport safer and more sustainable, by integrating clean technologies and supporting flexible shared-mobility services. Leveraging this new form of transport to transform mobility in cities will depend fundamentally on public acceptance of AVs, and the ways in which individuals choose to use them, to meet their daily travel needs. Empirical studies exploring public attitudes towards automated driving technologies and interest in AVs have emerged in the last few years. However, within this strand of research there is a paucity of theory-driven and behaviourally consistent methodologies to unpack the determinants of user adoption decisions with respect to AVs. In this paper, we seek to fill this gap, by advancing and testing four conceptual frameworks which could be deployed to capture the range of possible behavioural influences on individuals’ AV adoption decisions. The frameworks integrate socio-demographic variables and relevant latent behavioural factors, including perceived benefits and perceived ease of use of AVs, public fears and anxieties regarding AVs, subjective norm, perceived behavioural control, and attitudinal factors covering the environment, technology, collaborative consumption, public transit and car ownership. We demonstrate the utility and validity of the frameworks, by translating the latent variables into indicator items in a structured questionnaire, and administering it online to a random sample of adult individuals (n = 507). Using the survey data in confirmatory factor analyses, we specify and demonstrate scale reliability of indicator items, and convergent and discriminant validity of relationships among latent variables. Ultimately, we advance four measurement models. These theory-grounded measurement models are intended for application in research aimed at understanding and predicting (a) AV interest and adoption intentions, and (b) user adoption decisions regarding three different AV modes: ownership, sharing and public transport.
164 citations
Cites background from "Advancements, prospects, and impact..."
...…shared-mobility schemes, AVs could also meet the travel needs of users, whilst contributing to the reduction of the negative travel-induced impacts on land use, energy use, traffic, biodiversity and public health (Chan, 2017; Sivak and Schoettle, 2015; Zhang et al., 2017; Crayton et al., 2017)....
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Abstract: Multirotor drones are considered a new and innovative technology. Therefore, many fields are showing increasing interest in utilizing multirotor drones, such as mapping in mining and surveillance i...
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TL;DR: In this article, the authors discuss the role of the government in the development of automated vehicles (AVs) and how this potentially transformative technology should be handled in the public domain.
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Cites background from "Advancements, prospects, and impact..."
...The technological transition towards vehicle automation is making rapid progress in numerous high-income countries (Chan, 2017)....
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TL;DR: In this paper, the authors provide some suggestions for these technologies that are currently emerging, such as Connected and Automated Vehicles (CAVs), which will provide a safe travel mode by eliminating the human driving error.
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TL;DR: This discussion is aimed at providing, in a comprehensive manner, how 5G technology will impact on smart cities, intelligent transportation systems –including autonomous or semi-autonomous vehicles– and vehicular communications, its technical, economic and legal challenges, in the following years.
Abstract: The new mobile technology, 5G, challenges the current scenario in communications by overcoming the flaws of currently working 4G. Such new technology offers to smart cities and intelligent transportation systems a new way to become fully integrated by allowing massive simultaneous connections and ubiquity of network, even under high mobility situations or dense populated areas. In this way, 5G will become a key enabler for real Internet of Things and its corresponding Internet of Vehicles. This discussion is aimed at providing, in a comprehensive manner, how 5G technology will impact on smart cities, intelligent transportation systems –including autonomous or semi-autonomous vehicles– and vehicular communications, its technical, economic and legal challenges, in the following years.
79 citations
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TL;DR: In this article, the authors explore the impacts that autonomous vehicles are likely to have on travel demands and transportation planning and explore how they will affect planning decisions such as optimal road, parking and public transit supply.
Abstract: This paper explores the impacts that autonomous (also called self-driving, driverless or robotic) vehicles are likely to have on travel demands and transportation planning. It discusses autonomous vehicle benefits and costs, predicts their likely development and implementation based on experience with previous vehicle technologies, and explores how they will affect planning decisions such as optimal road, parking and public transit supply. The analysis indicates that some benefits, such as independent mobility for affluent non-drivers, may begin in the 2020s or 2030s, but most impacts, including reduced traffic and parking congestion (and therefore road and parking facility supply requirements), independent mobility for low-income people (and therefore reduced need to subsidize transit), increased safety, energy conservation and pollution reductions, will only be significant when autonomous vehicles become common and affordable, probably in the 2040s to 2060s, and some benefits may require prohibiting human-driven vehicles on certain roadways, which could take longer.
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TL;DR: The National Motor Vehicle Crash Causation Survey (NMVCCS) as discussed by the authors collected on-scene information about the events and associated factors leading up to crashes involving light vehicles.
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TL;DR: In this article, the authors discuss issues related to road safety with self-driving vehicles, and support that the expectation of zero fatalities with selfdriving vehicles is not realistic and it is not a foregone conclusion that a selfdriving vehicle would ever perform more safely than an experienced, middle-aged driver.
Abstract: Self-driving vehicles are expected to improve road safety, improve the mobility of those who currently cannot use conventional vehicles, and reduce emissions. In this white paper the authors discuss issues related to road safety with self-driving vehicles. Safety is addressed from the following four perspectives: (1) Can self-driving vehicles compensate for contributions to crash causation by other traffic participants, as well as vehicular, roadway, and environmental factors? (2) Can all relevant inputs for computational decisions be supplied to a self-driving vehicle? (3) Can computational speed, constant vigilance, and lack of distractibility of self-driving vehicles make predictive knowledge of an experienced driver irrelevant? (4) How would road safety be influenced during the expected long transition period during which conventional and self-driving vehicles would need to interact on the road? The presented arguments support the following conclusions: (1) The expectation of zero fatalities with self-driving vehicles is not realistic. (2) It is not a foregone conclusion that a self-driving vehicle would ever perform more safely than an experienced, middle-aged driver. (3) During the transition period when conventional and self-driving vehicles would share the road, safety might actually worsen, at least for the conventional vehicles.
72 citations
01 Jan 2014
61 citations