Advancement in automated driving technology has created opportunities for smart urban mobility. Automated vehicles are now a popular topic with the rise of the smart city agenda. However, legislators, urban administrators, policymakers, and planners are unprepared to deal with the possible disruption of autonomous vehicles, which potentially could replace conventional transport. There is a lack of knowledge on how the new capabilities will disrupt and which policy strategies are needed to address such disruption. This paper aims to determine where we are, where we are headed, what the likely impacts of a wider uptake could be, and what needs to be done to generate desired smart urban mobility outcomes. The methodology includes a systematic review of the existing evidence base to understand capability, impact, planning, and policy issues associated with autonomous vehicles. The review reveals the trajectories of technological development, disruptive effects caused by such development, strategies to address the disruptions, and possible gaps in the literature. The paper develops a framework outlining the inter-links among driving forces, uptake factors, impacts and possible interventions. It concludes by advocating the necessity of preparing our cities for autonomous vehicles, although a wider uptake may take quite some time.

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Understanding autonomous vehicles: A systematic literature review on capability, impact, planning and policy

What drives the acceptance of autonomous driving? An investigation of acceptance factors from an end-user's perspective

Autonomous vehicles are one of the most spectacular recent developments of Artificial Intelligence. Among the problems that still need to be solved before they can fully autonomously participate in traffic is the one of making their behaviour conform to the traffic laws. This paper discusses this problem by way of a case study of Dutch traffic law. First it is discussed to what extent Dutch traffic law exhibits features that are traditionally said to pose challenges for AI & Law models, such as exceptions, rule conflicts, open texture and vagueness, rule change, and the need for commonsense knowledge. Then three approaches to the design of law-conforming AV are evaluated in light of the challenges posed by Dutch traffic law, which includes an assessment of the usefulness of AI & Law models of nonmonotonic reasoning, argumentation and case-based reasoning.

/pdf/on-the-problem-of-making-autonomous-vehicles-conform-to-ysk9hx8yw8.pdf

On the problem of making autonomous vehicles conform to traffic law

This study conducted an experiment to test how the level of blame differs between an artificial intelligence (AI) and a human driver based on attribution theory and computers are social actors (CAS

Why Is Artificial Intelligence Blamed More? Analysis of Faulting Artificial Intelligence for Self-Driving Car Accidents in Experimental Settings

Autonomous vehicles (AV) have become a symbol of futuristic and intelligent transport innovation This new driving technology has received heightened attention from academic, public, and private sectors Nonetheless, a big challenge limiting a clear understanding of AV research is its scale A large volume of literature is produced—covering various fields This paper aims to map out the research on AV for a better understanding of the trends, patterns, and interconnections, and it critically reflects on their implications for research A scientometric analysis technique is applied to analyze 4,645 papers published between 1998 and 2017 The findings disclose that (a) 877 percent of the AV studies was conducted by educational institutes; (b) Europe is the most productive continent in AV research with a 359 percent share of publications; (c) North America is the most influential continent in AV research, receiving 411 percent of the citations; (d) Over 50 percent of the studies were conducted during the last three years of the analysis period; (e) Urban and social contexts of AV research are still at their early stage; and (f) Relatively limited collaboration and knowledge sharing between academia and industry exist

Nynke Vellinga Vellinga

Papers

From the testing to the deployment of self-driving cars: Legal challenges to policymakers on the road ahead