Automated Vehicles: Changes in expert opinions over time

Maarten Kroesen, Dimitris Milakis and Bert van Wee

Transport Policy, 2023, vol. 136, issue C, 1-10

Abstract: Innovations in transportation can contribute to reaching relevant societal objectives (e.g. reduce emissions, congestion levels and/or risks). To determine which innovations to stimulate (and which not) it is important for policy makers to assess their effects on beforehand. Expert judgement is an often-used method for this purpose. Although expert opinions can provide useful input for decision-making, these judgement are potentially subject to change, for example, due to new information becoming available or because the (academic) discussion about the innovation in question takes a new turn. Studies that explicitly study stability and change in expert judgements are rare, but highly relevant to determine the reliability of experts' assessments. To address this gap, this study assesses experts’ judgments at multiple points in time focusing on the effects of a transport innovation with potentially widespread societal implications, namely Automated Vehicles (AVs). To this end a survey was administrated to a group of experts involved in the WISE-ACT project. The results indicate that expert opinions towards this innovation are generally favorable; AVs are believed to reduce congestion delays, greenhouse gas emissions and traffic accidents. Although the consulted experts are generally quite stable in their opinions, they are becoming less optimistic about these positive effects over time. A Q-factor analysis additionally reveals two clusters of experts, one with a positive and one a negative outlook on AVs. The latter group beliefs that AVs will lower the value of travel time, thereby increasing travel demand, and, in turn, emission and congestion levels. Overall, the changing and diverging opinions among experts indicate that the transition to AVs is not necessarily regarded as a desirable one.

Keywords: Automated vehicles; Panel survey; Expert judgement; Q-factor analysis (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (6)

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DOI: 10.1016/j.tranpol.2023.03.005

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