Virtual Reality Experiment to Study the Role of Social Conformity in the Acceptance of Autonomous Vehicles: Pedestrian Crossing Data in VR, 2022-2023

Farooq, Bilal and Nazemi, Mohsen and Cherchi, Elisabetta and Yin, Hao (2024). Virtual Reality Experiment to Study the Role of Social Conformity in the Acceptance of Autonomous Vehicles: Pedestrian Crossing Data in VR, 2022-2023. [Data Collection]. Colchester, Essex: UK Data Service. 10.5255/UKDA-SN-857223

Many governments worldwide are introducing new plans to promote and anticipate the recent rapid development of automation. The economic and societal benefits of autonomous vehicles are foreseen to be enormous (up to Euros 17tn to GDP). But, these benefits could be jeopardised if users fail to adopt the technology. In response to this urgent need, the project aims to take advantage of virtual reality technologies to use them in a scientific context to understand and then model users' acceptance of Fully Autonomous Vehicles (FAVs), particularly Fully Automated Taxis (FATs). In order to achieve the research overall aim, the project set the following specific objectives:- Understand to which extent the acceptance of FATs is affected by how much familiar we can get with this highly technological and innovative product and by what other people around us think about and how they behave with respect to FATs;- Develop a new method for studying acceptance of innovative products, which includes a method to collect the information from customers and a method to analyse this data that can be used then to take policy and industrial decisions that affect every day citizens' life;- Test the benefit of the experiment created to be used across the population to help people to live in and adapt to the forthcoming new technological urban environments. This research will add extensive value to the critical discussions about adoption and diffusion of FAVs or FATs and about the policy incentives that should be given to foster the market. The usability of Virtual Reality environment to social contexts will open opportunities for new applications.

Data description (abstract)

The Veronica project data includes two parts: taxi passenger choice data and pedestrian crossing data. This part primarily involves pedestrian crossing data. The key motivation for the study is to measure the pedestrain crossing behaviours in the mixed traffic of autonomous vehicles (AVs) and normal vehicles. This study uses virtual reality (VR) to simulate two urban mid-block environments, one in downtown Toronto, Canada and the other in central Newcastle, UK, to investigate the crossing behaviour of 428 participants (9,262 observations). The research questions addressed in this paper, in the context of unmarked mid-block crossing, are: (a) Do various vehicle types, i.e., normal vehicles and AVs, impact pedestrian behaviour? (b) How do other pedestrians influence one’s crossing behaviour? (c) How do traffic characteristics, road type, and environmental characteristics impact pedestrian behaviour? (d) What is the influence of demographics on pedestrian behaviour? and, Are there differences in pedestrian behaviour in different countries?

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