Shared automated vehicles: A statistical analysis of consumer use likelihoods and concerns

Abstract

Shared automated vehicles have the potential to revolutionize future transportation mode choice. Because shared automated vehicles could be a disruptive transportation modal alternative, understanding the factors that may affect the likelihood of using and possible concerns is extremely important. To do so, the current paper uses a survey of American Automobile Association members to ask whether or not survey respondents were willing to use shared automated vehicles if they became available. They were also asked their main concerns associated with this technology (safety, privacy, reliability, travel time or travel cost). Two random parameter logit models were estimated to gain insights into the likely usage/concerns processes. Some of the key variables playing statistically significant roles in the willingness to use of shared automated vehicles were ethnicity, household size, daily travel times, and vehicle crash history. Respondents from one vehicle households, that were in close proximity to grocery stores, and have previously been involved in a vehicle crash, were found to be more willing to use shared automated vehicles. Other variables significant in the analysis were high education indicator and driving alone for commute indicator. With regard to shared automated vehicle concerns, the characteristics of respondents who were more or less likely to be concerned with safety, reliability, privacy, and travel time/travel cost were identified. While the opinions and perceptions towards shared automated vehicles are likely to fluctuate in the coming years as more and more information relating to the potential of such sharing becomes available, the findings provide an important initial assessment before this technology becomes widely available to the public. The more is known about shared automated vehicles and their early adopters, the better and seamless the potential modal transition can be. Learning what groups of people are more or less willing to use this technology will help to improve the overall mobility of all. Combining the significant variables provides a rough profile description of early users of shared automated vehicles and their environment. This helps to prioritize possible investments and allows the policy and auto makers to identify the critical needs of the users. This initial assessment provides the characteristics of early adopters and their travel behavior. The model estimation results clearly show that different socio-demographic groups value different aspects and have different concerns relating to shared automated vehicles.