Measures of baseline intent to use automated vehicles: A case study of Texas cities

Abstract Early consistent measurement of intent to use automated vehicles will help explore the public’s reactions, improve the knowledge base, and facilitate an understanding of the potential benefits that could be achieved. Adopting a car technology acceptance model (CTAM), online surveys were implemented in several Texas cities including 2016 survey of Dallas, Houston, and Waco, which is an extension of a prior 2015 survey study in Austin. Adding different geographic content provided an opportunity to assess trends and to obtain more robust results and different insights on the consumer acceptance and travel behavior impacts of self-driving vehicles. Following an extensive descriptive analyses, a multivariate model was estimated to examine the factors influencing intent to use in Texas cities. The results show an increase in intent to use from 2015 to 2016. Demographic variables mattered but to lesser extent compared to psychosocial variables of the CTAM, which were highly significant in predicting intent to use. Younger individuals, males and individuals with physical conditions that prohibiting them from driving had a higher likelihood of intent to use. Travel behavior characteristics were also important. For example, individuals owning a vehicle with highly automated features had a higher intention to use. The strongest associations with intent to use were observed for attitudes toward self-driving vehicles, performance expectation, perceived safety, and social influence. In moving forward, it will be important to continue to monitor and track the behavior with diverse populations, and build an evidence-based consensus through continuous measurement on intent to use automated vehicles.