Understanding driverless car adoption: Random parameters ordered probit model for Brisbane, Melbourne and Sydney

With advanced policy and technology support, driverless cars are expected to be a reality on Australian roads in next 5-10 years. The pace at which driverless cars emerge as a mainstream travel mode greatly depends on public adoption and acceptance; this is likely to be based on multiple factors. The impact these factors may have on various adoption time horizons, however, is rarely discussed in contemporary research. Therefore, this study focuses on illustrating the impact of factors associated with the adoption of driverless cars in Australia. A survey was conducted on 2608 participants living in metropolitan Brisbane, Melbourne, and Sydney. A total of 1108 participants expressed their preference towards driverless car adoption over three different time intervals, ranging from now to 10 years following deployment. Four random parameters ordered probit models were developed using the survey data-three separate models for Brisbane, Melbourne, and Sydney, and one for the combined dataset. Significance differences among models were evaluated using the likelihood ratio test. The results showed a significant difference among cities in terms of contributing factors towards driverless car adoption timeline. Additionally, different groups, considering the following factors-gender, age, household members, level of education, employment status, income, driving licence duration, travel distance to school, travel distance for social outings, car ownership, familiarity with driving aids and driverless car rid-ing-exhibited a mixed interest regarding the adoption timeline for driverless cars. Other groups, considering the following factors exhibited a unidirectional interest-age, level of education, workplace type, income, employment status, travel distance to work, travel distance to school, travel distance for social outings, number of employed in a household, occupation, driver's licence age, number of smart tech use, driverless car trip purpose, feature preference in a driverless car, and use of driving aids. The study offers insights for future planning and policy direction related to driverless car adoption.