Modelling the adoption and deployment of automated vehicles
Creators: name: Chen, Yilun
Publisher: name: RMIT University
Year: 2024
Subjects: classificationCode: 400512
subject: Transport engineering

description: Automated vehicles (AVs) are positioned to revolutionise the way we travel, offering significant benefits such as increased safety, easy accessibility, reduced congestion and lower emissions. Therefore, AVs have attracted significant attention from researchers, policymakers and industry leaders. However, the deployment and adoption of AVs is a complex process that depends on various factors, including technological readiness, public perception and modelling frameworks. To fully realise the benefits of AVs, it is important to understand these factors and how they interact. This thesis aimed to provide insights into the adoption and deployment of AVs by investigating and modelling the factors that influence these processes. By employing a multidisciplinary approach incorporating insights from engineering, psychology, transport modelling and public policy, this thesis aimed to provide a comprehensive understanding of the challenges and opportunities associated with AVs to inform the development of effective policies and strategies for their adoption and deployment.

First, the study presented a comprehensive literature review of the factors affecting the adoption of AVs. With 90 per cent of accidents stemming from human error, AVs have great potential to significantly reduce human-made road accidents. However, understanding the public’s attitude towards AV adoption is crucial for developing appropriate policies and strategies to leverage the potential benefits of this disruptive technology. Despite previous research into AV adoption attitudes, there is a lack of a systematic and comprehensive literature review that considers various interlinked factors, such as road traffic environment changes, psychological factors, AV transition and policy influences. This study aimed to fill this gap by synthesising past research into driverless technology and uncertainty, road traffic environment changes, policy influences and findings from AV adoption modelling approaches to understand public attitudes towards AVs. The study highlights critical issues and future research directions, such as the uncertainty of AV adoption experiments, policy implementation, infrastructure readiness and demand modelling. By analysing and synthesising existing research, this study provides insights into the factors influencing public acceptance of Avs. In addition, it identifies gaps in current knowledge that can inform future research and policy development by leveraging AV benefits.

Second, the study addressed the lack of systematic investigation into the factors that affect the public acceptance of fully AVs, particularly in the Australian context. Previous research suggests that public attitudes towards and the adoption of AVs may differ between countries. Therefore, this study aimed to systematically explore the factors influencing public opinion towards fully AVs by conducting a national survey in Australia. The study focused on seven key attributes—benefits/usefulness, ease of use, attitude, data privacy, willingness to pay more, social influence and trust—and their association with demographic and travel behaviour. Results from 809 Australian responses revealed a generally positive attitude towards AVs, with age and years of driving experience being the two most important factors influencing acceptance, rather than travel characteristics. Less exposure to automation technology is a significant barrier to adoption for age and driving experience. Males also hold a more favourable attitude towards AVs than females, and Australians are less willing to pay more for fully AVs than conventional vehicles. Data privacy concerns are also a significant factor for Australian people. The study’s theoretical and practical implications are discussed in detail, providing valuable insights into the acceptance of fully AVs in Australia.

Third, the study aimed to assess the behavioural intention to use fully AVs in Australia by extending the technology acceptance model, including data privacy and trust of its constructs. Previous studies have used user acceptance models to explore the public acceptance of AVs in different countries. However, other important factors such as trust and data privacy have not been adequately considered. Based on the survey of 809 adult respondents from Australia, this research revealed that perceived trust and data privacy are the two most important variables affecting attitude towards fully AVs, followed by perceived ease of use and usefulness. Perceived data privacy was found to positively influence attitude, perceived trust, perceived usefulness, perceived ease of use and behavioural intentions. Perceived trust mediated the perceived data privacy on attitudes in this study. Moreover, the study found that the two major variables in the proposed model, perceived trust and data privacy, significantly affected attitudes towards AVs, with total effects being 0.637 and 0.604, respectively. Attitude was the most significant variable that correlated with behavioural intentions, leading to the acceptance of fully AVs. Additionally, multi-group analysis revealed gender, age and income-related differences regarding public acceptance of AVs.

The findings of this study provide several theoretical and practical implications that can be employed to better understand public attitudes towards fully AVs and to develop effective strategies and policies to promote AV adoption in Australia. The study also highlights the importance of considering trust and data privacy issues to gain a more comprehensive understanding of public acceptance of new technologies.

Moreover, as the transportation system faces significant disruptions, including the emergence of AVs, it is crucial to investigate their potential effects on mode shift among other modes, such as public transport and conventional vehicles. However, limited studies have systematically considered the interlinked factors at the system level. To address this knowledge gap, we proposed a system dynamics approach to investigate the influence of AVs on mode shift between conventional vehicles, AVs and public transport. By systematically considering a range of factors, including road network, vehicle cost, public transport supply, congestion level and word-of-mouth effects, the proposed system dynamics model simulated the interactions among these modes of transportation in the transportation system in the longer term using time series.

The proposed system dynamics model was applied to Melbourne’s transport network in a case study. Inputs such as current traffic, road capacity, public perception and AV technological advancement were used to assess the effects of different policy options on the transport systems. The data source was the Victorian integrated transport model provided by the Department of Transport and Planning, Melbourne, Australia, supplemented by data from the existing literature and assumptions. The findings suggest that AVs will gradually replace conventional vehicles as another primary mode of transportation. However, public transport will still play a significant role in the transportation system, accounting for 50 per cent of total trips by person after 2058. Cost was the most critical factor affecting AV adoption rates, followed by road network capacity and awareness programs.
This study identifies the need for future research to investigate the induced demand for travel due to AV adoption and the application of equilibrium constraints to the traffic assignment model to increase model accuracy. These findings can be helpful for policymakers and stakeholders to make informed decisions regarding AV adoption policies and strategies. Overall, the proposed system dynamics model provides a useful tool to systematically consider the influence of AVs on mode shift and to inform policy decisions for a sustainable transportation system after AVs come to the market.