Public Acceptance of AI Technology in Self-Flying Aircraft

The research article includes a literature dissection on the topics of public acceptance of automated vehicles, including self-driving cars and unmanned aerial vehicles. Information reviewed will be applied to the potential future application of self-flying aircraft. The use of the Technology Acceptance Model is reviewed for application of public acceptance studies. Contributing factors commonly observed include perceived ease of use, perceived usefulness, perceived risk and environmental benefits. Additionally, trust in automated technology for decision-making is reviewed. Research is based on existing studies of public acceptance in similar technologies and is applied to the likely public acceptance of self-flying aircraft

Social Perception of Autonomous Vehicles

The technology of autonomous vehicles is gaining more and more emphasis these days. In the near future the technological developments will make it possible for vehicles to travel on the roads without human intervention. However, downstream users have differing views on this new mode of transport. The aim of our research was to explore the opinions of different social generation groups and traffic groups about fully autonomous self-driving (SAE Level 5). In our research, we conducted an online self-report questionnaire survey. The questionnaire was completed by 223 people. The results were analyzed from several perspectives. The results showed that opinions and expectations in the field of autonomous vehicles differed by generation group, gender and primary mode of transport

Driving the future : using TAM and UTAUT to understand public acceptance of fully autonomous vehicles

The implementation of fully autonomous vehicles (FAVs) has been proposed to yield societal and environmental benefits. However, there are uncertainties regarding the factors influencing the acceptance of FAVs in developing countries which has been understudied. Therefore, this study aims to examine the factors affecting public acceptance of the adoption of FAVs, applying the Technology Acceptance Model (TAM) and Unified Theory and Acceptance Technology (UTAUT) conceptual frameworks. Data was collected through an online survey (n = 593). The results reveal a moderate predictive ability of both TAM and UTAUT in explaining behavior intention to use FAVs. The most significant predictors of FAVs adoption behavior are perceived usefulness and social influence. This study also identified the perceived ease of use, attitude toward behavior, hedonic motivation, performance expectancy, and effort expectancy as significant predictors. Conversely, facilitating condition is found to exert minimal influence on FAVs acceptance. Finally, none of the demographic factors (age, gender, education, occupations, and residencies) serves as a significant moderator in the relationship between the main factors of TAM and UTAUT. Our findings may help researchers and practitioners to enhance the acceptability of FAV adoption

Driver Perceptions of V2V and V2I for Autonomous Vehicles: A Study of Technology Acceptance Factors

We acknowledge that an earlier version of this material was presented in a conference at the International Conference on Information Society (i-Society 2023), held on 24th to 26th October 2023, Dublin, Ireland.This study will examine user acceptance towards the latest autonomous vehicle technologies with a focus on vehicle-to-vehicle (V2V) and vehicle-to infrastructure (V2I) technologies. An online survey was utilised to collect 203 responses (from a diverse group of people with about 35 master students). This research will predominantly utilise a quantitative research approach to study consumer views on autonomous vehicle technologies and will be conducted amongst professional and nonprofessional drivers. The technology acceptance model (TAM) by Davis represents the underlying research model of this study updated to include significant factors. Hypothesis testing is performed for three scenarios (AV, V2V, and V2I) using multiple regression analysis and ANOVA test in SPSS version 20. However, the outcomes of this study revealed that V2V exhibited the most considerable and statistically significant positive impact on the driver, as evidenced by the variables compatibility (COP) and perceived ease of use (PEOU). Besides, the study also conducted on V2I demonstrated that the most significant positive influence was observed by attitude towards using (ATU) and driver context (DC), which relates to the existing literature on pervasive computing. Furthermore, it was found that PEOU and DC variables exhibited a strong positive impact on autonomous vehicles (AV), with statistical significance

Is Australia Ready for Autonomous Vehicles? Examining the Factors Influencing AV Adoption through Expert Interviews

As Autonomous Vehicles (AVs) on public roads today becomes an increasingly realistic possibility, there is growing need to better understand the factors that will facilitate their successful introduction. This study focuses specifically on Australia and investigates various micro and macro environmental factors that may either hinder or support their adoption in the country. The study comprised 18 in-depth interviews with experts from both the public and private sectors who possess direct experience working with AVs. These experts provided valuable insights into several areas, including the legislation and regulations governing AV use, the technical and infrastructure requirements necessary for safe operation on public roads, and the importance of public sentiment in driving AV adoption and introduction. Based on the study’s findings, an integrated framework has been developed to identify and classify the key factors related to AV adoption, as well as their interrelatedness with each other. This framework seeks to guide the development of national strategies to accommodate the necessary political, legal, and social adjustments required for the successful implementation of AVs

Driving forward together : the common intention of Indonesians in different residential areas to use autonomous vehicles

Despite the significant benefits of Autonomous Vehicles (AVs) for global transportation, Indonesia's diverse geographical landscape encounter unique adoption challenges due to infrastructural shortcomings and economic limitations. This study explores the adoption of AVs in Indonesia, considering its potential market and crucial role in AV and Electric Vehicle supply chains. Drawing upon the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT), we assessed AV acceptance across Indonesia's Metropolitan Cities, frontier regions (“3T”), and the New National Capital City (IKN) areas. Using a cross-sectional study design, we distributed an online questionnaire, focusing on demographics, perceived safety, transport mode changes, and behavioral intention towards AVs, based on TAM and UTAUT factors. From 1,255 valid responses, we found significant influences of gender (t (1253) = 4.22), safety perceptions (F (2,1252) = 52.373), and transport mode frequency (F (4, 1250) = 6.662) on AVs adoption intentions. Both TAM and UTAUT models were moderately effective in explaining willingness to use AVs (R2 = 34% and 48%, respectively). TAM highlighted perceived usefulness (β = 0.421) and ease of use (β = 0.540), while UTAUT emphasized effort expectancy (β = 0.317) and social influence (β = 0.240). However, the findings from the multigroup analysis did not corroborate the role of residential areas in determining the intention to use AVs. These findings offer crucial insights for developing AV promotion strategies, creating user-friendly designs, and formulating supportive policies for AV adoption in diverse Indonesian regions

The relevance of social factors in sharing a trip with strangers: Creating travel communities in the autonomous vehicles era

There has been a growing interest in autonomous vehicles (AVs) for the past few years due to technological innovation and their far-reaching expected impacts on urban mobility. The impact of AVs depends ultimately on how the technology will be adopted, e.g. privately or shared AVs (SAVs), and integrated into the socio-technical mobility system. In this study, we evaluate how social considerations and the AV technology may enhance new social arrangements for travel, especially for groups suffering from some disadvantages in accessing transport. Particularly, we explore a proposed new form of social arrangement, coined “Travel Community” (TC), to create shared AVs trips based on individual preferences. An online national representative sample in Israel was conducted (N = 1009). The data was analyzed using multivariate methods including multinomial logistic regression models for the willingness to adopt TC in two contexts: commuting (TCC) and travel leisure (TCL). The findings suggest that TC was well accepted by the participants under certain assumptions and could address latent demand for improving travel options for people with different constraints accessing transport, such as women, young, sporadic travelers, and low-income individuals. The personal social preferences option might help overcome psychological barriers regarding shared mobility, such as the fear of sharing the trip with strangers and a social value promoting a new kind of social interaction. Planners and stakeholders should consider social considerations' relevance (opportunities and risks) for promoting and creating new forms of mobility and improving urban sustainability and social inclusion

Commercial Short-Haul Flight or Autonomous Mobility-On-Demand: Modeling Air Passengers’ Modal Choice

Commercial short-haul flights (SF) are vital to airports and airlines because they account for one-third of hub traffic and have higher profit margins than the long-haul market. While U.S. commercial air passenger travel has increased steadily over the past decades, SF has been declining and was doing so before the unprecedented decrease in air travel caused by restrictions related to the COVID-19 global pandemic. Once autonomous mobility-on-demand (aMoD) is more viable than the human-driven car, demand for SF could be negatively impacted. Although there is published research on SF and aMoD, studies on factors influencing the choice between SF and aMoD are missing. Based on goal framing theory (GFT) variables, contextual trip attributes, COVID-19 items, and demographics, this study used a quantitative survey design to answer two research questions. The first question sought to identify factors that most influence U.S. air travelers’ modal choice for inter-regional travel. The second question aimed to identify distinct passenger clusters for SF and aMoD and evaluate the similarities and differences within these passenger segments. An online questionnaire of 69 items was developed based on extant literature and the theoretical foundation of the GFT. The survey was administered online with an air passenger sample in October 2021 via Amazon’s MTurk Results from 1,388 air passenger respondents qualified for data analyses, including exploratory factor analysis (EFA), multinomial logistic regression (MNL), two-step cluster analysis (CA), and multivariate analysis of variance (MANOVA). The findings support the GFT as a theoretical framework for modeling future mode choice and SF and aMoD clusters. The current primary transport mode was the most critical predictor for future mode choice. Self-efficacy, value of time, trust, and habit are new variables added to the GFT framework. The first two were useful in predicting future mode choice; trust and habit were not. Two-thirds (66%) of the current SF passengers intend to shift to other transport modes once aMoD is available; 31% of the current SF market share could be lost to aMoD and 20% to conventional driving. More than half of the current most-traveled air passengers intend to use aMoD as their main transport choice. The potential significant shifts in the ground- and air-mode shares revealed in this study may have crucial impacts on airlines, airports, infrastructure, future air/land-use planning, and the travel and hospitality industries

Automated vehicles and future transport inequalities in the UK. Exploring the potential accessibility implications for older people

It is often argued that automated vehicles (AVs) will reduce the unmet accessibility needs of older people. However, these assumptions tend to overlook the potential barriers to AV uptake for older population groups and the fact that AVs may have broader effects on mobility behaviours and transport systems. Although these impacts cannot be predicted with certainty, early engagement with these questions may assure that older people’s accessibility needs are considered in future transport policy. The thesis focuses on two critical research gaps to untangle the future accessibility implications of AVs. First, it explores how transport policymakers perceive and plan to manage the effects of AVs on older people’s accessibility. Second, it investigates older people’s perceptions and acceptance of AVs. The research draws from a content analysis of strategy and planning documents from transport authorities in England and interviews with transport policymakers and experts. Key findings are that while there is an emphasis on the potential of AVs for the UK ageing society, certain barriers to adoption of AVs are often overlooked. Moreover, the potential impacts of AVs on older people’s accessibility as users of other modes (e.g. walking) are not considered. Transport authorities have mostly played a facilitating role in the development of AVs, but have not yet developed plans and policies to ensure that older people will benefit from the transition to AVs. Through interviews with older citizens in Greater Manchester, the research identifies that some older people perceive that AVs would improve their current or future accessibility levels. Nevertheless, several factors may inhibit the ability and willingness of some older population groups to use AVs. Finally, the study explored older people’s acceptance of different automated transport services. Although most interviewees appeared as willing to use at least some of the proposed services, some showed strong reluctance to use AVs