A multi-level model on automated vehicle acceptance (MAVA): a review-based study

Evidence of automated vehicle safety's influence on people's acceptance of the automated driving technology

Existing studies identified targeted audiences showing increases in Automated Vehicles (AV) acceptance after experiencing automated driving. However, there is still uncertainty regarding the reasons. Although some studies cited safety as the primary reason, there is no objective evidence from safety performance in verifying its impact on AV acceptance. This study contributes to the literature by quantitatively revealing why AV acceptance is changed after experiencing automated driving via a Structural Equation Modeling (SEM) method and objectively validating that safety is the primary factor in determining AV acceptance. Sixty drivers completed driving tasks on a driving simulator under Levels 0, 4, 3, and 2 and survey questions in between. As a result, the safety-related perceptions of AV were identified as reasons for affecting AV acceptance. Particularly, the evaluation of traffic conflicts and conflict severity validates the results from SEM, proving that safety is the primary and significant reason for influencing AV acceptance.

Knowledge as a key determinant of public support for autonomous vehicles

Autonomous vehicles (AVs) have the potential to revolutionize transportation safety and mobility, but many people are still concerned about the safety of AVs and hesitate to use them. Here we survey 4112 individuals to explore the relationship between knowledge and public support for AVs. We find that AV support has a positive relationship with scientific literacy (objective knowledge about science) and perceived understanding of AV (self-assessed knowledge). Respondents who are supportive of AVs tended to have more objective AV knowledge (objective knowledge about AVs). Moreover, the results of further experiments show that increasing people's self-assessed knowledge or gaining additional objective AV knowledge may contribute to increasing their AV support. These findings therefore improve the understanding of the relationship between public knowledge levels and AV support, enabling policy-makers to develop better strategies for raising AV support, specifically, by considering the role of knowledge, which in turn may influence public behavioural intentions and lead to higher levels of AV acceptance.

Trusting autonomous vehicles as moral agents improves related policy support

Compared to human-operated vehicles, autonomous vehicles (AVs) offer numerous potential benefits. However, public acceptance of AVs remains low. Using 4 studies, including 1 preregistered experiment (total N = 3,937), the present research examines the role of trust in AV adoption decisions. Using the Trust-Confidence-Cooperation model as a conceptual framework, we evaluate whether perceived integrity of technology—a previously underexplored dimension of trust that refers to perceptions of the moral agency of a given technology—influences AV policy support and adoption intent. We find that perceived technology integrity predicts adoption intent for AVs and that messages that increase perceived integrity of AV technology result in greater AV adoption intent and policy support. This knowledge can be used to guide communication efforts aimed at increasing public trust in AVs, and ultimately enhance integration of AVs into transport systems.

Usability testing of three visual HMIs for assisted driving: How design impacts driver distraction and mental models

There is a variety of visual human-machine interfaces (HMI) designed across vehicle manufacturers that support drivers while supervising driving automation features, such as adaptive cruise control (ACC). These various designs communicate the same limited amount of information to drivers about their ACC system and it is unclear which HMI designs impact driver distraction the least or how their design could be modified to help drivers develop more accurate mental models of their ACC system. Using a user-centred design (UCD) approach, we designed a speedometer to inform drivers about some of the system's capabilities and then invited 23 drivers to use ACC in a low-fidelity driving simulator to compare the usability of three HMIs using eye-tracking, response times, and qualitative data. Our attempt at designing an intuitive and more informative speedometer received mixed results, but design recommendations are given regarding the indication of the set target speed, set time gap between vehicles (headway distance), and system mode (conventional or adaptive cruise). Practitioner summary: Manufacturers' heterogeneous designs of their visual HMIs for the ACC systems may impact driver distraction in different ways. We used usability testing to compare three HMIs in a driving simulator and make several design recommendations to indicate speed, time gap, and system mode in a more efficient way. Abbreviations: ACC: adaptive cruise control; ADAS: advanced driving assistance system; HMI: human-machine interface; ISO: international organisation for standardization; OEM: original equipment manufacturer; RSME: rating scale of mental effort; RT: response time; R-TLX: raw task load index; SUS: system usability scale; TGT: total glance time; UCD: user-centred design; UX: user experience; xTGT: extended total glance time.

A Video-Based, Eye-Tracking Study to Investigate the Effect of eHMI Modalities and Locations on Pedestrian–Automated Vehicle Interaction

Numerous studies have emerged on the external human–machine interface (eHMI) to facilitate the communication between automated vehicles (AVs) and other road users. However, it remains to be determined which eHMI modality and location are proper for the pedestrian–AV interaction. Therefore, a video-based, eye-tracking study was performed to investigate how pedestrians responded to AVs with eHMIs in different modalities (flashing text, smiley, light band, sweeping pedestrian icon, arrow, and light bar) and locations (grill, windshield, and roof). Moreover, the effects of pedestrian-related factors (e.g., gender, sensation-seeking level, and traffic accident involvement) were also included and evaluated. The dependent variables included pedestrians’ clarity-rating scores towards these eHMI concepts, road-crossing decision time, and gaze-based metrics (e.g., fixation counts, dwell time, and first fixation duration). The results showed that the text, icon, and arrow-based eHMIs resulted in the shortest decision time, highest clarity scores, and centralized visual attention. The light strip-based eHMIs yielded no significant decrease in decision time yet longer fixation time, indicating difficulties in comprehension of their meaning without learning. The eHMI location had no effect on pedestrians’ decision time but a substantial influence on their visual searching strategy, with a roof eHMI contradicting pedestrians’ inherent scanning pattern. These findings provide implications for the standardized design of future eHMIs.

The Effect of eHMI Malfunctions on Younger and Elderly Pedestrians' Trust and Acceptance of Automated Vehicle Communication Signals

To ensure traffic flow and road safety in automated driving, external human-machine interfaces (eHMIs) could prospectively support the interaction between automated vehicles (AVs; SAE Level 3 or higher) and pedestrians if implicit communication is insufficient. Particularly elderly pedestrians (≥65 years) who are notably vulnerable in terms of traffic safety might benefit of the advantages of additional signals provided by eHMIs. Previous research showed that eHMIs were assessed as useful means of communication in AVs and were preferred over exclusively implicit communication signals. However, the attitudes of elderly users regarding technology usage and acceptance are ambiguous (i.e., less intention to use technology vs. a tendency toward overreliance on technology compared to younger users). Considering potential eHMI malfunctions, an appropriate level of trust in eHMIs is required to ensure traffic safety. So far, little research respected the impact of multiple eHMI malfunctions on participants' assessment of the system. Moreover, age effects were rarely investigated in eHMIs. In the current monitor-based study, N = 36 participants (19 younger, 17 elderly) repeatedly assessed an eHMI: During an initial measurement, when encountering a valid system and after experiencing eHMI malfunctions. Participants indicated their trust and acceptance in the eHMI, feeling of safety during the interaction and vigilance toward the eHMI. The results showed a positive effect of interacting with a valid system that acted consistently to the vehicle's movements compared to an initial assessment of the system. After experiencing eHMI malfunctions, participants' assessment of the system declined significantly. Moreover, elderly participants assessed the eHMI more positive across all conditions than younger participants did. The findings imply that participants considered the vehicle's movements as implicit communication cues in addition to the provided eHMI signals during the encounters. To support traffic safety and smooth interactions, eHMI signals are required to be in line with vehicle's movements as implicit communication cues. Moreover, the results underline the importance of calibrating an appropriate level of trust in eHMI signals. An adequate understanding of eHMI signals needs to be developed. Thereby, the requirements of different user groups should be specifically considered.

Users' acceptance of private automated vehicles: A systematic review and meta-analysis

INTRODUCTION

This research systematically reviewed relevant studies on users' acceptance of conditional (Level 3) to full (Level 5) automated vehicles when such vehicles are to be used privately (herein referred to as 'private automated vehicles or private AVs).

METHOD

The search followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, and was undertaken in three databases: APA PsycINFO, Transport Research International Documentation, and Web of Science. Articles were required to focus on individuals' acceptance of private SAE Level 3-5 AVs. Acceptance was defined as individuals' attitudes towards or intentions and/or willingness to use AVs in the future. A total of 2,354 articles were identified in the database search. Thirty-five articles were included in the review, six of which included multiple studies and/or comparison groups.

RESULTS

Most studies (n = 31) applied self-reported measures to assess user acceptance together with a range of psychosocial factors predicting such acceptance. The meta-analytic correlations revealed that perceived behavioral control, perceived benefits/usefulness, perceived ease of use, and subjective/social norms had significant positive pooled relationships with attitudes and intentions. Trust and sensation seeking also had significant positive pooled correlations with intentions, while knowledge of AVs had a significant and negative pooled correlation with intentions. Age did not show any significant pooled relationship with attitudes, intentions, or willingness.

CONCLUSIONS

The findings obtained from the systematic review and meta-analysis provide support for psychosocial models to aid understanding of users' acceptance of private AVs. Practical applications: Examining acceptance of AVs after participants have experienced these vehicles on closed tracks or open roads would advance contemporary knowledge of users' intentions to use these vehicles in the future. Further, experiencing these vehicles firsthand may also help with addressing any perceived barriers reducing acceptance of future use of private AVs.

User experience and usability when the automated driving system fails: Findings from a field experiment

We are entering an era of automated vehicles (AVs), which has potential to improve road safety considerably. A compelling user experience is crucial to AV adoption in the future commercial market. The automated driving system (ADS) that replaces human drivers should be perceived as very useful before the latter are willing to give up their control and entrust their lives to the ADS. However, compared with the growing number of studies on public acceptance of AVs, there has been limited research focusing on user experience and usability. We examined AV and ADS user experience and usability, ADS failures' influence on them, and their influences on re-riding willingness. We conducted a field study using a real AV and a large-scale test track. We invited participants (N = 261) to travel in the AV as passengers in a low-speed environment. Participants were randomly assigned into the normal condition or the fault condition (its participants were exposed to an ADS failure). We measured participants' positive experience (feeling relaxed, safe, and comfortable) and negative experience (feeling tense and risky) while riding in the AV and perceived usability of the ADS based on the System Usability Scale. In both conditions, participants reported moderate positive experience and perceived usability but a relatively high level of willingness to ride in our AV again. The ADS failure reduced positive experience and perceived usability, and it increased negative experience. Positive experience and perceived usability, but not negative experience, influenced re-riding willingness. Compared with male participants, female participants reported less positive experience and lower perceived usability. We discuss implications of our results as well as limitations of this research.

What drives people to use automated vehicles? A meta-analytic review

Lack of consumer acceptance is a prominent barrier to the large-scale adoption of automated vehicles (AVs). This study investigated the underlying mechanisms for AV acceptance and how the mechanisms differed across subgroups by reviewing and synthesizing existing literature. We proposed AV acceptance models by extending the basic Technology Acceptance Model (TAM) with trust and perceived risk factors. Data from 36 studies were extracted to fit the models using meta-analytic structural equation modeling technique. The results suggested that trust contributed most in determining AV acceptance, followed by perceived usefulness and perceived risk, and perceived ease of use makes the least contribution. The subgroup analyses showed that the model parameters differed across the levels of three variables, i.e., sample origin (Europe/Asia/America), automation level (full/partial), and age (young/middle-aged). Specifically, trust was unanimously identified as the most important determinant of AV acceptance across all subgroups. Perceived risk only remained significant in America, fully AVs, and middle-aged subgroups. Perceived ease of use was insignificant in the above-mentioned three subgroups while remained significant in the rest subgroups. Building trust could be the most useful and universal way to improve AV acceptance, and policy makers should consider the characteristics of consumers when making AV promotion strategies.

Advancing Behavioural Theories in Sustainable Mobility: A Research Agenda

Ensuring that the growing mobility demand is met in a sustainable manner is important for our climate goals, and this would require changes to our current mobility behaviours. Behaviour and behaviour change theories have an important role in informing the mobility behaviour research and practices that seek to achieve these changes, and this paper discusses the application of these theories in both research and practice. Newer and more comprehensive theories have been developed in this area in the last decade, improving the quality of theories available. However, two key challenges of using theories are identified. The great number of theories today makes it challenging when deciding what and when to use them, and the appropriateness of many theories are either too simplistic or too complex. Thus, there is a need to critically review the state of theories in this area and identify ways to advance our application and development of behavioural theories. Here, two suggestions are put forward on how we can address these challenges while advancing the use of theories in mobility behaviour research and practice. First, integrate and summarise multiple, individual theories into a comprehensive and accessible framework for researchers and practitioners. Second, expand this framework beyond behaviour and behaviour-change theories by mapping out their interconnections with theories from other paradigms and disciplines using a systems approach to facilitate a more holistic theorisation.

Factors that influence parents' intentions of using autonomous vehicles to transport children to and from school

High-level autonomous vehicles (AVs) are likely to improve the quality of children's travel to and from school (such as improve travel safety and increase travel mobility). These expected benefits will not be presented if parents are not willing to use AVs. Therefore, it is necessary to explore parents' intentions of using AVs to transport children to and from school (parents' intentions). This study has two primary aims: 1) Exploring parents' intentions and their potential determinants. 2) Making recommendations for manufacturers to develop and market AVs suitable for school travel based on the research results. Research results show that face consciousness with Chinese characteristics can significantly affect parents' intentions. Knowledge of AVs is the most significant factor in influencing parents' intentions. Perceived usefulness, attitude towards school travel in AVs, and perceived risk can significantly affect parents' intentions. The direct impact of perceived ease of use and public engagement on parents' intentions is not significant. Finally, this research could provide decision-making support for governments and manufacturers to formulate relevant policies and marketing strategies, promoting parents' acceptance of AVs.

Older adults' acceptance of fully automated vehicles: Effects of exposure, driving style, age, and driving conditions

Automated vehicles are anticipated to have benefits for older adults in maintaining their mobility and autonomy. These anticipated benefits can only be realized if this technology is accepted and thus used by older adults. However, it remains unclear how certain factors affect older adults' acceptance of automated vehicles. This study investigated the extent to which older adults' acceptance of fully automated vehicles are affected by exposure to automated vehicle technology (pre- vs. post-exposure), driving style (manual style relative to automated style), driving conditions (clear, rain, traffic), and age. Thirty-six older adults (M = 73.25, SD = 5.96) completed non-automated (manual) and fully automated driving scenarios under different driving conditions in a high-fidelity driving simulator. The fully automated driving scenarios were designed to be reliably driven by the system in a conservative driving style. Driving conditions included clear daytime, rain, and high-traffic. Pre- and post-exposure to the simulated fully automated driving experience, participants rated their comfort level with fully automated vehicles (FAVs). Additionally, after each driving condition, participants answered a validated questionnaire on their acceptance of the simulated fully automated experience for each respective driving condition. Age and driving style were found to have a significant effect on older adults' acceptance of FAVs, with older age and greater dissimilarity of an individual's manual driving style from the FAV's driving style being associated with lower acceptance. The results suggest that if reliability of fully automated vehicles is ultimately ensured and is demonstrated to the older adults, their acceptance of fully automated vehicles is generally high, particularly if the FAV is operated in a style similar to their own.

Concept of an Ontology for Automated Vehicle Behavior in the Context of Human-Centered Research on Automated Driving Styles

In the human-centered research on automated driving, it is common practice to describe the vehicle behavior by means of terms and definitions related to non-automated driving. However, some of these definitions are not suitable for this purpose. This paper presents an ontology for automated vehicle behavior which takes into account a large number of existing definitions and previous studies. This ontology is characterized by an applicability for various levels of automated driving and a clear conceptual distinction between characteristics of vehicle occupants, the automation system, and the conventional characteristics of a vehicle. In this context, the terms ‘driveability’, ‘driving behavior’, ‘driving experience’, and especially ‘driving style’, which are commonly associated with non-automated driving, play an important role. In order to clarify the relationships between these terms, the ontology is integrated into a driver-vehicle system. Finally, the ontology developed here is used to derive recommendations for the future design of automated driving styles and in general for further human-centered research on automated driving.

Does initial experience affect consumers' intention to use autonomous vehicles? Evidence from a field experiment in Beijing

The demonstration, showcase, and city studies of autonomous vehicles (AVs) provide valuable opportunities for the public to interact with AV. Understanding the relationship between experiencing and intention to use AV is crucial because first-hand experience shapes an individual's initial impressions on autonomous driving. This study investigated the users' intention to use AVs based on extended theory of planned behavior, which incorporated experience satisfaction and trust. The data were collected through a field experiment from 117 respondents who had experienced a SAE Level 4 autonomous minibus in China. The proposed relationships were examined using partial least squares structural equation modelling. A satisfied experience contributes to a higher degree of trust, attitude, subjective norm (SN), and perceived behavioral control (PBC). Excluding SN, results suggest that attitude, PBC, experience satisfaction, and trust, are statistically proven to affect the intention to use AV. Moreover, an examination of individual difference reflects that the impact of experience satisfaction on PBC varies distinctively in male and female group, as well as in less educated and more educated group. Findings show the theoretical contributions and practical implications on the role of initial experience of AV acceptance.

How Can Smart Mobility Innovations Alleviate Transportation Disadvantage? Assembling a Conceptual Framework through a Systematic Review

Transportation disadvantage is about the difficulty accessing mobility services required to complete activities associated with employment, shopping, business, essential needs, and recreation. Technological innovations in the field of smart mobility have been identified as a potential solution to help individuals overcome issues associated with transportation disadvantage. This paper aims to provide a consolidated understanding on how smart mobility innovations can contribute to alleviate transportation disadvantage. A systematic literature review is completed, and a conceptual framework is developed to provide the required information to address transportation disadvantage. The results are categorized under the physical, economic, spatial, temporal, psychological, information, and institutional dimensions of transportation disadvantage. The study findings reveal that: (a) Primary smart mobility innovations identified in the literature are demand responsive transportation, shared transportation, intelligent transportation systems, electric mobility, autonomous vehicles, and Mobility-as-a-Services. (b) Smart mobility innovations could benefit urban areas by improving accessibility, efficiency, coverage, flexibility, safety, and the overall integration of the transportation system. (c) Smart mobility innovations have the potential to contribute to the alleviation of transportation disadvantage. (d) Mobility-as-a-Service has high potential to alleviate transportation disadvantage primarily due to its ability to integrate a wide-range of services.

Understanding Public Acceptance of Autonomous Vehicles Using the Theory of Planned Behaviour

Public acceptance of autonomous vehicles (AVs) is vital for a society to reap their intended benefits such as reduced traffic accidents, land usage, congestion and environmental pollution. The purpose of this paper is to use the theory of planned behaviour to pinpoint and examine the components affecting public acceptance of AVs. A model consisting of a network of hypothesised relationships is introduced. Thereafter, 526 residents in Seoul, Korea, were given a survey created for this research. Subsequently, to evaluate the collected information and estimate the model, structural equation modelling was adopted. The outcomes show individuals’ mindset on AVs, subjective customs, and behavioural influence directly influencing the acceptance of AVs. Furthermore, cognitive and emotive factors, namely comparative advantage, compatibility, complexity and hedonic motivation indirectly influence the acceptance of AVs via mindset and behavioural manipulation. Based on analysing the cumulative effect, attitude emerged with the strongest effect on public acceptance of autonomous vehicles. After this is, in decreasing order of influence, behavioural control, relative advantage, subjective norms, compatibility, hedonic motivation and complexity. The findings of this study implicate the prioritisation and allocation of resources, and policies relating to marketing, education, subsidisation and infrastructure development to better public acceptance of AVs.

Understanding Autonomous Road Public Transport Acceptance: A Study of Singapore

This study examines the perceptions of concerns and benefits surrounding autonomous road vehicles deployed for public transport, their relationships with public acceptance, and what the public prefers during its implementation. Surveying 210 participants in Singapore, we found a general acceptance of the deployment of autonomous road public transport in Singapore with agreement that introducing them would be beneficial, particularly in improving public transport reliability and accessibility. However, they reported concerns in the areas of technical-related issues and legal liability. Participants who perceived greater benefits were also likely to report greater acceptance, even after taking into account their concerns and sociodemographic backgrounds. Participants also reported preferences for human operators to continue playing an active role, the government to test the autonomous vehicles extensively before making them available for public use and greater clarity on the legal liability when accidents involving autonomous vehicles occur when autonomous road public transport is eventually implemented.

Ready to bully automated vehicles on public roads?

Automated vehicles (AVs), the wide adoption of which is expected to improve traffic safety significantly, are penetrating our roads. The AVs that are testing on public roads have been bullied by human road users. We are not sure whether the bullying incidents are isolated or will be common in the future. In a cross-national survey (N = 998 drivers in China and South Korea), we developed an eleven-item bullying intention questionnaire. We assumed and confirmed that, overall, participants had a greater intention to bully machine drivers than to bully other human drivers. Compared to the Korean participants, the Chinese participants reported a greater intention to drive aggressively. The correlations of their intention to bully AVs with their attitude toward AVs and with risk-benefit perception of AVs were weak. Male participants (vs. female participants) and younger participants (vs. older participants) reported a greater intention to drive aggressively. Drivers' aggressive behaviors toward AVs might be common in the future, which might increase traffic risk and hinder the implementation of this technology.