Consequences of autonomous vehicles: Ambivalent expectations and their impact on acceptance

Connected and autonomous vehicles (CAVs) are within reach of widespread deployment on public roads, but public perceptions are ambivalent. The objective of the present research was to assess expectations about the consequences of CAV introduction. These expectations should explain CAV acceptance, but their relative importance is poorly understood. We conducted a survey with a representatively drawn panel sample (N = 529) from France, Germany, Italy, and the UK. The survey consisted of a large item pool of expected consequences from CAV introduction, as well as general and affective evaluation of CAVs, ease of use, and behavioral intention to use CAVs. Exploratory factor analysis revealed four facets of expected consequences: road safety, privacy, efficiency and ecological sustainability. On average, expectations were mostly positive for ecological sustainability and safety, but negative for privacy. At the same time, substantial variance existed between respondents and between countries. For safety and efficiency, improvement was expected by a third of respondents, while another third expected worsening. Respondents from Italy expected more positive consequences for safety, while respondents from both France and Germany expected more negative consequences for privacy. To different degrees, all four facets predicted the intention to use CAVs in a structural equation model, primarily via affective evaluations. For policy makers, manufacturers, and service providers, understanding the trade-offs inherent to different CAV solutions will be central to ensure citizens’ needs are respected.     

What are the factors determining user intentions to use AV while impaired?

In this study, we employ the Integrated Choice Latent Variable (ICLV) framework to model the public’s intention of using Autonomous Vehicles (AVs) while impaired under the influence of alcohol, medicine, or fatigue. We identify five latent constructs from psychometric indicators that define respondent’s perception and attitudes towards AVs which are i) perceived benefits, ii) perceived risks, iii) enjoy driving, iv) wheels public transport attitude, and v) rails public transport attitude. We use these latent variables along with explanatory variables to study user intentions regarding delegation of vehicle control from human driving to autonomous driving. The study uses survey data collected from 1,065 Czech residents between 2017 and 2018. Our findings indicate that user intentions are primarily defined by attitudes rather than socio-demographic attributes. However, the inclusion of both types of variables is crucial in evaluating user intentions. Despite a positive outlook towards AVs, people were found to be reluctant in using AVs while impaired which can be attributed to distrust towards the technology. Our analysis shows that with appropriate efforts from policymakers, the public’s attitude can be changed to promote adoption. The efforts will have to be emphasized towards building positive attitudes (such as perceived benefits) and diminishing existing negative attitudes (such as perceived risks).     

Factors that influence the acceptance of future shared automated vehicles – A focus group study with United Kingdom drivers

The development of Shared Automated Vehicles (SAVs) is well underway to provide mobility as a service (MaaS) and bring benefits such as reduced traffic congestion, reduced reliance on privately owned vehicles and increased independence to non-drivers. To realise the benefits of SAVs, adoption by private vehicle users is crucial. Previous research has shown this subset of users as the least likely to adopt SAVs, and it is not well understood what factors are important to achieve such adoption. The purpose of this study is to obtain an in-depth understanding of attitudes, perceptions and preferences that influence the acceptance of future SAVs for drivers. This paper presents the results from an online asynchronous focus group study with 21 British drivers as participants. From the analysis, Service Quality, Trust and Price Value emerged as the three most prominent factors to understand user acceptance of SAVs. These three main factors may be of prime importance for convincing naïve private car owners to accept high-speed SAVs. Productive use of travel time has been frequently mentioned in previous research as a benefit of vehicle automation but was scarcely mentioned by participants in this study. Shared Space Quality in introduced as an indicator for Service Quality, together with Security and Trusting Co-passengers as two indicators of Trust. Based on the findings, this paper concludes with a conceptual SAV technology acceptance model is introduced, with the results added as extended model predictors to the Unified Theory of Acceptance and Use of Technology (UTAUT2).     

Perceived risk of using shared mobility services during the COVID-19 pandemic

The COVID-19 pandemic has caused our daily routines to change quickly. The pandemic provokes public fear, resulting in changes in what modes of transport people use to perform their daily activities. It is imperative for transportation authorities to properly identify the different degrees of behavioral change among various social groups. A major factor that can substantially explain individuals’ behavioral changes is the personal risk perceptions toward using shared mobility solutions. Thus, this study explores the risk that individuals perceive while using public transit and ridesharing services (as the most widespread forms of shared mobility) during the COVID-19 pandemic. To do so, we designed and implemented a multidimensional travel-behavior survey in the Chicago metropolitan area that comprises socio-demographic information and retrospective questions related to attitudes and travel behavior before and during the pandemic. Utilizing a bivariate ordered probit modeling approach to better account for the potential correlation between unobserved factors, we simultaneously modeled the perceived risk of exposure to the novel coronavirus in case of riding transit and using ridesharing services. A wide range of factors is found to be influential on the perceived risk of using shared mobility services, including the socio-demographic attributes, built environment settings, and the virus spread. Further, our results indicate that the mitigation strategies to increase the ridership of shared mobility services should be adaptive considering the spatial variations.     

Identifying when children with visual impairment share attention: A novel protocol and the impact of visual acuity

BackgroundIn Coordinated Joint Engagement (CJE), children acknowledge that they and their social partners are paying attention to the same object. The achievement of CJE, critical for healthy development, is at risk in infants with visual impairment (VI). Research on CJE in these children is limited because investigators use a child’s gaze switch between social partner and object to index CJE. Research is needed that identifies CJE in children with VI using behaviors that do not require normal vision and that explores the relationship between CJE and visual function. This study aimed to (a) develop a protocol for identifying CJE in children with VI, and (b) explore the relationship between CJE and infants’ visual acuity (VA) and contrast sensitivity (CS), measured with Preferential Looking (PL) techniques and Visual Evoked Potential (VEP).MethodsA protocol that included 9 indices of CJE that did not require normal vision was developed to code videos of 20 infants with VI (mean age =1 year, 6 months, 27 days) and their caregivers. The percentage of CJE episodes in which each index was observed was calculated. Inter-coder reliability was measured using Cohen’s Kappa. Linear regression analysis was used to examine the relationship between the infants’ visual function and CJE.ResultsInter-rater reliability between a first coder and each of two second coders were 0.98 and 0.90 for determining whether the child participated in CJE. The following indices were observed the most (in 43–62 % of CJE): child’s body orientation to caregiver, gaze switch between caregiver and object, and vocalization to caregiver. The only significant model included VA (measured with PL) as a single predictor and explained 26.8 % of the variance in CJE.ConclusionsThe novel protocol can be used to identify CJE in children with VI with good inter-coder reliability. The data suggest that children with lower VA exhibited less CJE.     

Seeing the mind of robots: Harm augments mind perception but benevolent intentions reduce dehumanisation of artificial entities in visual vignettes

According to moral typecasting theory, good- and evil-doers (agents) interact with the recipients of their actions (patients) in a moral dyad. When this dyad is completed, mind attribution towards intentionally harmed liminal minds is enhanced. However, from a dehumanisation view, malevolent actions may instead result in a denial of humanness. To contrast both accounts, a visual vignette experiment (N = 253) depicted either malevolent or benevolent intentions towards robotic or human avatars. Additionally, we examined the role of harm-salience by showing patients as either harmed, or still unharmed. The results revealed significantly increased mind attribution towards visibly harmed patients, mediated by perceived pain and expressed empathy. Benevolent and malevolent intentions were evaluated respectively as morally right or wrong, but their impact on the patient was diminished for the robotic avatar. Contrary to dehumanisation predictions, our manipulation of intentions failed to affect mind perception. Nonetheless, benevolent intentions reduced dehumanisation of the patients. Moreover, when pain and empathy were statistically controlled, the effect of intentions on mind perception was mediated by dehumanisation. These findings suggest that perceived intentions might only be indirectly tied to mind perception, and that their role may be better understood when additionally accounting for empathy and dehumanisation.     

The first direct replication on using verbal credibility assessment for the detection of deceptive intentions

Verbal deception detection has gained momentum as a technique to tell truth‐tellers from liars. At the same time, researchers' degrees of freedom make it hard to assess the robustness of effects. Replication research can help evaluate how reproducible an effect is. We present the first replication in verbal deception research whereby ferry passengers were instructed to tell the truth or lie about their travel plans. The original study found truth‐tellers to include more specific time references in their answers. The replication study that closely mimicked the setting, procedure, materials, coding, and analyses found no lie–truth difference for specific time references. Although the power of our replication study was suboptimal (0.77), Bayesian statistics showed evidence in favor of the null hypothesis. Given the great applied consequences of verbal credibility tests, we hope this first replication attempt ignites much needed preregistered, high‐powered, multilab replication efforts.     

Trust in organization as a moderator of the relationship between self‐efficacy and workplace outcomes: A social cognitive theory‐based examination

Drawing on a social cognitive theory perspective, we contend that an employee's trust in oneself, or self‐efficacy, will interact with the individual's trust in the system, or trust in organization, to predict job attitudes and behaviours. Specifically, we expected that self‐efficacy would have stronger effects on job attitudes (job satisfaction and turnover intentions) and behaviours (task performance and organizational citizenship behaviours) to the degree to which employees perceive high levels of trust in organization. Using data collected from 300 employees and their respective supervisors at a manufacturing organization in Turkey across three waves, we found that self‐efficacy had more positive effects on job satisfaction, task performance, and citizenship behaviours when trust in organization was high. Interestingly, self‐efficacy had a positive effect on turnover intentions when trust in organization was low, indicating that high trust in organization buffered the effects of self‐efficacy on intentions to leave. The results suggest that the motivational value of trust in oneself is stronger to the degree to which employees also have high trust in the system, whereas low trust in system neutralizes the motivational benefits of self‐efficacy.

Practitioner points

• Practicing managers should not only invest in increasing self‐efficacy of their employees, but also invest in building trust to improve employees’ attitudes, behaviours, and performance. This is because when employee trust in organization is high, employee self‐efficacy has greater potential to have a positive influence over job satisfaction, task performance, and organizational citizenship behaviours.
• Self‐efficacy may actually increase an employee's desire to leave the organization when organizational conditions are unfavourable, such as in the case of low trust in the organization. Practicing managers should be aware that employees who have high levels of confidence may be at higher risk of turnover when they are unhappy with the organization.

     

Research on parking choice behavior of shared autonomous vehicle services by measuring users’ intention of usage

Shared autonomous vehicles (SAVs) are one of the important development directions of smart and green transportation. However, relevant researches are not sufficient at present. The factors influencing the intention to use SAVs and their parking choice behaviors need to be further analyzed. First, in order to better explain, predict, and improve travelers’ intention to use SAVs, the conceptual framework based on technology acceptance model was developed to establish the relationships between the travelers’ intention to use SAVs, social influence of SAVs, attitude toward behavior of SAVs, perceived risk of SAVs, perceived usefulness of SAVs and perceived ease of these use. Then structural equation model (SEM) was established to analyze the relationship between various variables. The results show that the perceived usefulness, behavior attitude, social influence, perceived ease of use, and perceived risk are the main factors that determine the intention to use SAVs. Through the test of direct effect, indirect effect, and total effect in the model, it is found that perceived usefulness has the largest total impact on intention to use SAVs, with a standardized coefficient of 0.765, followed by behavior attitude (0.732), social influence (0.597), perceived ease of use (0.462) and perceived risk of SAVs (−0.452). In addition, through the study of observed indicator variables ATB2 and BI3, it is found that perceived usefulness, perceived ease of use, social influence, perceived risk, attitude toward behavior, and behavior intention all have an impact on parking behavior. In order to study the specific influencing factors of parking choice behavior, a multinomial logit (MNL) model was established to analyze the relationships between travelers’ parking choice behaviors and the influential factors, which include travelers’ individual characteristics, travel attributes, and parking modes’ attributes by extracting from a questionnaire. The results show that the travel time, travel fees, parking charge, cruising fees, parking time and traffic emission are the main factors that determine travelers’ choices of parking. This paper provides advice for operators of SAVs.