The influence of system transparency on trust: Evaluating interfaces in a highly automated vehicle

Previous studies indicate that, if an automated vehicle communicates its system status and intended behaviour, it could increase user trust and acceptance. However, it is still unclear what types of interfaces will better portray this type of information. The present study evaluated different configurations of screens comparing how they communicated the possible hazards in the environment (e.g. vulnerable road users), and vehicle behaviours (e.g. intended trajectory). These interfaces were presented in a fully automated vehicle tested by 25 participants in an indoor arena. Surveys and interviews measured trust, usability and experience after users were driven by an automated low-speed pod. Participants experienced four types of interfaces, from a simple journey tracker to a windscreen-wide augmented reality (AR) interface which overlays hazards highlighted in the environment and the trajectory of the vehicle. A combination of the survey and interview data showed a clear preference for the AR windscreen and an animated representation of the environment. The trust in the vehicle featuring these interfaces was significantly higher than pretrial measurements. However, some users questioned if they want to see this information all the time. One additional result was that some users felt motion sick when presented with the more engaging content. This paper provides recommendations for the design of interfaces with the potential to improve trust and user experience within highly automated vehicles.     

Modelling the acceptance of fully autonomous vehicles: A media-based perception and adoption model

As the technology matures, fully autonomous vehicles (AVs) are on the corner. This calls for exploring the factors that might influence potential users’ perception and acceptance of AVs. Limited existing studies related to acceptance modeling investigated the effects of media and human on fully AVs’ beliefs. Hence, a media-based perception and adoption model (MPAM) is developed to investigate how information and opinion (from mass media and social media) affect human self-perception (including self-efficacy and subjective norms) and product value perception (including perceived usefulness and risks), which in turn drive users’ adoption intention to private AVs and public AVs as well. Through a questionnaire survey, 355 samples from two universities were collected in Beijing. The structural equation model results confirm that media channels have salient effects on consumer and product with different emphases. Mass media enhances potential users’ self-efficacy of fully AVs, while social media strengthens subjective norms. Both usefulness and risks of AVs are perceived simultaneously via mass media, whereas risks perception can be significantly eliminated by social media. All constructs of user’s self-perception and product perception are verified to drive users’ intention to using AVs and public AVs. Besides the theoretical and modeling contributions, practical implications are provided for the marketers and stakeholders in the early stages of AVs launch.     

Using the UTAUT2 model to explain public acceptance of conditionally automated (L3) cars: A questionnaire study among 9,118 car drivers from eight European countries

We investigated public acceptance of conditionally automated (SAE Level 3) passenger cars using a questionnaire study among 9,118 car-drivers in eight European countries, as part of the European L3Pilot project. 71.06% of respondents considered conditionally automated cars easy to use while 28.03% of respondents planned to buy a conditionally automated car once it is available. 41.85% of respondents would like to use the time in the conditionally automated car for secondary activities. Among these 41.85%, respondents plan to talk to fellow travellers (44.76%), surf the internet, watch videos or TV shows (44%), observe the landscape (41.70%), and work (17.06%). The UTAUT2 (Unified Theory of Acceptance and Use of Technology) was applied to investigate the effects of performance and effort expectancy, social influence, facilitating conditions, and hedonic motivation on the behavioural intention to use conditionally automated cars. Structural equation analysis revealed that the UTAUT2 can be applied to conditional automation, with hedonic motivation, social influence, and performance expectancy influencing the behavioural intention to buy and use a conditionally automated car. The present study also found positive effects of facilitating conditions on effort expectancy and hedonic motivation. Social influence was a positive predictor of hedonic motivation, facilitating conditions, and performance expectancy. Age, gender and experience with advanced driver assistance systems had significant, yet small (<0.10), effects on behavioural intention. The implications of these results on the policy and best practices to enable large-scale implementation of conditionally automated cars on public roads are discussed.     

Willingness of people who are blind to accept autonomous vehicles: An empirical investigation

Attitudes of a sample of 211 UK people who are blind concerning autonomous vehicles (AVs), and the determinants of the willingness of people who are blind to travel in AVs, were examined. Participants answered an open-ended question regarding their attitudes towards level 5 AVs and the results were analysed using a semi-automated structural topic modelling procedure. (Level 5 AVs are fully autonomous anywhere, and do not require controlled areas in which to operate.) Four “topics” emerged from the exercise: (i) “hope” for future independence and freedom to travel offered by AVs to people who are blind, (ii) scepticism that AVs will ever be configured to meet the needs of people who are blind, (iii) concerns over safety, and (iv) the affordability of AVs. The four topics were employed as mediating variables in a structural equation model designed to explain the respondents’ willingness to travel in an AV. A number of covariates were presumed to influence the four mediating topics, including a participant’s desire for independence, comorbidity, locus of control, and level of generalised anxiety. Three of the mediating variables exerted significant influences on willingness to travel in an AV, i.e., hope for future independence, misgivings about safety, and affordability. Scepticism about AVs did not have a significant effect. Several implications for AV design and for the creation of public information messages promoting AVs are suggested. In particular, public information campaigns should emphasise the freedom to travel that AVs will provide for people who are blind; reassurances concerning safety; and the inevitability of AVs appearing on the roads of economically developed countries.     

Road user interactions in a shared space setting: Priority and communication in a UK car park

Appropriate communication between road users can lead to safe and efficient interactions in mixed traffic. Understanding how road users communicate can support the development of effective communication methods for automated vehicles. We carried out observations of 66 pedestrian-driver and 124 driver-driver interactions in a shared space setting. Specific actions and reactions of the road users involved were recorded using a novel observation protocol. Overall, results showed that pedestrians’ failure to look towards a driver created the greatest uncertainty in the interaction, with the driver slowing down, but not completely stopping, in response to pedestrians. Looking towards the driver also influenced which road user took priority in driver-driver interactions. Groups of pedestrians were more likely to be given priority than an individual pedestrian, and the use of vehicle-based signals were also associated with taking priority during an interaction. Our observations show the importance of non-verbal communication during road user interactions, highlighting it as an essential area of research in the development of automated vehicles, to allow their safe, cooperative, interactions with other road users. Observations were made on a limited number of interactions to inform challenges facing future automated vehicles. Further work should therefore be done to corroborate and extend our findings, to examine interactions between human road users and automated vehicles in shared space settings.     

Who buys New Energy Vehicles in China? Assessing social-psychological predictors of purchasing awareness,intention, and policy

This paper investigates the salience of social-psychological factors in explaining why drivers purchase (or fail to purchase) New Energy Vehicles (NEVs)—including hybrid electric vehicles, battery electric vehicles, and fuel cell electric vehicles—in China. A questionnaire measuring six dimensions (including attitudes, subjective norms, perceived behavioral control, personal norms, low-carbon awareness and policy) was distributed in Tianjin, where aggressive policy incentives for NEVs exist yet adoption rates remain low. Correlation analysis and hierarchical multiple regression analyses are applied data collected through 811 valid questionnaires. We present three main findings. First, there is an “awareness-behavior gap” whereby low-carbon awareness has a slight moderating effect on purchasing behavior via psychological factors. Second, subjective norms has a stronger influence on intention to purchase New Energy Vehicles than other social-psychological factors. Third, acceptability of government policies has positive significant impact on adoption of New Energy Vehicles, which can provide reference potential template for other countries whose market for New Energy Vehicles is also in an early stage.     

Oddity learning by African dwarf goats ( Capra hircus)

Seventeen African dwarf goats (adult females) were trained on oddity tasks using an automated learning device. One odd stimulus and three identical nonodd stimuli were presented on a screen divided into four sectors; the sector for the odd stimulus was varied pseudorandomly. Responses to the odd stimulus were deemed to be correct and were reinforced with food. In phase 1, the goats were trained on eight stimulus configurations. From trial to trial the odd discriminandum was either a + symbol or the letter S, and the nonodd discriminandum was the symbol not used as the odd one. In phase 2, the animals were similarly trained using an unfilled triangle or a filled (i.e., solid black) circle. In phase 3, three new discriminanda were used, an unfilled, small circle with radiating lines, an unfilled heart-shaped symbol, and an unfilled oval; which of the three discriminanda was odd and nonodd was varied from trial to trial. Following these training phases, a transfer test was given, which involved 24 new discriminanda sets. These were presented twice for a total of 48 transfer test trials. Results early in training showed approximately 25% correct, which might be expected by chance in a four-choice task. After 500-2,000 trials, results improved to approximately 40-44% correct. The best-performing subject reached 60-80% correct during training. On the transfer test, this subject had 47.9% correct and that significantly exceeded 25% expected by chance. This finding suggests that some exceptional individuals of African dwarf goats are capable of learning the oddity concept.     

Semi-automated versus highly automated driving in critical situations caused by automation failures

The purpose of this study was to examine the effects of vehicle automation and automation failures on driving performance. Previous studies have revealed problems with driving performance in situations with automation failures and attributed this to drivers being out-of-the-loop. It was therefore hypothesized that driving performance is safer with lower than with higher levels of automation. Furthermore, it was hypothesized that driving performance would be affected by the extent of the automation failure. A moving base driving simulator was used. The design contained semi-automated and highly automated driving combined with complete, severe, and moderate deceleration failures. In total the study involved 36 participants. The results indicate that driving performance degrades when the level of automation increases. Furthermore, it is indicated that car drivers are worse at handling complete than partial deceleration failures.     

Moral disengagement mechanisms in interactions of human drivers with autonomous vehicles: Validation of a new scale and relevance with personality,driving style and attitudes

The introduction of autonomous vehicles (AVs) in the road transportation systems raises questions with respect to their interactions with human drivers’, especially during the early stages. Issues such as unfamiliarity or false assumptions regarding the timid and safe behaviour of AVs could potentially result in undesirable human driver behaviours, for instance “testing” AVs or being aggressive towards them. Among other factors, morality has been determined as a source of aggressive driving behaviour. Following previous approaches on moral disengagement, the current paper argues that moral standards during interactions of human drivers with AVs could potentially blur, leading to the disengagement of self-regulation mechanisms of moral behaviour. The study investigates the impact of moral disengagement on the intention of human drivers to be aggressive towards AVs. To that end, an online survey was conducted including a newly developed survey of moral disengagement, adapted to the context of AVs. Moreover, measures of personality, driving style, attitudes towards sharing the road with AVs and perceived threats were collected. A confirmatory factor analysis provided support for the concept of moral disengagement in the context of AVs. Moreover, relationships between personality, driving style and attitudes towards sharing the road with AVs were found, via a structural equation modelling approach (SEM). The results could have implications in the future driver training and education programmes, as it might be necessary to not only focus on driving skills but also on the development of procedural skills that will improve the understanding of AVs’ capabilities and ensure safer interactions. Efforts on improving attitudes towards AVs may also be necessary for improving human driver behaviour.     

Two-step communication for the interaction between automated vehicles and pedestrians

An important challenge of automated vehicles (AV) will be the cooperative interaction with surrounding road users such as pedestrians. One solution to compensate for the missing driver-pedestrian interaction might be explicit communication via external human machine interfaces (eHMIs). Additionally, implicit communication such as a vehicle pitch motion might support AVs when interacting with pedestrians. While previous work explored various explicit and implicit communication cues, these concepts communicated the intention of the AV at one single time point. Currently, empirical findings on two-step communication lack so far. In this study, we empirically test the effect of a two-step AV communication that uses an implicit cue at a long distance and subsequently provides an implicit or explicit cues at a short distance. We compared its efficiency to single-step communication concepts providing implicit or explicit cues at the shorter distance only. To explore whether the right communication cue is used at the right distance, we analyzed pedestrians’ fixations while approaching an AV using an eye tracking device.We conducted a virtual reality study (N = 30) with AV communication concept that provided an active pitch motion or an eHMI and compared them with a two-step AV communication concept that provided an additional active pitch motion at a long distance when approaching the pedestrian. Furthermore, we recorded pedestrians’ fixation behavior while the AV approached.Consistently to previous work, single-step AV communication showed a beneficial effect on crossing behavior. Pedestrians initiated their crossing earlier while approaching an AV with an active pitch motion or an eHMI compared to the baseline condition. While active pitch motion reduced subjective safety feeling, eHMI increased it. However, the two-step communication concept did not further improve pedestrians’ crossing initiation times and their safety feeling. The pattern of fixation behavior differed as a function of AV distance. When the approaching AV was far away, pedestrians exclusively looked at the environment. During the approach, pedestrians gradually fixated the bumper and the hood and only then the windshield of the AV. Hence, it seems to be useful to present an AV intent communication at a certain distance from the pedestrian. These findings posit the importance of considering pedestrians’ fixation behavior when developing communication concepts between AVs and pedestrians.