Subliminal priming of motivational orientation in educational settings: Effect on academic performance moderated by mindfulness

Recent literature indicates that a motivational orientation can be unconsciously primed. This study examined whether motivational priming influences students’ academic performance within an educational setting and whether this effect is moderated by students’ degree of mindfulness. Two randomly assigned groups of students received an identical lesson. However, the teacher’s slideshow contained different subliminal words according to the condition (autonomous vs. controlled motivation). Results demonstrated an interaction between students’ dispositional mindfulness and priming conditions. The more mindful students were immune to the manipulation whereas the less mindful students were affected by the priming: those primed with autonomous motivation obtained better results than those primed with controlled motivation. These findings contribute to priming research specifying individual differences of priming responsiveness.     

Driving without the brain? Effects of value predispositions,media attention,and science knowledge on public willingness to use driverless cars in Singapore

This study employs the cognitive miser model and science literacy model as theoretical frameworks to investigate motivations behind public willingness to use driverless cars in Singapore. Findings from a large-scale survey of 1,006 adult Singaporeans indicate that public willingness to use driverless cars was strongly related to value predispositions, especially affect. Aside from having a direct relationship with willingness to use driverless cars, this study found that affect also had an indirect relationship with willingness to use driverless cars via benefit perceptions. Meanwhile, findings failed to reveal significant relationships between two types of science knowledge and willingness to use driverless cars. The findings shed light on the current public opinion on driverless cars in Singapore and lend support to the cognitive miser model over the scientific literacy model. Theoretical and practical implications are discussed.     

User acceptance of automated public transport: Valence of an autonomous minibus experience

Autonomous driving is receiving increasing attention in the automotive industry as well as in public transport. However, it is still unclear whether users are willing to use automated public transportation at all. In order to answer this and other questions, the transport company of the city of Mainz, Germany, tested the autonomous minibus EMMA (Elektro-Mobilität Mainz Autonom) on a 600-meter-long test track in public space. The study presented here was conducted with the aim of exploring crucial determinants for the use of an autonomous minibus. On the basis of established acceptance models, a questionnaire was developed, which was completed in a field survey by a total of 942 participants before or after their journey with the minibus. Autonomous vehicles in public transport in general and the minibus in particular were evaluated positively by the majority of respondents. Above all, participants judged safety and environmental friendliness of the minibus as important. Participants who completed the questionnaire after their first trip with EMMA provided higher ratings of acceptance than those who had not travelled on the bus. Performance expectancy was the most important predictor for both acceptance of automated public transport in general and acceptance of the minibus EMMA. However, the experienced valence of the ride, in terms of how pleasant or unpleasant passengers experienced the first trip with the minibus, also affected acceptance of the minibus. This suggests a role of valence on intention-to-use, which has hardly been considered in previous theories and studies.     

Examining human attitudes toward shared mobility options and autonomous vehicles

This paper presents a comprehensive analysis of people’s attitudes toward shared mobility options and autonomous vehicles (AVs), with a focus on the underlying patterns and potential determinants. A stated preference (SP) survey was designed and implemented in the U.S. Four sets of questions were included in the questionnaire, each focused on one unique aspect of user attitudes, including a) preferences for mobility options and lifestyle (such as overall view of driving, factors in mode choice decisions and technology engagement), b) perceived benefits and concerns of shared mobility option, c) reasons toward or against private vehicle ownership, and d) motivations for and desired features of AVs. A structural equations model was developed to identify latent attitudinal factors and examine the correlations between the latent attitudes (as the endogenous variables) and the observed covariates (including the socio-economic and demographic characteristics, and users’ current mobility profile, such as mode use frequency, travel distance, and trip fare). The model identified eleven latent factors that represent various aspects of attitudes toward AVs and shared mobility options. The findings could be used by policymakers and Transportation Network Companies (TNCs) to a) recognize the users’ latent attitudes, b) understand the underlying patterns of attitudes, c) implement plans and policies more efficiently, d) guide or influence users’ perceptions, and e) enhance travel behavior models. This study lays the foundation for further analysis on understanding user acceptance and adoption of these emerging mobility options, which is essential to estimate the likelihood and magnitude of behavior shifts in the era of automated, connected and shared mobility.     

Assessing the feasibility of the theory of planned behaviour in predicting drivers’ intentions to operate conditional and full automated vehicles

Guided by the Theory of Planned Behaviour (TPB), this study examined the beliefs underpinning, and feasibility of the factors in predicting, individuals’ intentions to use a conditional (Level 3) automated vehicle (AV) and a full (Level 5) AV. Australian drivers (N = 505) aged 17–81 years (Mean age = 33.69, SD = 18.79) were recruited and completed a 20 min online survey which featured both quantitative and qualitative items. For the quantitative data, two linear regressions revealed that the TPB standard constructs of attitudes, subjective norm, and perceived behavioural control (PBC) accounted for 66% of the variance in intentions to use a conditional AV and 68% of the variance in intentions to use a full AV. Of the TPB constructs, attitudes and subjective norms were significant positive predictors of future intentions to use conditional and full AVs. For the qualitative data, some differences emerged for the underlying behavioural beliefs that underpinned intentions to use conditional and full AVs. For example, having beliefs about control over the conditional AV was identified by many participants as an advantage, while not being in full control of the full AV was identified as a disadvantage. For underlying control beliefs, participants identified similar barriers for both vehicle types, including; high costs, lack of trust, lack of control over the vehicle, lack of current legislation to support the mainstream introduction of these vehicles, and concerns of safety for self and for other road users when operating AVs. Overall, these findings provide some support for applying the TPB to understand drivers’ intended use of AVs. However, while the current study showed that the constructs of attitudes and subjective norms might reflect intended use of AVs, more research is required to further examine the role of PBC. Additionally, the findings provide initial insights into the underlying behavioural and control beliefs that may motivate drivers to use AVs and highlight the similarities and differences in drivers’ perceptions towards two levels of vehicle automation.     

Safe and optimal navigation for autonomous multi-rotor aerial vehicle in a dynamic known environment by a decomposition-coordination method

In this paper, we present a new solution for the Autonomous navigation problem, using a Decomposition-Coordination Method (DCM) 1. The main purpose of this work is to compute an optimal and safe path for the multi-rotor Unmanned Aerial Vehicle (UAV) in a dynamic environment, moving from an initial location to the desired state. We assume that the flight environment is totally known to a supervisory unit, and the positions and trajectories of dynamic obstacles could be known in real-time, thus to perform in such environment a high reactivity is required as well as good connectivity with the supervisory unit that provides the safe path, each time one obstacle or more are detected on the road, so that the UAV could autonomously diverts from the unsafe path to the new safe one, and avoid the potential collisions. First and foremost, we choose a generalized nonlinear model for the multi-rotors in view of the rotational and translational dynamics of the UAV. We then associate that model with the objective functions. After that, we proceed to the resolution of the multi-objective optimization problem using our approach of decomposition-coordination. The principle of this method consists in decomposing the system into several smaller subsystems to simplify the treatment. Then we achieve the coordination afterward using Lagrange multipliers. To prove the convergence and stability of our method we make use of a Lyapunov function chosen particularly for this system. In the last section we present the simulation results, to confirm the reliability of our method.     

Approach-achievement goals and motivational context on psycho-physiological functioning and performance among novice basketball players

ObjectivesDrawing from an integrated motivational model (Vansteenkiste, Lens, Elliot, Soenens, & Mouratidis, 2014), this study tested the impact of induced approach-based achievement goal states under different motivational contexts on the psycho-physiological functioning and motor task performance of novice basketball players.DesignA 3 × 2 (Goal [task-/self-/other-approach] x Context [autonomy-supportive/controlling]) repeated measures experimental design was employed.Method114 novice participants (M_age = 23.53; SD = 4.56) performed a basketball shooting task. They were subsequently randomly assigned to one of six experimental conditions before repeating this task. Physiological (heart rate [HR] and blood pressure [BP]) and psychological (stress appraisals, state anxiety, task enjoyment, perceived competence, and goal attainment) data were captured at different intervals throughout the experiment.ResultsFactorial ANOVAs revealed participants: 1) performing under a controlling motivational context reported significantly higher HR (p < .001) and systolic BP (p < .05) post-task compared to those operating within an autonomy-supportive environment, 2) induced to an other-approach goal group, recorded significantly higher diastolic BP (p < .05) than those induced to self- and task-approach goals post-task, 3) adopting a task-approach goal under controlling conditions appraised the shooting task as significantly more threatening (p < .05) than their counterparts in the task-approach autonomy-supportive condition, and finally, 4) following approach-based goals under an autonomy-supportive context significantly improved their performance (p < .001) from pre-to post-shooting task.ConclusionsOur findings provide limited support for an integrated motivational model and are discussed in relation to their unique theoretical and practical utility.     

The plausibility of using unmanned aerial vehicles as a serious game for dealing with attention deficit-hyperactivity disorder

Attention Deficit-Hyperactivity Disorder (ADHD) is considered a mental disease that affects an estimated 5% of the world’s youth population. Brain-Computer Interfaces (BCIs) such as Electroencephalograms (EEGs) and functional Magnetic Resonance Imaging (fMRI) have been used to study and treat this mental disease. This paper shows the plausibility of using Unmanned Aerial Vehicles (UAVs) as a serious game for therapeutic purposes through a systematic review of the current state of UAVs and how they have been coupled to BCIs in order to control them through mental commands. Also, challenges and research opportunities from a usability approach related to the game design, interaction design, and cognitive rehabilitation are identified and described. We hope that the research opportunities identified in this paper can be useful to guide future research and gain insight into how to solve challenges related to the use of Unmanned Aerial Vehicles in cognitive therapies.     

Interaction between pedestrians and automated vehicles: A Wizard of Oz experiment

Automated vehicles (AVs) will be introduced on public roads in the future, meaning that traditional vehicles and AVs will be sharing the urban space. There is currently little knowledge about the interaction between pedestrians and AVs from the point of view of the pedestrian in a real-life environment. Pedestrians may not know with which type of vehicle they are interacting, potentially leading to stress and altered crossing decisions. For example, pedestrians may show elevated stress and conservative crossing behavior when the AV driver does not make eye contact and performs a non-driving task instead. It is also possible that pedestrians assume that an AV would always yield (leading to short critical gaps). This study aimed to determine pedestrians’ crossing decisions when interacting with an AV as compared to when interacting with a traditional vehicle. We performed a study on a closed road section where participants (N = 24) encountered a Wizard of Oz AV and a traditional vehicle in a within-subject design. In the Wizard of Oz setup, a fake ‘driver’ sat on the driver seat while the vehicle was driven by the passenger by means of a joystick. Twenty scenarios were studied regarding vehicle conditions (traditional vehicle, ‘driver’ reading a newspaper, inattentive driver in a vehicle with “self-driving” sign on the roof, inattentive driver in a vehicle with “self-driving” signs on the hood and door, attentive driver), vehicle behavior (stopping vs. not stopping), and approach direction (left vs. right). Participants experienced each scenario once, in a randomized order. This allowed assessing the behavior of participants when interacting with AVs for the first time (no previous training or experience). Post-experiment interviews showed that about half of the participants thought that the vehicle was (sometimes) driven automatically. Measurements of the participants’ critical gap (i.e., the gap below which the participant will not attempt to begin crossing the street) and self-reported level of stress showed no statistically significant differences between the vehicle conditions. However, results from a post-experiment questionnaire indicated that most participants did perceive differences in vehicle appearance, and reported to have been influenced by these features. Future research could adopt more fine-grained behavioral measures, such as eye tracking, to determine how pedestrians react to AVs. Furthermore, we recommend examining the effectiveness of dynamic AV-to-pedestrian communication, such as artificial lights and gestures.