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).     

Toward integrating cognitive components with computational models of emotion using software design patterns

Computational models of emotion (CMEs) are software systems designed to imitate particular aspects of human emotions. The main purpose of this type of computational model is to capture the complexity of the human emotion process in a software system that is incorporated into a cognitive agent architecture. However, creating a CME that closely imitates the actual functioning of emotions demands to address some challenges such as (i) sharing information among independently developed cognitive and affective components, and (ii) interconnecting complex cognitive and affective components that must interact with one another in order to generate realistic emotions, which may even affect agents’ decision making. This paper proposes an architectural pattern aimed at cataloging and describing fundamental components of CMEs and their interrelationships with cognitive components. In this architectural pattern, external cognitive components and internal affective components of CMEs do not interact directly but are extended by including message exchange methods in order to use a publish-subscribe channel, which enables their intercommunication, thus attenuating issues such as software heterogeneity. This structural approach centralizes communication management and separates the inherent complexity of the cognitive and affective processes from the complexity of their interaction mechanisms. In so doing, it enables the design of CMEs’ architectures composed of independently developed affective and cognitive components. The proposed architectural pattern attempts to make progress in capturing the complex process of human emotions in a software system that adheres to software engineering best practices and that incorporates quality attributes such as flexibility and interoperability.     

An adaptive network model for pain and pleasure through spicy food and its desensitization

This paper aims to map out the adaptive causal pathways of processes underlying capsaicin consumption and the desensitization process of the TRPV1 receptor as a feedback loop together with pain and pleasure perception. In order to map out these causal capsaicin pathways, adaptive causal network modeling was applied, which is a way of modeling biological, neural, mental and social processes from an adaptive causal modeling perspective.     

On the dynamics and adaptivity of mental processes: Relating adaptive dynamical systems and self-modeling network models by mathematical analysis

In this paper, it is addressed by mathematical analysis how network-oriented modeling relates to the dynamical systems perspective on mental processes. It has been mathematically proven that any dynamical system can be modeled as a temporal-causal network model and that any adaptive dynamical system (of any order) can be modeled by a self-modeling network (of the same order).     

Bio-inspired cognitive model of motor learning by imitation

Learning, and even more so by imitation, is an essential Cognitive Functions because it is carried out throughout life and allows us to adapt our behaviors from other beings through observation. In this work, we propose a model, and implementation of the cognitive function of imitation motor learning (IML), based on psychological and neuroscientific evidence. According to the evidence, learning by imitation includes imitation of action and imitation of action over an object sub-processes. The imitation of action consists of the movement of the limbs. The imitation of action over an object consists of the interaction with an object within the environment. We achieve an implementation of the proposed model for IML and endow a virtual entity with it. In order to validate the proposal, we use a case study to analyze the sub-processes performance. From results, we conclude that both imitation of action and imitation of action over an object sub-processes play an essential role in getting the agent to interact with stimuli within the environment.     

The right man in the right place? Substitutions and goal-scoring in soccer

ObjectivesWe investigate how the goal-scoring probability in international club soccer evolves after player substitutions.DesignTo this end, we analyse rich data concerning 2,025 recent soccer games played in the two most prestigious club soccer competitions, i.e. the UEFA Champions League and the UEFA Europa League.MethodAs first in the literature, we control for within-game dynamics by applying a minute-by-minute bivariate probit approach.Results/ConclusionsWe find that teams experience increased goal-scoring probabilities after their first and second substitution and a decreased probability of scoring after the three substitutions made by their opponent. This association is less distinct during the first 3 mins after the substitution, which is consistent with difficulties to adapt to (i) the game intensity by the substitute player or (ii) tactical changes by the entire team. Furthermore, we find that the change in the goal-scoring probability is substantially bigger if the team is losing at the moment of the substitution.     

A dual-process model of affective and instrumental attitudes in predicting physical activity

IntroductionA novel dual-process model based upon the affective-reflective theory which distinguishes between affective attitude and instrumental attitude at an explicit and implicit level was used to predict physical activity.MethodUndergraduate students (N = 114) completed a lab-based study at two time-points, spaced two weeks apart. Participants completed self-report measures of the theory of planned behavior constructs, including explicit affective attitude and explicit instrumental attitude. Implicit affective attitude and implicit instrumental attitude were measured using single category implicit association tests.ResultsExplicit affective attitude and perceived behavioral control indirectly predicted physical activity through intention, and explicit affective attitude, implicit affective attitude, and intention predicted physical activity directly with a modest effect size (R² = 0.24).DiscussionFindings suggest explicitly and implicitly held evaluative information are conceptually distinct, and affective evaluations are key in guiding physical activity behavior regardless of whether such evaluations are implicit or consciously accessible.     

When the final whistle blows: Social identity pathways support mental health and life satisfaction after retirement from competitive sport

For many athletes, retirement from higher levels of competitive sport poses significant challenges. Research has shown that athletic identity is a key predictor of adjustment trajectories, but the mechanisms through which this affects outcomes are less clear. Added to this, there has been limited research on the role that wider social identities, and the resources they enable, play in adjustment. Addressing both these issues, we examined theoretically derived social identity pathways to retirement adjustment in athletes who had played sport at higher competitive levels and two potential mechanisms, or psychological resources, through which adjustment might be enabled. This was examined in two samples: retired athletes from countries in Western (n = 215) and Eastern (n = 183) regions. Loss of athletic identity, social group memberships (multiple, maintained and new), psychological resources (perceived meaning in life and control), and adjustment (life satisfaction, depression, and perceived physical health) were assessed. In both samples, the loss of athletic identity undermined adjustment by reducing meaning in life and perceived control. Path analysis showed that both maintained and gained social group memberships counteracted the negative effects of athletic identity loss on adjustment. Evidence that these pathways enabled access to psychological resources was found primarily in Chinese athletes, with maintained groups influencing personal control and new groups influencing meaning in life. These findings highlight the importance of social identity processes to retirement from higher levels of competitive sport and the mechanisms through which they can either support or undermine adjustment.     

The Factors that Motivate Law Enforcement's Use of Force: A Systematic Review

Media attention relevant to law enforcement use of force in the last decade finally alerted the scientific community to the need for more research regarding law enforcement discretion and decision making. The purpose of this study was to synthesize the existing literature to explore the motivating factors for law enforcement use of force. This study will utilize a social–ecological framework to systematically examine factors that impact officer decisions to use force at the individual and community levels. The paper includes recommendations for research and practice through an equity lens that highlights the disparate use of force against men of color in particular. Interventions, trainings, education, and research to stop the promotion of perceived safety over justice will be highlighted.