Ecological interface design effectively reduces cognitive workload – The example of HMIs for speed control

This paper aims to demonstrate that ecological interface design reduces the use of cognitive resources. Making the boundaries of acceptable performance visually perceivable should elicit skill-based behavior, thus lowering the cognitive load. To illustrate the psychological mechanisms of ecological interface design and validate its influence on cognitive load, we compared a conventional speedometer to an ecological speedometer. Both interfaces were displayed on the head-up display of a static driving simulator and were tested in a rural highway scenario. In a 2 × 2 × 2 repeated-measure design, the human–machine interface was tested along with the informative intelligent speed assistance system (representing an existing alternative for speed control) and the additional workload induced by a 1-back task (representing cognitively demanding driving situations). To measure cognitive load, we used a tactile version of the detection response task and controlled for all confounding variables. The experiment was conducted with 28 male and 21 female drivers. Our hypotheses and the ecological interface design theory are supported by the finding that the ecological speedometer reduces the use of cognitive resources. Moreover, the specific application of the ecological speedometer enables better driving performance (i.e., longitudinal and lateral control) compared to a conventional speedometer.     

Modélisation pour un environnement multimédia de l'apprentissage individualisé de la lecture

The aim of our research project is to study what contribution the new technologies can bring to teaching and learning. So, we have chosen a pluridiciplinary approach, combining the exploration of computer potentialities with the integration of research studies about the learning application. The application is a tutor module of AMICAL project (Architecture Multi-agent Interactive Compagnon pour l'Apprentissage de la Lecture). The issue is to determine and to explain the knowledge at work in a teaching process. To begin with, we shall explain the different decision-making processes, which characterize the teaching act. In a second part, we shall describe the processes of knowledge determination and modelling.     

A cognitively enhanced collaborative control architecture for an intelligent wheelchair: Formalization,implementation and evaluation

For people with mobility impairment, powered wheelchairs are able to extend independent transportation. However, most users find it difficult to operate the powered wheelchairs effectively. This can be due to variety of physical or cognitive impairments. Herein lies the motivation of developing intelligent wheelchairs that provide the user, assistance in control and navigation as and when required, supporting retention of residual skills. For better Human-Robot Interaction, such intelligent wheelchairs need to be cognitively enhanced. This paper propose a Cognitive Collaborative Architecture (CCA) for an intelligent wheelchair which is designed to assist the user as a team member. Whenever user finds it difficult to drive or control the wheelchair, CCA transfers control to the robotic agent which continues the human navigation strategy providing ‘assistance-as-required’.     

‘Journey in the world of professions and work’: A career intervention for children

A structured ten-unit training was devised to stimulate some career adaptability resources such as optimism and hope toward the future, curiosity, career exploration, and occupational knowledge in children. Ten classes, for a total of 154 children (79 boys and 75 girls) with a mean age of 10.65 years (SD = 1.24), were randomly assigned to either the experimental, who was the focus of the intervention, or control group. At post-test the experimental group held significantly more hope, optimism, curiosity, career exploration, occupational knowledge, information, planning, and time perspective than the control group. The pattern of effect sizes strengthens the idea that the training enhanced experimental participants’ some career adaptability resources.     

A conceptual framework for establishing trust in real world intelligent systems

Intelligent information systems that contain emergent elements often encounter trust problems because results do not get sufficiently explained and the procedure itself can not be fully retraced. This is caused by a control flow depending either on stochastic elements or on the structure and relevance of the input data. Trust in such algorithms can be established by letting users interact with the system so that they can explore results and find patterns that can be compared with their expected solution. Reflecting features and patterns of human understanding of a domain against algorithmic results can create awareness of such patterns and may increase the trust that a user has in the solution. If expectations are not met, close inspection can be used to decide whether a solution conforms to the expectations or whether it goes beyond the expected. By either accepting or rejecting a solution, the user’s set of expectations evolves and a learning process for the users is established. In this paper we present a conceptual framework that reflects and supports this process. The framework is the result of an analysis of two exemplary case studies from two different disciplines with information systems that assist experts in their complex tasks.     

The electric vehicle: A new driving experience involving specific skills and rules

The arrival of the electric vehicle (EV) on the market is one consequence of government measures to improve air quality and reduce CO² emissions. However, the EV has specific properties of use associated with its limited range and relative silence compared to normal vehicles, influencing the mobility behaviours of drivers and requiring them to develop some new driving abilities. This paper examines the behavioural modifications brought about by daily use of an electric vehicle at three different levels of driving activity: strategic, tactical and operational. The study collected and analyzed the self-reported behaviours (via questionnaires and travels dairies) of 36 Parisian private drivers, each of whom drove for six months an electric MINI E prototype. The results of the study show that driving an EV requires a learning phase to acquire the skills and knowledge necessary to operate the vehicle. At the strategic level of driving, drivers take into account the restricted range of the EV, implement a daily charge process, and develop new behaviours related to trip planning. The study also examines driver behaviour at the tactical level, in terms of driver interactions with other road users to deal with the silent nature of the EV, and at the operational level of driving, in terms of braking behaviour to master the regenerative braking function of the EV. The paper discusses the interactions between these three levels of driving activity.     

The impact of auditory continual feedback on take-overs in Level 3 automated vehicles

ObjectiveTo implement auditory continual feedback into the interface design of a Level 3 automated vehicle and to test whether gaze behavior and reaction times of drivers improved in take-over situations.BackgroundWhen required to assume manual control in take-over situations, drivers of Level 3 automated vehicles are less likely than conventional drivers to spot potential hazards, and their reaction time is longer. Therefore, it is crucial that the interface of Level 3 automated vehicles will be designed to improve drivers’ performance in take-over situations.MethodIn two experiments, participants drove a simulated route in a Level 3 automated vehicle for 35 min with one imminent take-over event. Participants’ gaze behavior and performance in an imminent take-over event were monitored under one of three auditory interface designs: (1) Continual feedback. A system that provides verbal driving-related feedback; (2) Persistent feedback. A system that provides verbal driving-related feedback and a persistent beep; and (3) Chatter feedback. A system that provides verbal non-driving-related feedback. Also, there was a control group without feedback.ResultsUnder all three auditory feedback designs, the number of drivers' on-road glances increased compared to no feedback, but none of the designs shortened reaction time to the imminent event.ConclusionIncreasing the number of on-road glances during automated driving does not necessarily improve drivers’ attention to the road and their reaction times during take-overs.ApplicationPossible implications for the effectiveness of auditory continual feedback should be considered when designing interfaces for Level 3 automated vehicles.     

The pattern theory of self in artificial general intelligence: A theoretical framework for modeling self in biologically inspired cognitive architectures

In an attempt to provide a unified account for a vast literature discussing a multiplicity of selves, Gallagher (2013) has proposed a pattern theory of self. Subsequent discussion on this account has led to a concern that the pattern theory, as originally presented, stands as a mere list of aspects that fails to explain how they are related in real-time. We suggest that one way to address these criticisms, and further develop the pattern theory of self is by exploring how it can be used to aid research on self in artificial general intelligence, especially in the context of biologically inspired cognitive architectures. We furthermore propose a conceptual implementation for actualizing such research in regards to the LIDA (Learning Intelligent Decision Agent) cognitive model.     

A neural cognitive architecture

It is difficult to study the mind, but cognitive architectures are one tool. As the mind emerges from the behaviour of the brain, neuropsychological methods are another method to study the mind, though a rather indirect method. A cognitive architecture that is implemented in spiking neurons is a method of studying the mind that can use neuropsychological evidence directly. A neural cognitive architecture, based on rule based systems and associative memory, can be readily implemented, and would provide a good bridge between standard cognitive architectures, such as Soar, and neuropsychology. This architecture could be implemented in spiking neurons, and made available via the Human Brain Project, which provides a good collaborative environment. The architecture could be readily extended to use spiking neurons for subsystems, such as spatial reasoning, and could evolve over time toward a complete architecture. The theory behind this architecture could evolve over time. Simplifying assumptions, made explicit, such as those behind the rule based system, could gradually be replaced by more neuropsychologically accurate behaviour. The overall task of collaborative architecture development would be eased by direct evidence of the actual neural cognitive architectures in human brains. While the initial architecture is biologically inspired, the ultimate goal is a biological cognitive architecture.