Ecological IVIS design : using EID to develop a novel in-vehicle information system

New in-vehicle information systems (IVIS) are emerging which purport to encourage more environment friendly or ‘green’ driving. Meanwhile, wider concerns about road safety and in-car distractions remain. The ‘Foot-LITE’ project is an effort to balance these issues, aimed at achieving safer and greener driving through real-time driving information, presented via an in-vehicle interface which facilitates the desired behaviours while avoiding negative consequences. One way of achieving this is to use ecological interface design (EID) techniques. This article presents part of the formative human-centred design process for developing the in-car display through a series of rapid prototyping studies comparing EID against conventional interface design principles. We focus primarily on the visual display, although some development of an ecological auditory display is also presented. The results of feedback from potential users as well as subject matter experts are discussed with respect to implications for future interface design in this field

Exploring the usability of a connected autonomous vehicle human machine interface designed for older adults

Users of Level 4–5 connected autonomous vehicles (CAVs) should not need to intervene with the dynamic driving task or monitor the driving environment, as the system will handle all driving functions. CAV human-machine interface (HMI) dashboards for such CAVs should therefore offer features to support user situation awareness (SA) and provide additional functionality that would not be practical within non-autonomous vehicles. Though, the exact features and functions, as well as their usability, might differ depending on factors such as user needs and context of use. The current paper presents findings from a simulator trial conducted to test the usability of a prototype CAV HMI designed for older adults and/or individuals with sensory and/or physical impairments: populations that will benefit enormously from the mobility afforded by CAVs. The HMI was developed to suit needs and requirements of this demographic based upon an extensive review of HMI and HCI principles focused on accessibility, usability and functionality [1, 2], as well as studies with target users. Thirty-one 50-88-year-olds (M 67.52, three 50–59) participated in the study. They experienced four seven-minute simulated journeys, involving inner and outer urban settings with mixed speed-limits and were encouraged to explore the HMI during journeys and interact with features, including a real-time map display, vehicle status, emergency stop, and arrival time. Measures were taken pre-, during- and post- journeys. Key was the System Usability Scale [3] and measures of SA, task load, and trust in computers and automation. As predicted, SA decreased with journey experience and although cognitive load did not, there were consistent negative correlations. System usability was also related to trust in technology but not trust in automation or attitudes towards computers. Overall, the findings are important for those designing, developing and testing CAV HMIs for older adults and individuals with sensory and/or physical impairments

On the Mental Workload Assessment of Uplift Mapping Representations in Linked Data

Self-reporting procedures have been largely employed in literature to measure the mental workload experienced by users when executing a specific task. This research proposes the adoption of these mental workload assessment techniques to the task of creating uplift mappings in Linked Data. A user study has been performed to compare the mental workload of “manually” creating such mappings, using a formal mapping language and a text editor, to the use of a visual representation, based on the block metaphor, that generate these mappings. Two subjective mental workload instruments, namely the NASA Task Load Index and the Workload Profile, were applied in this study. Preliminary results show the reliability of these instruments in measuring the perceived mental workload for the task of creating uplift mappings. Results also indicate that participants using the visual representation achieved smaller and more consistent scores of mental workload

Supporting dynamic change detection: using the right tool for the task

Detecting task-relevant changes in a visual scene is necessary for successfully monitoring and managing dynamic command and control situations. Change blindness—the failure to notice visual changes—is an important source of human error. Change History EXplicit (CHEX) is a tool developed to aid change detection and maintain situation awareness; and in the current study we test the generality of its ability to facilitate the detection of changes when this subtask is embedded within a broader dynamic decision-making task. A multitasking air-warfare simulation required participants to perform radar-based subtasks, for which change detection was a necessary aspect of the higher-order goal of protecting one’s own ship. In this task, however, CHEX rendered the operator even more vulnerable to attentional failures in change detection and increased perceived workload. Such support was only effective when participants performed a change detection task without concurrent subtasks. Results are interpreted in terms of the NSEEV model of attention behavior (Steelman, McCarley, & Wickens, Hum. Factors 53:142–153, 2011; J. Exp. Psychol. Appl. 19:403–419, 2013), and suggest that decision aids for use in multitasking contexts must be designed to fit within the available workload capacity of the user so that they may truly augment cognition

Maritime Navigation: Characterizing Collaboration in a High-Speed Craft Navigation Activity

acceptedVersio

The design-by-adaptation approach to universal access: learning from videogame technology

This paper proposes an alternative approach to the design of universally accessible interfaces to that provided by formal design frameworks applied ab initio to the development of new software. This approach, design-byadaptation, involves the transfer of interface technology and/or design principles from one application domain to another, in situations where the recipient domain is similar to the host domain in terms of modelled systems, tasks and users. Using the example of interaction in 3D virtual environments, the paper explores how principles underlying the design of videogame interfaces may be applied to a broad family of visualization and analysis software which handles geographical data (virtual geographic environments, or VGEs). One of the motivations behind the current study is that VGE technology lags some way behind videogame technology in the modelling of 3D environments, and has a less-developed track record in providing the variety of interaction methods needed to undertake varied tasks in 3D virtual worlds by users with varied levels of experience. The current analysis extracted a set of interaction principles from videogames which were used to devise a set of 3D task interfaces that have been implemented in a prototype VGE for formal evaluation

Analysing the Impact of Machine Learning to Model Subjective Mental Workload: A Case Study in Third-Level Education

Mental workload measurement is a complex multidisciplinary research area that includes both the theoretical and practical development of models. These models are aimed at aggregating those factors, believed to shape mental workload, and their interaction, for the purpose of human performance prediction. In the literature, models are mainly theory-driven: their distinct development has been influenced by the beliefs and intuitions of individual scholars in the disciplines of Psychology and Human Factors. This work presents a novel research that aims at reversing this tendency. Specifically, it employs a selection of learning techniques, borrowed from machine learning, to induce models of mental workload from data, with no theoretical assumption or hypothesis. These models are subsequently compared against two well-known subjective measures of mental workload, namely the NASA Task Load Index and the Workload Profile. Findings show how these data-driven models are convergently valid and can explain overall perception of mental workload with a lower error

Predictive feedback control and Fitts' law

Fitts’ law is a well established empirical formula, known for encapsulating the “speed-accuracy trade-off”. For discrete, manual movements from a starting location to a target, Fitts’ law relates movement duration to the distance moved and target size. The widespread empirical success of the formula is suggestive of underlying principles of human movement control. There have been previous attempts to relate Fitts’ law to engineering-type control hypotheses and it has been shown that the law is exactly consistent with the closed-loop step-response of a time-delayed, first-order system. Assuming only the operation of closed-loop feedback, either continuous or intermittent, this paper asks whether such feedback should be predictive or not predictive to be consistent with Fitts law. Since Fitts’ law is equivalent to a time delay separated from a first-order system, known control theory implies that the controller must be predictive. A predictive controller moves the time-delay outside the feedback loop such that the closed-loop response can be separated into a time delay and rational function whereas a non- predictive controller retains a state delay within feedback loop which is not consistent with Fitts’ law. Using sufficient parameters, a high-order non-predictive controller could approximately reproduce Fitts’ law. However, such high-order, “non-parametric” controllers are essentially empirical in nature, without physical meaning, and therefore are conceptually inferior to the predictive controller. It is a new insight that using closed-loop feedback, prediction is required to physically explain Fitts’ law. The implication is that prediction is an inherent part of the “speed-accuracy trade-off”

Shared Spatial Situation Awareness as a Team Performance Indicator in Collaborative Spatial Orientation Task

International audienceThe present study investigates the link between time taken by a team to perform a spatial orientation task and the evaluation of spatial shared situational awareness (SSA). Paired in teams, volunteers have to collaborate to send a vehicle to a specific location on a computer simulation as quickly as they can. The roles and information they have to reach that goal are different. Every 45 seconds participants are asked to mark on their map the location they believe the vehicle to be. Along with its real position, these marks are used to objectively evaluate spatial SSA. First results allow us to divide participants into three groups in accordance with Endsley's distinction of Shared SA evaluation. Interestingly, fastest teams were not the ones with the most accurate and shared spatial representation of the situation. Potential use of such indicators in team training is outlined