A user’s prior experience with digital technologies predicts their success with a novel digital interface. Consequently, low technology prior experience can cause a potential user to be excluded from successfully navigating a user journey with a digital interface. The Engineering Design Centre’s exclusion calculator can predict the percentage of a population who will be unable to complete a task step in a user journey, but it does not explicitly take into account user exclusion due to insufficient technology prior experience. This paper develops the rationale for a proposed method for assessing the digital inclusivity of a digital interface user journey through evaluation of explicitness and digital interaction pattern familiarity.

This paper presents formative research to inform the design of intelligent automotive user interfaces. It describes an evaluation of dialogue-based interfaces, mediating the driver to take back control from the autonomous mode of a car. Four concepts designed to increase driver Situation Awareness were evaluated in a driving simulator. They used dialoguebased interaction, where driving-related information was either asked from or repeated by the driver, with the alternative of a countdown-based interface with no additional information. An inclusive set of participants, with a wide age spectrum, tested the interfaces. The shorter and simpler interaction of the countdown timer was most accepted. The interface seeking answers to driving-related questions came next, and the interface requiring repetition of driving-related information, even when augmented by visual and tactile cues, was least accepted. Design guidelines on utilizing dialogue as a means of keeping the driver in the loop during a takeover were thus derived.

Fully autonomous vehicles provide an opportunity to improve current transportation solutions; both for drivers and for people unable to drive. In this paper we present the preliminary results of a study aiming to understand user needs and expectations for autonomous vehicle interfaces. We found that users expect a different type of information to be fed back to them depending on whether the vehicles are privately owned or shared. The results of this study will be confirmed by further work and contribute to the development of a baseline fully autonomous vehicle user interface.

The automobile is becoming more complex as vehicle technologies advance. As a result, driver awareness of internal and external aspects of the environment will influence performance for a range of activities. Inclusivity is an important aspect of vehicle design, especially as autonomous driving functionality increases. This paper examines how users of differing gender and age perform within the vehicle. A simulator study was carried out to assess performance on a range of tasks, whilst driving under different driving conditions. The results show that differences exist between males and females, and older and younger operators for a range of driving and non-driving measures. Older operators generated higher steering wheel variation than younger drivers in driving-only conditions, whilst older and female operators require more button presses and glances away from the road than younger and male operators. The implications relating to in-vehicle interface design are discussed.

Autonomous vehicles could become an important part of the mobility solution for members of society previously excluded from driving. This paper presents the results of an interview study on users' needs and expectations of fully autonomous vehicles, and specifically on the inclusivity considerations that emerged. Six drivers and two individuals that are currently excluded from driving participated in this study. The main finding was that conventional multimodal interfaces would indeed enable a broader range of users to operate these vehicles. However, fundamental considerations such as the accessibility of displays and easy ingress/egress were of equal importance. We hope the emerging recommendations would form part of an inclusive set of user requirements to be taken into account by industry and academia when designing fully autonomous vehicle user interfaces.

This paper presents an analysis of user capability data using Topological Data Analysis (TDA) (unsupervised machine learning) to extract insight. The aim was to explore the global shape and sub-groupings (clusters of profiles) of people using data collected from the Cambridge Better Design Pilot Study of 362 people from across England and Wales. The resulting topological network demonstrated the global shape of the sample and distribution of sensory, cognitive and motor capability across the sample. The TDA network was automatically grouped into 14 distinct clusters, and distinguishing features of each cluster was extracted. The results demonstrate the value of applying TDA to analyse and visualise user capability data, and it is proposed that the cluster descriptions could be used for developing empirically based design tools such as personas for Inclusive Design.

The paper describes an iterative development process used to understand the suitability of different inclusive design evaluation tools applied into design practices. At the end of this process, a tool named Inclusive Design Advisor was developed, combining data related to design features of small appliances with ergonomic task demands, anthropometric data and exclusion data. When auditing a new design the tool examines the exclusion that each design feature can cause, followed by objective recommendations directly related to its features. Interactively, it allows designers or clients to balance design changes with the exclusion caused. It presents the type of information that enables designers and clients to discuss user needs and make more inclusive design decisions.

Fully autonomous vehicles can be classified as robots. In this paper we propose to approach the development of autonomous vehicle user interfaces from a human-robot interaction perspective, based on two principles. First, different robots require different user interfaces depending on their level of automation. Second, as the level of robot automation increases so should the automation of the interface itself; creating a spectrum ranging from a conventional “master-slave” level interaction to a fully intelligent “equal-footing” level interaction. Two research questions arise: where along the spectrum described above should autonomous vehicle user interfaces be, and what technological advance would have the greatest impact in enabling those interfaces. This paper presents the theoretical foundation of our research at the intersection of three previously unconnected fields: autonomous vehicles, human-robot interaction and affective computing. We then outline an experimental framework for developing a prototype interface based on our findings.

Despite a large literature on autonomous vehicles and a large number of relevant surveys examining public perception of self-driving vehicles, recent studies suggest that reported public perception is rapidly changing, volatile, and highly dependent on context and potential biases in reporting. In addition, some conclusions from very recent studies are supported: namely, that very little of the survey literature addresses key user centred design consideration that arise from inclusion of the wider population in the use of autonomous vehicles. We report initial studies that are intended to form part of a method currently under development that aims to bring together automotive design and Inclusive design; an analytical functional approach to design for user capability in the wider population. This paper describes the development stages of a user centred design capable methodology for sampling public opinion from a range of different qualitative studies. The finding are made available at two levels. Firstly, a general report on public perceptions’, examines key elements of sensitivity in responses to autonomous vehicle issues. Secondly, the methodology shows how to address in an unbiased way the specification and design a number of potential HMI concepts for managing takeover from car to driver in an autonomously capable vehicle in urban and highway usage cases.

High levels of Situation Awareness (SA) have been shown to improve performance of an operator in a complex environment. This paper describes an experimental study looking at whether increases in awareness of a non-driving related activity can improve performance in an automotive multitasking condition. 50 participants drove a low-fidelity driving simulator whilst attempting to carry out a number of alternative activities using an in-vehicle interface. The findings demonstrate that increased awareness of the non-driving interface delivers improvements in both driving and non-driving activities. Differences in the driving scenario itself were unable create a difference in perceived workload and SA of the driving activity. Objective measures were sensitive enough to demonstrate effects due to differences in both non-driving task experience and driving scenario under multitasking conditions.

Many industries have been transformed by the provision of service solutions characterised by personalisation and customisation - most dramatically the development of the iPhone. Personalisation and customisation stand to make an impact on cars and mobility in comparable ways. The automobile industry has a major role to play in this change, with moves towards electric vehicles, autonomous cars, and car sharing as a service. These developments are likely to bring disruptive changes to the business of car manufacturers as well as to drivers. However, in the automobile industry, both the user’s preferences and demands and also safety issues need to be confronted since the frequent use of different makes and models of cars, implied by car sharing, entails several risks due to variations in car controls depending on the manufacturer. Two constituencies, in particular, are likely to experience even more difficulties than they already do at present, namely older people and those with capability variations. To overcome these challenges, and as a means to empower a wide car user base, the paper here presents a basic concept of an intelligent driver profiling system for cars: the system would enable various car characteristics to be tailored according to individual driver-dependent profiles. It is intended that wherever possible the system will personalise the characteristics of individual car components; where this is not possible, however, an initial customisation will be performed.

Autonomous driving is a topic of extensive research; however user views on this new technology are largely unexplored, especially for an inclusive population. This paper presents a survey and two focus groups, investigating driving habits and attitudes towards autonomous cars of an inclusive group of UK drivers. A subset of survey participants were invited to attend one of two focus groups, to discuss handovers of control between car and driver. Maintaining safety, trust and control were themes commonly identified in both focus groups, while unique views and concerns, relating to different characteristics of the group were expressed. These results can inform an inclusive, user-centred design of autonomous vehicle interfaces, especially for the safety-critical use case of driver handovers of control.

An inclusive workplace environment should be comfortable and functional for all of its users. Over the past decade, workplace environments have changed to offer more flexible spaces in a variety of ways and locations. Modern office designs blend different working and social spaces, which include, for example, modular workstations, corridors, furniture, non-traditional layouts and open spaces. In this way, workplaces are designed to offer spaces for the effective collaboration of staff and to optimize work practices by promoting spontaneous and free-flowing communication. However, new design tendencies often lead to greater complications in moving around the workplace. Such complications may affect all workers, but they will mainly affect those with sight loss who experience extra difficulties in pursuing their target destination.

This paper presents a methodology for designing automotive user interfaces using Situation Awareness (SA). The development of interfaces providing users with relevant, timely information is critical for optimal performance. This paper presents a variation on the original SA model allowing for a consideration of all situational factors in a modern motor car. “Dual Goal SA” provides environmental and cognitive considerations for developing interfaces used when multi-tasking. A pilot study was carried out to test the Dual Goal concept and identify appropriate measures. Subjective results proved inconclusive. Objective results showed good evidence supporting the hypothesis but most promising was a factor analysis involving all key objective measures. This produced factors that classified the experimental groups consistently with predictions, demonstrating evidence of variations in performance consistent with variations in SA for two competing goals.

This paper looks at recent trends in automotive human machine interfaces, with a lens of evaluation from an inclusive design perspective. The goal of Inclusive Design is to ensure that the population of potential users for a product or service is maximised. Until relatively recently, automotive human machine interfaces (HMI’s) have excluded and caused difficulties for users due to visibility, reach and force required to operate controls. Over the last 15 or so years however, there has been a significant increase in control and display location, interface types and integration of functions, as well as dramatically increased potential functionality due to in-vehicle emergent technologies. It is suggested that this increase in interface unfamiliarity for a driver will cause significant difficulty and potential exclusion, due to the demands of learning and conflicts in expectation. The effects on this trend in the context of an ageing population and automated driving technologies are discussed.

Successful inclusive product design requires knowledge about the capabilities, needs and aspirations of potential users and should cater for the different scenarios in which people will use products, systems and services. This should include: the individual at home; in the workplace; for businesses, and for products in these contexts. It needs to reflect the development of theory, tools and techniques as research moves on.And it must also to draw in wider psychological, social, and economic considerations in order to gain a more accurate understanding of users' interactions with products and technology. However, recent research suggests that although a number of national disability surveys have been carried out, no such knowledge currently exists as information to support the design of products, systems and services for heterogeneous users. This paper outlines the strategy behind specific inclusive design research that is aimed at creating the foundations for measuring inclusion in product designs. A key outcome of this future research will be specifying and operationalising capability, and psychological, social and economic context measures for inclusive design. This paper proposes a framework for capturing such information, describes an early pilot study, and makes recommendations for better practice.

In the assessment of the inclusivity of products with interfaces for digital devices, there are difficulty and validity issues relating the cognitive demand of using and learning an unfamiliar interface to the capabilities outlined in the population source data. This is due to the disparity between the types of cognitive tasks used to create the source data, and those needed to operate a digital interface. Previous work to understand the factors affecting successful interactions with novel digital technology interfaces has shown that the user’s technology generation, technology prior experience and their motivation are significant. This paper suggests a method which would permit digital interfaces to be assessed for inclusivity by similarity to known interaction patterns. For a digital device interface task that contained a non-transparent or novel interaction pattern, then the resulting cognitive workload could also be assessed.

His paper illustrates the use of scenario writing and storyboard visualisation methods based on ethnographic study of diverse personas, narratives, and user experience to guide automotive engineers and designers for creating innovative ideas and developing inclusive Human Machine Interface (iHMI) concepts for future cars in 2025 and beyond. This paper documents the importance of continuing visual research process based on anthropological case studies that looked into diverse persona, cultural and geographical attributes. These methods are used to visually analyse situational car use, thereby leading to scenario-based HMI tasks that can be applied to generate innovative user oriented future car designs. Storyboard visualisation of narratives is a method that derives from ethnographic interviews with strategically chosen car users from around the world. This is a powerful tool for analyzing situations, describing feelings, and evaluating the usability of functions within the car. With this visual process, future scenarios can be drawn in order to create new and inclusive HMI ideas and design concepts embedded within the storyboards to help engineers and designers’ to understand users’ different needs, exploring their expectations, emotions and motivations. The realistic details on the character illustrations of each persona are essential for better understanding of the users’ including older people, the visually impaired and wheelchair users, child and parent, technophobic or technophile persons. Each HMI concept can be sketched as required in task sequences, with detail and scaled paper model produced for detailed step-by-step design. The required interactions can be observed, photographed and captured on video for in-depth design thinking workshops. A series of HMI working design concepts for future cars will emerge from this pipeline for prototyping and engineering.

Interface design is often constrained by the limited scope and resource-intensive nature of conventional user studies. We aim to unburden this process by introducing an automated user modelling framework that continuously injects design guidelines into the development process. We present a pipeline that converts a given user interface design into a widgetised data structure, executes a performance simulation based on the cognitive model of a user, and analyses its output to give design guidelines. We introduce the research methodology employed to create the model, implementation details of the model, and initial results from its validation. These include the dynamics of age-based modelling, the temporal integrity of the output of the cognitive model, and indications of the accuracy of the overall design guidelines produced.