Investigating older adults’ preferences for functions within a human-machine interface designed for fully autonomous vehicles

© Springer International Publishing AG, part of Springer Nature 2018. Compared to traditional cars, where the driver has most of their attention allocated on the road and on driving tasks, in fully autonomous vehicles it is likely that the user would not need to intervene with driving related functions meaning that there will be little need for HMIs to have features and functionality relating to these factors. However, there will be an opportunity for a range of other interactions with the user. As such, designers and researchers need to have an understanding of what is actually needed or expected and how to balance the type of functionality they make available. Also, in HMI design, the design principles need to be considered in relation to a range of user characteristics, such as age, and sensory, cognitive and physical ability and other impairments. In this study, we proposed an HMI specially designed for connected autonomous vehicles with a focus on older adults. We examined older adults’ preferences of CAV HMI functions, and, the degree to which individual differences (e.g., personality, attitude towards computers, trust in technology, cognitive functioning) correlate with preferences for these functions. Thirty-one participants (M age = 67.52, SD = 7.29), took part in the study. They had to interact with the HMI and rate its functions based on the importance and likelihood of using them. Results suggest that participants prefer adaptive HMIs, with journey planner capabilities. As expected, as it is a CAV HMI, the Information and Entertainment functions are also preferred. Individual differences have limited relationship with HMI preferences

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

The utility of psychological measures in evaluating perceived usability of automated vehicle interfaces – A study with older adults

The design of the traditional vehicle human-machine interfaces (HMIs) is undergoing major change as we move towards fully connected and automated vehicles (CAVs). Given the diversity of user requirements and preferences, it is vital for designers to gain a deeper understanding of any underlying factors that could impact usability. The current study employs a range of carefully selected psychological measures to investigate the relationship with self-report usability of an in-CAV HMI integrated into a fully automated Level 5 simulator, during simulated journeys. Twenty-five older adults (65-years+) participated and were exposed to four journeys in a virtual reality fully automated CAV simulator (with video recorded journeys) into which our HMI was integrated. Participants completed a range of scales and questionnaires, as well as computerized cognitive tests. Key measures were: perceived usability of the HMI, cognitive performance, personality, attitudes towards computers, trust in technology, simulator sickness, presence and emotion. HMI perceived usability correlated positively with cognitive performance (e.g., working memory) and some individual characteristics such as trust in technology and negatively with neuroticism anxiety. Simulator sickness was associated negatively with CAV HMI perceived usability. Positive emotions correlated positively with reported usability across all four journeys, while negative emotions were negatively associated with usability only in the case of the last two journeys. Increased sense of presence in the virtual CAV simulator was not associated with usability. Implications for design are critically discussed. Our research is highly relevant in the design of high-fully automated vehicle HMIs, particularly for older adults, and in informing policy-makers and automated mobility providers of how to improve older people’s uptake of this technology

Regime confluence in socio-technical transitions: a study of connected, autonomous, shared and electric vehicles

This PhD research aims to investigate sustainable future automobility by using socio-technical transitions theory (STT). Automobility plays multi-functional roles in society not only as commuting tool but also serving tool for serving higher quality of life, freedom of movement, and increasingly is associated with environmentally friendly concepts. This emergent form of automobility integrates many aspects ranging from connectivity (C) between vehicles and to everything else, to vehicle automation (A), car sharing (S), and electronic powertrain (E), which ultimately may combine to provide automobility as an on-demand service. Therefore, these so-called ‘CASE’ (connected, autonomous, shared, electric) vehicles bridge automobility freedom of movement in physical ‘limited’ spaces with ‘unlimited’ virtual spaces into one seamless experience, fundamentally transforming the meaning of automobility. Hence, this research has the following issues to address: is it possible for the four features (CASE) to combine? If this becomes a prevalent trend, could they redefine automobility, and with what consequences? To answer the relevant research questions, mixed data collective methods have been conducted. In which, secondary data extracted mainly from governmental documents, companies’ official webpages, professional online websites, and the grey literature. Meanwhile, primary data via interviews are used to further verify the cases’ validity. Hence, 340 instances of CASE developments identified during the research have been collected to construct an empirical storyline supplemented with 33 in-depth interviews. Additionally, we have highlighted 7 corporate cases in the traditional automotive industry and 4 outsiders to illustrate the CASE transformation process. The main findings are: 1) network theory could supplement STT to provide insights into the relationships between ‘niche’ areas and the ‘regime’; 2) regime boundary dissolution and network reintegration help new niches emerge at regime level; 3) CASE concepts have allowed ‘outsiders’ to challenge automotive OEM incumbents; and 4) the automobility transformation pathway is following ‘dealignment - realignment’ pattern. The thesis concludes many individual initiatives have failed but some remain, finding a development path for a multiplicity of reasons (political, market-driven, corporate strategy or environmental requirements). These half-mature niches and networks will finally challenge existing rules and regulations and thus push society and technology forward to reach to another ‘balance’. However, to reach a new ‘balance’ is a huge challenge that requires to leverage different stake holders such as environment sustainability, policymakers, customers and of course car manufacturers