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

Abstract

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. Twentyfive 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 PERCEIVED USABILITY OF AUTOMATED VEHICLES 3 policy-makers and automated mobility providers of how to improve older people's uptake of this technology.

Evaluation of Multimodal External Human–Machine Interface for Driverless Vehicles in Virtual Reality

“…There are two distinct focuses of research into human-machine interfaces for driverless vehicles. The major emphasis of related work is on the interactive interface between the driverless vehicle and the person inside the vehicle, which we call the iHMI (interior human-machine interface) [12][13][14]. The external human-machine interface (eHMI) that focuses on the interaction of the driverless vehicle and the pedestrian, is less explored, which is the focus of our work.…”

A Design Space for Human Sensor and Actuator Focused In-Vehicle Interaction Based on a Systematic Literature Review

“…For example, kinesthetic input at the center stack [242], steering wheel [221], seat [181], table [163], or ceiling [163]. We also found approaches for tactile input at similar locations, e.g., dashboard [377], center stack [270], steering wheel [289], table [276], or door [158]. Only a few publications considered novel input modalities at anchored locations, such as EDA [143], skin temperature [143], or heart rate [239] (all located on the steering wheel).…”

Older Adult Willingness to Use Fully Autonomous Vehicle (FAV) Ride Sharing

“…Along with the fear and distrust noted by those who were not willing to use FAV ride sharing, the most important feature of a self-driving vehicle that would make older adults willing to take a ride was a proven safety record in terms of performance and technology. Indeed, existing research indicates that a low trust in technology is associated with negative attitudes toward self-driving vehicles [24] and that those with positive perceptions towards AV technology are more likely to be the early adopters [25]. Until the safety and reliability of FAVs can be fully demonstrated, it appears unlikely that older adults will be willing to adopt the technology and harness the benefits of FAV ride sharing as a transportation option.…”