Exploring the Usability of a Connected Autonomous Vehicle Human Machine Interface Designed for Older Adults [chapter]

Phillip L. Morgan, Alexandra Voinescu, Chris Alford, Praminda Caleb-Solly
2018 Advances in Intelligent Systems and Computing  
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 humanmachine 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,
more » ... ght 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. Introduction We are moving at a rapid pace towards fully autonomous vehicles that handle all driving related functions without the need for user intervention. Level 5 fully connected autonomous vehicles (CAVs) are defined by SAE International [4] as systems that can handle 'the full-time performance by an automated driving system of all aspects of the dynamic driving task under all roadway and environmental conditions that can be managed by a human driver', whereas Level 4 highly automated vehicles are similar but only have such system capabilities for some driving modes and may require human intervention for some non-driving related actions. Both levels assume that the user is not an active driver and can therefore have eyes and mind off the road. This means they will not require driving input devices such as a steering wheel and pedals. Instead, user interaction with Level 4 and 5 CAVs will be through human-machine interface (HMI) dashboards providing vehicle-related (e.g., speed, time/distance to destination, local area information) and other features and functions (e.g., infotainment). Level 4 CAV HMIs may also offer some interactive features such as the ability to personalize journeys (e.g., an unplanned stop or deviation) en route. [4-6] It is therefore vital for human factors specialists, designers, engineers, and programmers -to develop effective CAV HMIs tailored to the needs and requirements of those using them and for a high degree of system usability. This will likely enhance factors such as trust, positive attitudes towards automated systems, and ultimately adoption and continued use of CAVs. The current paper presents findings relating to the evaluation of a prototype CAV HMI designed for older adults and/or individuals with sensory and/or physical impairments. Both populations are likely to be early adopters of Level 4 and 5 CAVs due the significant and increased mobility options that they will offer. The key focus is on HMI usability and relationships with important factors such as situation awareness (SA), task load, attitudes towards computers, and, trust in technology and automation. A recent review by [2] (see also [1]) synthetized best practice design principles to inform the development of CAV in-vehicle HMIs for use by older adults and individuals with sensory and/or physical impairments that would prevent them from driving or mean that driving ability is impaired. They organized these into five themed areas including general principles and ageing-related factors that could affect HMI accessibility and usability, and inform functionality and adaptability requirements. We discuss these below and give examples that relate to the design of CAV in-vehicle HMIs for use by our target populations with a key focus on usability principles. General principles put forward by [7] emphasize the importance of factors such as: providing informative feedback (e.g., verification -'confirm', 'cancel' -of a chosen action such as destination); consistency (e.g., location and grouping of related features such as speed and time to destination); allow easy error handling (option to reverse actions such as when accidentally activating a system stop button); and reduce memory demands (e.g., easy access to important information such as current location, destination, and any stops). [8] extended these to include e.g.: striving for a good match between the system and the real world (e.g., meaningful icons displayed in a logical manner -such as a battery for energy status); ensuring easy access to system status information (e.g., vehicle status in terms of tyres, brakes, engine and network), simplicity (e.g., only display information that is absolutely necessary, avoid display clutter), and to always aim to establish standards and conventions that can be adhered
doi:10.1007/978-3-319-93885-1_54 fatcat:43yvdfdhqjeonn4mp7gqqkfqdu