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Information requirements for future HMI in partially automated vehicles
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Ulahannan, Arun (2019) Information requirements for future HMI in partially automated vehicles. EngD thesis, University of Warwick.
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Official URL: http://webcat.warwick.ac.uk/record=b3714793~S15
Abstract
Partially automated vehicles are increasing in prevalence and enable drivers to hand over physical control of the vehicle’s longitudinal and latitudinal control to the automated system. However, at this partial level of automation, drivers will still be required to continuously monitor the vehicle’s operation and take back control at any time from the system when required. The Society of Automotive Engineers (SAE) defines this as Level 2 automation and consequently a number of design implications arise.
To support the driver in the monitoring task, Level 2 vehicles today present a variety of information about sensor readings and operational issues to keep the driver informed; so appropriate action can be taken when required. However, existing research has shown that current Level 2 HMIs increase the cognitive workload, leading to driver cognitive disengagement and hence increasing the risk to safety. However, despite this knowledge, these Level 2 systems are available on the road today and little is known about what information should be presented to drivers inside these systems. Hence, this doctorate aimed to deliver design recommendations on how HMIs can more appropriately support the driver in the use of a partially automated Level 2 (or higher) vehicle system. Four studies were designed and executed for this doctorate.
Study 1 aimed to understand the information preferences for drivers in a Level 2 vehicle using semi-structured interviews. Participants were exposed to a 10 minute, Level 2 driving simulation. A total of 25 interviews were conducted for first study. Using thematic analysis, two categories of drivers: ‘High Information Preference’ (HIP) and ‘Low Information Preference’ (LIP) were developed. It was evident that the drivers' expectations of the partial automation capability differed, affecting their information preferences and highlighting the challenge of what information should be presented inside these vehicles. Importantly, by defining these differing preferences, HMI designers can be more informed to design effective HMI, regardless of the driver’s predisposition.
Building on this, an Ideas Café public engagement event was designed for Study 2; implementing a novel methodology to understand factors of trust in automated vehicles. Qualitative data gathered from the 35 event attendees was analysed using thematic analysis. The results reaffirmed the importance of the information presented in automated vehicles. Based on these first two studies, it was evident that there was an opportunity to develop a more robust understanding of what information is required in a Level 2 vehicle.
Information requirements were quantitatively investigated through two eye-tracking studies (Studies 3 and 4). Both used a novel three- or five-day longitudinal study design. A shortlist of nine types of information was developed based on the results from the first two studies, regulatory standards and collaborations with Jaguar Land Rover experts. This was the first shortlist of its kind for automated vehicles. These 9 information types were presented to participants and eye tracking was used to record their information usage during Level 2 driving. Study 3 involved 17 participants and displayed only steady state scenarios. Study 4 involved 27 participants and introduced handover and warning events. Across both studies, information usage changed significantly, highlighting the methodological importance of longitudinal testing over multiple exposures. Participants increased their usage of information confirming the vehicle’s current state technical competence. In comparison, usage decreased of future state information that could help predict the future actions of the vehicle. By characterising the change in information usage, HMI designers can now ensure important information is designed appropriately. Notably, the ‘Action Explanation’ information, that described what the vehicle was doing and why, was found to be consistently the most used information. To date, this type of information has not been observed on any existing Level 2 HMI. Results from all four studies was synthesised to develop novel design recommendations for the information required inside Level 2 vehicles, and how this should be adapted over time depending on the driver’s familiarity with the system and driving events.
This doctorate has contributed novel design recommendations for Level 2 vehicles through an innovative methodological approach across four studies. These design recommendations can now be taken forward to design and test new HMIs that can create a better, safer experience for future automated vehicles.
Item Type: | Thesis (EngD) | ||||
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Subjects: | T Technology > TL Motor vehicles. Aeronautics. Astronautics | ||||
Library of Congress Subject Headings (LCSH): | Automated vehicles, Automobiles -- Automatic control, Automated vehicles -- Psychological aspects, Automobile driving -- Psychological aspects, Automobiles -- Instruments, User interfaces (Computer systems) | ||||
Official Date: | October 2019 | ||||
Dates: |
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Institution: | University of Warwick | ||||
Theses Department: | Warwick Manufacturing Group | ||||
Thesis Type: | EngD | ||||
Publication Status: | Unpublished | ||||
Supervisor(s)/Advisor: | Birrell, Stewart A. ; Oliveira, Luis B. ; Cain, Rebecca ; Jennings, Paul Andrew | ||||
Sponsors: | Jaguar Land Rover (Firm) | ||||
Format of File: | |||||
Extent: | xi, 137 leaves : illustrations (some colour) | ||||
Language: | eng |
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