16,430 research outputs found

    The influence of system transparency on trust: Evaluating interfaces in a highly automated vehicle

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    Previous studies indicate that, if an automated vehicle communicates its system status and intended behaviour, it could increase user trust and acceptance. However, it is still unclear what types of interfaces will better portray this type of information. The present study evaluated different configurations of screens comparing how they communicated the possible hazards in the environment (e.g. vulnerable road users), and vehicle behaviours (e.g. intended trajectory). These interfaces were presented in a fully automated vehicle tested by 25 participants in an indoor arena. Surveys and interviews measured trust, usability and experience after users were driven by an automated low-speed pod. Participants experienced four types of interfaces, from a simple journey tracker to a windscreen-wide augmented reality (AR) interface which overlays hazards highlighted in the environment and the trajectory of the vehicle. A combination of the survey and interview data showed a clear preference for the AR windscreen and an animated representation of the environment. The trust in the vehicle featuring these interfaces was significantly higher than pretrial measurements. However, some users questioned if they want to see this information all the time. One additional result was that some users felt motion sick when presented with the more engaging content. This paper provides recommendations for the design of interfaces with the potential to improve trust and user experience within highly automated vehicles

    Designing an Adaptive Interface: Using Eye Tracking to Classify How Information Usage Changes Over Time in Partially Automated Vehicles

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    While partially automated vehicles can provide a range of benefits, they also bring about new Human Machine Interface (HMI) challenges around ensuring the driver remains alert and is able to take control of the vehicle when required. While humans are poor monitors of automated processes, specifically during ‘steady state’ operation, presenting the appropriate information to the driver can help. But to date, interfaces of partially automated vehicles have shown evidence of causing cognitive overload. Adaptive HMIs that automatically change the information presented (for example, based on workload, time or physiologically), have been previously proposed as a solution, but little is known about how information should adapt during steady-state driving. This study aimed to classify information usage based on driver experience to inform the design of a future adaptive HMI in partially automated vehicles. The unique feature of this study over existing literature is that each participant attended for five consecutive days; enabling a first look at how information usage changes with increasing familiarity and providing a methodological contribution to future HMI user trial study design. Seventeen participants experienced a steady-state automated driving simulation for twenty-six minutes per day in a driving simulator, replicating a regularly driven route, such as a work commute. Nine information icons, representative of future partially automated vehicle HMIs, were displayed on a tablet and eye tracking was used to record the information that the participants fixated on. The results found that information usage did change with increased exposure, with significant differences in what information participants looked at between the first and last trial days. With increasing experience, participants tended to view information as confirming technical competence rather than the future state of the vehicle. On this basis, interface design recommendations are made, particularly around the design of adaptive interfaces for future partially automated vehicles

    Digitizing human-to-human interaction for automated vehicles

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    From Manual Driving to Automated Driving: A Review of 10 Years of AutoUI

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    This paper gives an overview of the ten-year devel- opment of the papers presented at the International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutoUI) from 2009 to 2018. We categorize the topics into two main groups, namely, manual driving-related research and automated driving-related re- search. Within manual driving, we mainly focus on studies on user interfaces (UIs), driver states, augmented reality and head-up displays, and methodology; Within automated driv- ing, we discuss topics, such as takeover, acceptance and trust, interacting with road users, UIs, and methodology. We also discuss the main challenges and future directions for AutoUI and offer a roadmap for the research in this area.https://deepblue.lib.umich.edu/bitstream/2027.42/153959/1/From Manual Driving to Automated Driving: A Review of 10 Years of AutoUI.pdfDescription of From Manual Driving to Automated Driving: A Review of 10 Years of AutoUI.pdf : Main articl

    An Evaluation Schema for the Ethical Use of Autonomous Robotic Systems in Security Applications

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    We propose a multi-step evaluation schema designed to help procurement agencies and others to examine the ethical dimensions of autonomous systems to be applied in the security sector, including autonomous weapons systems

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

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    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

    I Am The Passenger: How Visual Motion Cues Can Influence Sickness For In-Car VR

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    This paper explores the use of VR Head Mounted Displays (HMDs) in-car and in-motion for the first time. Immersive HMDs are becoming everyday consumer items and, as they offer new possibilities for entertainment and productivity, people will want to use them during travel in, for example, autonomous cars. However, their use is confounded by motion sickness caused in-part by the restricted visual perception of motion conflicting with physically perceived vehicle motion (accelerations/rotations detected by the vestibular system). Whilst VR HMDs restrict visual perception of motion, they could also render it virtually, potentially alleviating sensory conflict. To study this problem, we conducted the first on-road and in motion study to systematically investigate the effects of various visual presentations of the real-world motion of a car on the sickness and immersion of VR HMD wearing passengers. We established new baselines for VR in-car motion sickness, and found that there is no one best presentation with respect to balancing sickness and immersion. Instead, user preferences suggest different solutions are required for differently susceptible users to provide usable VR in-car. This work provides formative insights for VR designers and an entry point for further research into enabling use of VR HMDs, and the rich experiences they offer, when travelling
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