Purring Wheel: Thermal and Vibrotactile Notifications on the Steering Wheel

Haptic feedback can improve safety and driving behaviour. While vibration has been widely studied, other haptic modalities have been neglected. To address this, we present two studies investigating the use of uni- and bimodal vibrotactile and thermal cues on the steering wheel. First, notifications with three levels of urgency were subjectively rated and then identified during simulated driving. Bimodal feedback showed an increased identification time over unimodal vibrotactile cues. Thermal feedback was consistently rated less urgent, showing its suitability for less time critical notifications, where vibration would be unnecessarily attention-grabbing. The second study investigated more complex thermal and bimodal haptic notifications comprised of two different types of information (Nature and Importance of incoming message). Results showed that both modalities could be identified with high recognition rates of up to 92% for both and up to 99% for a single type, opening up a novel design space for haptic in-car feedback

Supporting Eyes-Free Human–Computer Interaction with Vibrotactile Haptification

The sense of touch is a crucial sense when using our hands in complex tasks. Some tasks we learn to do even without sight by just using the sense of touch in our fingers and hands. Modern touchscreen devices, however, have lost some of that tactile feeling while removing physical controls from the interaction. Touch is also a sense that is underutilized in interactions with technology and could provide new ways of interaction to support users. While users are using information technology in certain situations, they cannot visually and mentally focus completely during the interaction. Humans can utilize their sense of touch more comprehensively in interactions and learn to understand tactile information while interacting with information technology. This thesis introduces a set of experiments that evaluate human capabilities to understand and notice tactile information provided by current actuator technology and further introduces a couple of examples of haptic user interfaces (HUIs) to use under eyes-free use scenarios. These experiments evaluate the benefits of such interfaces for users and concludes with some guidelines and methods for how to create this kind of user interfaces. The experiments in this thesis can be divided into three groups. In the first group, with the first two experiments, the detection of vibrotactile stimuli and interpretation of the abstract meaning of vibrotactile feedback was evaluated. Experiments in the second group evaluated how to design rhythmic vibrotactile tactons to be basic vibrotactile primitives for HUIs. The last group of two experiments evaluated how these HUIs benefit the users in the distracted and eyes-free interaction scenarios. The primary aim for this series of experiments was to evaluate if utilizing the current level of actuation technology could be used more comprehensively than in current-day solutions with simple haptic alerts and notifications. Thus, to find out if the comprehensive use of vibrotactile feedback in interactions would provide additional benefits for the users, compared to the current level of haptic interaction methods and nonhaptic interaction methods. The main finding of this research is that while using more comprehensive HUIs in eyes-free distracted-use scenarios, such as while driving a car, the user’s main task, driving, is performed better. Furthermore, users liked the comprehensively haptified user interfaces

Assisting Navigation and Object Selection with Vibrotactile Cues

Our lives have been drastically altered by information technology in the last decades, leading to evolutionary mismatches between human traits and the modern environment. One particular mismatch occurs when visually demanding information technology overloads the perceptual, cognitive or motor capabilities of the human nervous system. This information overload could be partly alleviated by complementing visual interaction with haptics. The primary aim of this thesis was to investigate how to assist movement control with vibrotactile cues. Vibrotactile cues refer to technologymediated vibrotactile signals that notify users of perceptual events, propose users to make decisions, and give users feedback from actions. To explore vibrotactile cues, we carried out five experiments in two contexts of movement control: navigation and object selection. The goal was to find ways to reduce information load in these tasks, thus helping users to accomplish the tasks more effectively. We employed measurements such as reaction times, error rates, and task completion times. We also used subjective rating scales, short interviews, and free-form participant comments to assess the vibrotactile assisted interactive systems. The findings of this thesis can be summarized as follows. First, if the context of movement control allows the use of both feedback and feedforward cues, feedback cues are a reasonable first option. Second, when using vibrotactile feedforward cues, using low-level abstractions and supporting the interaction with other modalities can keep the information load as low as possible. Third, the temple area is a feasible actuation location for vibrotactile cues in movement control, including navigation cues and object selection cues with head turns. However, the usability of the area depends on contextual factors such as spatial congruency, the actuation device, and the pace of the interaction task

Passenger Response to Driving Style in an Autonomous Vehicle

Despite rapid advancements in automated driving systems (ADS), current human-computer interaction research tends to focus more on the safety driver in lower level vehicles. The future of automated driving lies in higher level systems that do not always require a safety driver to be present. However, passengers might not fully trust the capability of the ADS in the absence of a safety driver. Furthermore, while an ADS might have a specific set of parameters for its driving profile (such as thresholds for acceleration and how closely it follows a lead vehicle), passengers might have different driving preferences, some more defensive than others. Taking these preferences into consideration is, therefore, an important issue which can only be accomplished by understanding what makes a passenger uncomfortable or anxious. In order to tackle this issue, we ran a user study in a physical autonomous vehicle. Various driving profile parameters were manipulated and tested in a scenario consisting of four different events. Physiological measurements were also collected along with self-report scores, and the combined data was analyzed using Linear Mixed-Effects Models. We found that the presence and proximity of a lead vehicle significantly moderated the effect of other parameters on the physiological responses. Stopping events also generated a higher level of response than non-stopping events. Finally, a statistically significant association between physiological responses and self-reported scores showed that such responses could potentially be used to indicate comfort or anxiety in future adaptive systems

Characterization of driver neuromuscular dynamics for human-automation collaboration design of automated vehicles

In order to design an advanced human-automation collaboration system for highly automated vehicles, research into the driver's neuromuscular dynamics is needed. In this paper a dynamic model of drivers' neuromuscular interaction with a steering wheel is firstly established. The transfer function and the natural frequency of the systems are analyzed. In order to identify the key parameters of the driver-steering-wheel interacting system and investigate the system properties under different situations, experiments with driver-in-the-loop are carried out. For each test subject, two steering tasks, namely the passive and active steering tasks, are instructed to be completed. Furthermore, during the experiments, subjects manipulated the steering wheel with two distinct postures and three different hand positions. Based on the experimental results, key parameters of the transfer function model are identified by using the Gauss-Newton algorithm. Based on the estimated model with identified parameters, investigation of system properties is then carried out. The characteristics of the driver neuromuscular system are discussed and compared with respect to different steering tasks, hand positions and driver postures. These experimental results with identified system properties provide a good foundation for the development of a haptic take-over control system for automated vehicles