Philipp Wintersberger

Automated Driving System, Male, or Female Driver: Who'd You Prefer? Comparative Analysis of Passengers' Mental Conditions, Emotional States & Qualitative Feedback

It is expected that automated vehicles (AVs) will only be used when customers believe them to be safe, trustworthy, and match their personal driving style. As AVs are not very common today, most previous studies on trust, user experience, or acceptance measures in automated driving are based on qualitative measures. The approach followed in this work is different, as we compared the direct effect of human drivers versus automated driving systems (ADSs) on the front seat passenger. In a driving simulator study (N=48), subjects had either to ride with an ADS, a male, or a female driver. Driving scenarios were the same for all subjects. Findings from quantitative measurements (HRV, face tracking) and qualitative pre-/post study surveys and interviews suggest that there are no significant differences between the passenger groups. Our conclusion is, that passengers are already inclined to accept ADS and that the market is ready for AVs.

Trust in Technology as a Safety Aspect in Highly Automated Driving

Abstract Trust in technology is an important factor to be considered for safety-critical systems. Of particular interest today is the transport domain, as more and more complex information and assistance systems find their way into vehicles. Research in driving automation / automated driving systems is in the focus of many research institutes worldwide. On the operational side, active safety systems employed to save lives are frequently used by non-professional drivers that neither know system boundaries nor the underlying functional principle. This is a serious safety issue, as systems are activated under false circumstances and with wrong expectations. At least some of the recent incidents with advanced driving assistance systems (ADAS) or automated driving systems (ADS; SAE J3016) could have been prevented with a full understanding of the driver about system functionality and limitations (instead of overreliance). Drivers have to be trained to accept and use these systems in a way, that subjective trust matches objective trustworthiness (cf. “appropriate trust”) to prevent disuse and / or misuse. In this article, we present an interaction model for trust calibration that issues personalized messages in real time. On the showcase of automated driving we report the results of two user studies related to trust in ADS and driving ethics. In the first experiment (N = 48), mental and emotional states of front-seat passengers were compared to get deeper insight into the dispositional trust of potential users of automated vehicles. Using quantitative and qualitative methods, we found that subjects accept and trust ADSs almost similarly as male / female drivers. In another study (N = 40), moral decisions of drivers were investigated in a systematic way. Our results indicate that the willingness of drivers to risk even severe accidents increases with the number and age of pedestrians that would otherwise be sacrificed. Based on our initial findings, we further discuss related aspects of trust in driving automation. Effective shared vehicle control and expected advantages of fully / highly automated driving (SAE levels 3 or higher) can only be achieved when trust issues are demonstrated and resolved.

Natural, intuitive finger based input as substitution for traditional vehicle control

Both amount as well as dynamicity of content to be displayed in a car increases steadily, forcing manufacturer to change over to customizable screens integrated in dashboard and center console instead of dozens to hundreds of individual control signals. In addition, new requirements such as Internet access in the car or web services accessible while driving invalidates rudimentary display formats. Traditional forms of interaction such as buttons or knobs are unsuitable to respond to dynamic content shown on digital screens, requesting new mechanisms for distraction-free yet effective user (driver) input. We pick up this problem by introducing a novel sensing device allowing for natural, contactless, and eyes-free operation by relating finger movements in the area of the gearshift to screen coordinates. To assess quality features of this interface two research questions were formulated, (i) that the application of such a device would allow for natural, intuitive mouse pointer control in a similar manner than traditional forms of input and (ii) that the interface is insusceptible to varying workload conditions of the driver. Results from experimentation have revealed that, with respect to the first hypothesis, proximity sensing in a two-dimensional plane is a viable approach to directly control a mouse cursor on a screen integrated into the dashboard. A generally accepted conclusion on the assumption that the index of performance of the interface does not change with varying workload (hypothesis ii) cannot be drawn. To simulate different conditions of workload a dual task signal-response setting was used.

A Framework for Analyzing and Calibrating Trust in Automated Vehicles

When predicting the traffic of the future and the acceptance of automated vehicles, we often like to assume that one of the major challenges will be to foster overall trust in automated vehicles for effective and safe mixed-traffic operations. In this paper, we propose a more faceted viewpoint and argue for the benefits of -- and provide an initial framework for --calibrated trust by fostering trust and distrust in automated vehicles. If drivers know exactly what their vehicle is and is not capable of, then they are more likely to react properly and be prepared when handover requests or other unexpected circumstances might occur.

Traffic Augmentation as a Means to Increase Trust in Automated Driving Systems

Many human factor issues regarding automated driving systems are still unresolved. For instance, it is not fully clear if, and to what extent, drivers will accept and trust this novel technology. Trust in technology is of utmost importance to avoid both disuse and misuse. Possibilities for increasing user trust in automated driving systems include proper feedback aiming to build a shared mental model so that system intentions are visible to the driver. A potential approach could be to augment traffic and other relevant objects in the environment. Technical advancements in display technology would allow the use of windshield displays in the near future. To investigate the effect of augmented reality aids (presented as augmentations of traffic objects) in potentially ambiguous situations, we conducted a user study (n=26) and assessed qualitative (trust scale TS, technology acceptance model TAM) and quantitative (HRV) factors. Initial results indicate that augmenting sensor data in the drivers line of sight can lead to increased trust and acceptance.

A Novel Approach for Researching Crossing Behavior and Risk Acceptance: The Pedestrian Simulator

To integrate unpredictable human behavior in the assessment of active and passive pedestrian safety systems, we introduce a virtual reality (VR)-based pedestrian simulation system. The device uses the Xsens Motion Capture platform and can be used without additional infrastructure. To show the systems applicability for pedestrian behavior studies, we conducted a pilot study evaluating the degree of realism such a system can achieve in a typical unregulated pedestrian crossing scenario. Six participants had to estimate vehicle speeds and distances in four scenarios with varying gaps between vehicles. First results indicate an acceptable level of realism so that the device can be used for further user studies addressing pedestrian behavior, pedestrian interaction with (automated) vehicles, risk assessment and investigation of the pre-crash phase without the risk of injuries.

Towards a Personalized Trust Model for Highly Automated Driving

User acceptance of automated vehicles (and dependent dimensions such as road safety, frequency of use or level of recommendation) is said to be highly dependent on the operator’s individual trust in this technology. As a consequence, the development of driving functions and future driver-vehicle interfaces should allow for appropriate trust calibration. To better understand trust and the effect of mis-calibration on the way to a personalized trust model, we propose a set of trust-related research questions derived from related work and our own user studies. Based on preliminary investigation, we recommend examining 1) differences in users and subgroups of users, 2) different levels of trust based on situation or context, 3) methods for quantifying trust in naturalistic driving studies, and 4) definitions for an established/approved trust model and the individual calibration of the model with regard to driving behavior and automotive user interfaces. The final outcome should be a multidimensional trust model that fits the individual passenger/driver by dynamically adapting driving mode and UI representation/feedback.

LumiConSense: a transparent, flexible, scalable, and disposable image sensor using thin-film luminescent concentrators

Our sensor [Koppelhuber and Bimber 2013] consists of a thin, transparent polycarbonate film, referred to as luminescent concentrator (LC), that is doped with fluorescent dyes. Light of a particular wavelength sub-band that penetrates the film is emitted in longer wavelengths, while wavelengths outside the sub-band are fully transmitted. The example shown in figure 1(a) absorbs blue and emits green light. The emitted light is mostly trapped inside the film by total internal reflection (TIR), and is transported with reduced multi-scattering towards the LC edges while losing energy over transport distance. The bright film edges indicate decoupling of the light integral transported to each edge point from all directions inside the LC.

Workaholistic: on balancing typing- and handover-performance in automated driving

Automated driving eliminates the permanent need for vehicle control and allows to engage in non-driving related tasks. As literature identifies office work as one potential activity, we estimate that advanced input devices will shortly appear in automated vehicles. To address this matter, we mounted a keyboard on the steering wheel, aiming to provide an exemplary safe and productive working environment. In a driving simulator study (n=20), we evaluated two feedback mechanisms (heads-up augmentation on a windshield, conventional heads-down display) and assessed both typing effort and driving performance in handover situations. Results indicate that the windshield alternative positively influences handovers, while heads-down feedback results in better typing performance. Text difficulty (two levels) showed no significant impact on handover time. We conclude that for a widespread acceptance of specialized interfaces for automated vehicles, a balance between safety aspects and productivity must be found in order to attract customers while retaining driving safety.

Let Me Finish before I Take Over: Towards Attention Aware Device Integration in Highly Automated Vehicles

A major promise of automated vehicles is to render it possible for drivers to engage in nondriving related tasks, a setting where the execution pattern will switch from concurrent to sequential multitasking. To allow drivers to safely and efficiently switch between multiple activities (including vehicle control in case of Take-Over situations), we postulate that future vehicles should incorporate capabilities of attentive user interfaces, that precisely plan the timing of interruptions based on driver availability. We propose an attention aware system that issues Take-Over Requests (1) at emerging task boundaries and (2) directly on consumer devices such as smartphones or tablets. Results of a driving simulator study (N=18), where we evaluated objective, physiological, and subjective measurements, confirm our assumption: attention aware Take-Over Requests have the potential to reduce stress, increase Take-Over performance, and can further raise user acceptance/trust. Consequently, we emphasize to implement attentive user interfaces in future vehicles.