In-vehicle voice assistants (VAs) can potentially enhance driving safety and user experience. However, their success depends on trust and acceptance. This study explores two influencing factors: (1) design-based and (2) performance-based attributes. In a driving simulator study, N = 53 participants engaged with VAs varying in anthropomorphic appearance and response latency. Results indicate that neither factor universally enhanced trust or acceptance. Instead, a nuanced interaction emerged: When response latency was short, anthropomorphic appearance had no impact. However, when response latency was long, both the non- and high-anthropomorphic VA were rated as more trustworthy than a low-anthropomorphic VA. Additionally, participants rated the high-anthropomorphic VA equally trustworthy across both latencies, suggesting a potential buffering effect of anthropomorphism under suboptimal performance conditions. Furthermore, trust fully mediated the relationship between the factors and acceptance, supporting models that conceptualize trust as a precursor of acceptance. Based on these insights, design recommendations were derived.

The Box Task combined with a Detection Response Task (BT + DRT) is a relatively less investigated but promising method for evaluating visual-manual and cognitive task demand due to the interaction with in-vehicle information systems while driving. The BT includes the tracking of a dynamic box whose size and position follow a sinusoidal pattern with uniform amplitudes and frequencies. However, it is unclear whether participants are able to predict and adapt to these uniform dynamics, which might lead to a reduced sensitivity of the BT + DRT. Within the present study, it was aimed to examine differences in BT + DRT performance depending on uniform and non-uniform BT dynamics. A laboratory study was conducted with N = 41 participants. The experimental conditions differed in the type and difficulty level of the secondary tasks as well as in the BT dynamics (uniform, varying amplitude, varying frequency). While the uniform BT dynamics could be more predictable, the non-uniform BT dynamics were designed slightly easier in their difficulty using a lower frequency or amplitude. The results revealed no performance benefits when performing uniform BT dynamics compared to non-uniform BT dynamics. The frequency BT condition was related to a significantly lower variability of box position and higher gaze duration on the secondary task compared to the uniform BT dynamics. These findings suggest that participants are not or only negligible able to adapt to the uniform BT dynamics. Therefore, it is recommended to use the uniform BT dynamics as suggested and implemented in previous studies.

With highly automated vehicles (HAVs), the human role shifts from active driver to mostly passive passenger, which has an impact on the perceived comfort while being driven. A number of factors need to be taken into account when designing an automated driving style (ADS) with the aim to minimize human discomfort. In this paper, the authors build on seven empirical studies to determine first, if a generally comfortable ADS exists and second, whether such an ADS should be designed depending on situational driving dynamics or individual user characteristics such as users’ manual driving styles. The results give an overview of the ADS- and user-related factors causing human discomfort in automated driving and provide potential strategies to overcome potential discomfort. Drawing on the data, upcoming challenges in the field of human discomfort in HAVs for both research and practice are presented.

In this paper we introduce an Intelligent Transport System (ITS), designed for enabling cooperative drivingmanoeuvres in mixed traffic scenarios considering heterogeneous communications and cloud infrastructuresystems. We present an architecture that enables connected vehicles to access ITS services independent oftheir underlying communication technology. This is achieved by introducing a large scale communicationsystem including the road-side infrastructure as well as a heterogeneous cloud. We present insights from theAutomated Connected Vehicle (ACV) concept and examine human factors elaborating on the experience oftwo aspects: driving in an ACV as well as driving in a Non-Automated Connected Vehicle (NACV), interactingwith an ACV. Furthermore, we present insights of initial demonstrations, emphasizing that the system workswell in real traffic scenarios.

It will not be long until Level 3 Automated Driving Systems (L3 ADS) enter the consumer market. An important role corresponds to methodology development. The present paper gives impetus to the process of developing robust methods for evaluating Human-Machine Interfaces (HMI) for L3 ADS. First, a literature review on automotive interfaces concerning methodology application is outlined showing that studies often lack to provide both self-report and observational data. To derive a comprehensive image of HMI quality, we recommend multi-method approach in user research. Subsequently, we provide an overview of state-of-the-art self-report and observational measures. From the availability of measures and the necessity to include both in user studies, the issue of the performance-preference dissociation arises. It threatens study designs and interpretation of results. Following methodological recommendations from the present work supports researchers and practitioners in the area of automated driving for proper study design and interpretation of study results.

Informal communication plays a crucial role for negotiation processes in transport and thus, needs to be implemented in automated vehicles. Slowing down to encourage pedestrians to cross is one example of informal communication. To implement naturally-looking automated slowdown, a first step is to examine expected moments of braking from a pedestrian's perspective. Gap Acceptance and Time-To-Arrival (TTA) estimates can provide these timings. The present experimental study assessed the effects of vehicle size, speed and participant's age on expected braking initiation. Pre-recorded real-world videos of approaching cars (truck/smart) with various speed (10 to 40 km/h) on a parking area were presented to 42 participants from 18 to 75 years. Results showed more risky estimations/decisions with increasing speed. Older participants showed more conservative gap acceptance. Vehicle size only influenced TTA estimations (size-arrival-effect) but not gap acceptance. Thus, applying one simple time gap value does not fit human/pedestrians perception and expectations.

Advancing range-information user interfaces towards enhanced usability is a continuous task in electric vehicle development. The objective of the present research was (1) to examine experienced trustworthiness of a typical range-information user interface, (2) to test a newly constructed trustworthiness scale, (3) to examine the relationship of experienced trustworthiness to individual usable range (i.e., comfortable range), and (4) to identify possibilities for further improvement of range-information user interfaces. Data from N = 74 participants of a large-scale electric vehicle field trial were analyzed. Results show that experienced trustworthiness of the range estimation system is related to a higher comfortable range. Moreover, users developed several suggestions on how to further improve the user interface. The results imply that perceived trustworthiness should be considered as a benchmark for evaluating range-information user interfaces and that users should have flexible options to adjust the parameters of the range estimation system.