Human–Vehicle Interactions

1. Introduction

Transportation is not only one of the largest industry sectors in the world [1]; it is also an elementary need of humans worldwide with an expected increase of almost 200% in global passenger transport demand from 2020 to 2050 [2]. To meet the ever-growing mobility demands while simultaneously aiming to achieve higher levels of safety, advances in sensor and automation technologies have caused an unprecedented transformation in the automotive industry. Instead of causing a linear shift towards higher degrees of vehicle strategic and tactical decision making with equally decreased human driver input, this transformation has instead resulted in a broad spectrum of functions and subsystems on an equally broad spectrum of automation—from fully manual to fully automated. At the same time, advances in data processing and communication infrastructure have enabled new ways for these subsystems to interact, exchange, and provide an entirely new operational layer that can influence a vehicle’s trajectory and decision making.

At the helm of the vehicles within this fundamentally transformed ecosystem is still the human—be it behind the wheel or behind a screen in a control center. The technical advancements create new opportunities for safer mobility that is accessible to a wider spectrum of users, as well as enabling new ways to use commuting time beyond the performance of manual driving tasks. These advancements also create new roles for humans interacting with vehicles across different transportation modes and degrees of automation. Most importantly, the resulting novel landscape of heterogeneous vehicle technologies and human roles creates a complex web of connection points between humans and vehicular technologies, which require appropriate interaction interfaces, techniques and, ultimately, an understanding of the interaction requirements in this evolving web of humans and the mobility technologies that shall serve their needs.

To this end, this Special Issue collects contributions representing the state of the art in human–vehicle interaction with the aim of providing tools, methods, and insights for interaction researchers and designers across the wider spectrum of topics and challenges within the domain.

2. Overview of Contributions to This Special Issue

The transportation sector is characterized by many different conceptions as well as expectations within the populace all around the world regarding the vehicles of the future and their capabilities, so much so that it raises the question of whether and/or to which extent these different biases and mental models might influence users’ experience of modern vehicle technologies. The contribution by Manger et al. [3] investigated exactly that for users of vehicle automation technologies. The study revealed that users did not develop automation bias but were susceptible to accepting automation system explanations more when accompanied by explanations, regardless of whether these are actually relevant explanations (referred to as the “Truthiness Effect”). The findings also suggest an effect of the user’s mental model on susceptibility to the Truthiness Effect—the more complex the mental model, the lower the susceptibility and vice versa. The work shows the importance of explanations in interaction design for automated vehicles that can either calibrate the user’s expectations of an automated vehicle or cause biases if not performed properly and provides important basic research for future vehicle interaction research and design.

The publication by Martin-Castresana et al. [4] addresses the challenge of proper lane-keeping during manual driving, a frequent factor in on-road accidents, especially during curves or bends in the road. These spaces are difficult to evaluate and design for, due to strong heterogeneity in road configurations, in particular, regarding lane widths and turning radii. To address this challenge, the publication investigates the effectiveness of different road marking designs to improve lane-keeping behavior during manual driving, evaluated across different radii and turning directions. The results show that a red-colored transverse band design can improve lateral position in left curves, while red peripheral transverse bars can improve overall lateral position variability.

With the rapid development of China’s automobile manufacturing prowess and an increase in IVIS (In-Vehicle Information System) levels of content and detail, there is an increased need to investigate interface requirements and their differences across the western and eastern markets. To this end, the publication by Zhong et al. [5] presents a study that investigated text sizes of in-vehicle interfaces for Chinese characters specifically. The publication defines an optimum of 7mm for Chinese text in IVIS, thereby complementing existing knowledge on ideal English and Korean text sizes, which enhances our tools to design across cultures and languages.

A significant challenge in today’s automotive environment consists of the ever-increasing degrees of connectivity and prevalence of C-ITS (Cooperative Intelligent Transport Systems). For both providers and users of C-ITS technologies, the field consists of a number of challenges which strongly manifest in an interplay of service provision and data requirements vs. data privacy concerns and varying levels of willingness to comply. The publication by Novak et al. [6] investigated the available literature on C-ITS services to untangle this complex field and identified compliance rates based on type of service provided as well as use case, which provides a valuable basis for future C-ITS service provision design and implementation.

Zhou et al. [7] present interaction strategies for in-vehicle voice assistants for different levels of driver fatigue. The study investigated driver responses to three different communication strategies (high, moderate, and low intensity) across three driver fatigue stats (severe fatigue, high fatigue, and non-fatigued). The results further enrich our tools, this time addressing the auditory dimension, to design for effective and safe interaction within vehicles of the present and future.

Distracted driving is still one of the main causes of decreased driver performance and a frequent cause of on-road accidents [8]. With the rise of modern smartphones and the increasing digitalization of the driver space, the number of potential distractors in modern vehicles is greater than before, with a significant proportion of distractors coming from interfaces and displays inside the vehicle. The publication by Harms et al. [9] presents a detailed insight into interaction frequencies and durations on a per-interaction-element basis. The authors identified the ten most frequently performed tasks, both driving relevant ones (e.g., adjusting windshield wipers) and non-driving relevant (e.g., changing radio stations), calculated aggregated task frequencies and durations per function category, and further assessed differences between interacting with a vehicle the user is familiar vs. unfamiliar with. The results provide a valuable basis to design in-vehicle interfaces targeted towards minimizing the distraction potentials with regard to their specific functional category, resulting frequency and/or duration of use.

The topic of on-road accidents extends beyond powered two-wheelers towards micromobility, which is becoming increasingly more relevant as alternative modes of transportation for urban contexts as well as more sustainable alternatives to “traditional” powered individual transportation modes. The contribution by Nathania et al. [10] presents detailed insights into e-scooter fall accidents, the most common type of e-scooter accident [11]. The paper contributes a detailed breakdown of influencing factors (human, vehicle, environmental) during both pre-fall and fall phases.

Driving automation technology, by its very nature of taking away manual driving tasks of a human driver, has the potential to render mobility more accessible to those who are unable or unfit to drive themselves. To this end, Walker et al. [12] investigated the specific on-road risks that drivers with dementia face when operating a vehicle and have identified, which of these could conceivably be addressed by which types of driving automation technology, thus paving the way for future driving automation innovations to serve as a mobility enabler for demographics that are unable to or are otherwise subject to limitations regarding the use of individual mobility means.

Dyadic interactions, i.e., interactions between two agents, have seen extensive studies in road interaction research. Dyadic settings are highly useful from a research point of view, as they allow for a clear focus on specific research questions. Since many traffic interactions in the real world are multifaceted and frequently involve more than two agents, it can be very difficult to scale research results up to an operational level. The publication by Dey et al. [13] addresses this gap by analyzing dyadic interaction studies through a study design framework. The results show the different dimensions, tradeoffs, and benefits of different setup choices and configurations to help researchers define the right laboratory setting for the right real-world problem to solve.

The final publication [14] presents an ontology-based customization management system for in-vehicle interfaces. The ontology contains attributes and relations for driver profiles, individual in-vehicle interface elements, as well as settings for restrictions. This allows the linking of legal requirements and constraints on the modifiability of interfaces or interface elements connected to specific user preferences. The result is a tool that can serve as a formal (and thereby machine-readable) basis for in-vehicle interfaces that are customized towards user preferences while maintaining legal conformity and a focus on safety at the same time.

3. Conclusions and Future Perspectives

The challenges in human–vehicle interaction design are manifold and cover a broad spectrum of technical, psychophysical, and sociopolitical aspects. It is imperative that advancements and innovations in mobility, a safety-critical domain, advance along this full spectrum of associated challenges as much as possible in order to ensure safe and working mobility solutions that ultimately benefit humans in their everyday lives. The publications contained in this Special Issue provide insights and solutions across a wide range of contemporary topics and challenges in human–vehicle interaction design. Their solutions provide a strong methodological basis for the design and development of effective human–vehicle interaction techniques and systems that are scalable towards future technology advancements as well as evolving societal developments.