Nadja Schoemig

Nadja Schoemig
WIVW GmbH

Dr.
Senior Researcher at WIVW GmbH

About

66
Publications
22,964
Reads
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993
Citations
Citations since 2017
38 Research Items
791 Citations
2017201820192020202120222023050100150
2017201820192020202120222023050100150
2017201820192020202120222023050100150
2017201820192020202120222023050100150
Additional affiliations
October 2003 - December 2007
University of Wuerzburg
Position
  • Senior Researcher

Publications

Publications (66)
Article
Augmented reality (AR) technology could establish direct relationships between displayed information and objects in the real driving environment, e.g. by highlighting relevant objects in the traffic environment. However, it is unclear how these potential benefits of augmentation affect drivers’ distraction from the driving task and their level of w...
Article
Full-text available
Vehicles equipped with so-called partially automated driving functions are becoming more and more common nowadays. The special feature of this automation level is that the driver is relieved of the execution of the lateral and longitudinal driving task, although they must still monitor the driving environment and the automated system. The method pr...
Conference Paper
Full-text available
The presented simulator study compared two different driver-in-the-loop strategies on driver's eye glances and intervention behavior at system limits in partial automated driving with a control condition without any strategy: A state-dependent strategy achieved by a driver monitoring system and a situation-dependent strategy by using a monitoring r...
Article
Full-text available
The presented method describes a standardized test procedure for the evaluation of takeover performance of drivers during automated driving. It was primarily developed to be used for evaluating Level 3 systems (conditional automated driving). It should be applied in a driving simulator environment during the development phase of a system. The metho...
Conference Paper
The presented simulator study investigated the effectiveness, user experience and usability of an innovative driver monitoring system (DMS) for partially automated driving, called "Jeannie". This virtual assistant provided continuous visual emotional feedback dependent on drivers' monitoring behaviour and issued warnings and speech outputs in respo...
Technical Report
Full-text available
Human Factors Fragestellungen sind ein wachsendes Forschungsfeld im Kontext des automatisierten Fahrens. Trotz der großen Anzahl an neu veröffentlichten Studien zu verschiedenen Themengebieten fällt auf, dass die meisten Studien kein standardisiertes Vorgehen beispielsweise bei der Untersuchung von Übernahmesituationen verwenden, was die Vergleichb...
Technical Report
Full-text available
The report presents two standardized methodological approaches for evaluating the efficiency and safety of human-machine interaction in the use of partially automated driving functions. For this purpose, test criteria were defined to assess the fulfilment of the necessary requirements for conveying adequate system knowledge, adequate system and sit...
Book
Full-text available
The human-machine interface of automated driving systems (ADS) will play a crucial role in their safe, comfortable and efficient use. For example, the ADS HMI should be capable of efficiently informing the user about the current automated driving mode and the user’s responsibilities (e.g., whether the ADS is functioning properly or requesting a tra...
Article
Full-text available
Today, OEMs and suppliers can rely on commonly agreed and standardized test and evaluation methods for in-vehicle human-machine interfaces (HMIs). These have traditionally focused on the context of manually driven vehicles and put the evaluation of minimizing distraction effects and enhancing usability at their core (e.g., AAM guidelines or NHTSA v...
Chapter
We examined the necessity for plausibilization of test scenarios within usability studies for AV HMIs in driving simulator studies. One group of drivers experienced system-initiated transitions without any obvious reason, the other with plausible reasons (e.g. fog for L3 → L2 transition, broken-down vehicle for L3 TOR). The results showed that reac...
Article
Full-text available
Within a workshop on evaluation methods for automated vehicles (AVs) at the Driving Assessment 2019 symposium in Santa Fe; New Mexico, a heuristic evaluation methodology that aims at supporting the development of human–machine interfaces (HMIs) for AVs was presented. The goal of the workshop was to bring together members of the human factors commun...
Technical Report
Full-text available
The report at hand gives an overview of current research issues and relevant methodical aspects concerning the conceptualization of experimental studies on highly automated driving (according to SAE automation level 3). For that purpose, 569 relevant publications from 1998 to 2019 were analyzed. The content of the report may serve as a guideline fo...
Article
Full-text available
Objective: The human–machine interface (HMI) is a crucial part of every automated driving system (ADS). In the near future, it is likely that—depending on the operational design domain (ODD)—different levels of automation will be available within the same vehicle. The capabilities of a given automation level as well as the operator’s responsibiliti...
Conference Paper
Full-text available
With the Federal Automated Vehicles Policy, the U.S. National Highway Traffic Safety Administration (NHTSA) has provided an outline that can be used to guide the development and validation of Automated Driving Systems (ADS). Acknowledging that the Human-Machine-Interface (HMI) – identified as one of the 12 priority safety design elements in this vo...
Article
Full-text available
In most levels of vehicle automation, drivers will not be merely occupants or passengers of automated vehicles. Especially in lower levels of automation, where the driver is still required to serve as a fallback level (SAE L3) or even as a supervisor (SAE L2), there is a need to communicate relevant system states (e.g., that the automated driving s...
Conference Paper
Full-text available
Reflecting the increasing demand for harmonization of human machine interfaces (HMI) of automated vehicles, different taxonomies of use cases for investigating automated driving systems (ADS) have been proposed. Existing taxonomies tend to serve specific purposes such as categorizing transitions between automation modes; however, they cannot be gen...
Conference Paper
This paper investigates whether an Augmented Reality Head-up Display (AR-HUD) supports usability and reduces visual demand during conditionally automated driving. In a driving simulator study, 24 drivers experienced several driving scenarios while driving with conditional automation. The drivers completed one drive with a fully developed HMI design...
Article
Reflecting the increasing demand for harmonization of human machine interfaces (HMI) of automated vehicles, different taxonomies of use cases for investigating automated driving systems (ADS) have been proposed. Existing taxonomies tend to serve specific purposes such as categorizing transitions between automation modes; however, they cannot be gen...
Article
During highly automated driving (level 3 automation according to SAE International, 2014) people are likely to increase the frequency of secondary task interactions. However, the driver must still be able to take over control within a reasonable amount of time. Previous studies mainly investigated take-over behavior by forcing participants to engag...
Chapter
With the increasing number of functionalities of In-Vehicle Information Systems (IVIS) their complexity is rising. In addition new input modalities are used to control the car. Many manufacturers switch from using haptic input devices to touchscreens. On the other hand there are increasingly more sensors available in a car that could support the dr...
Chapter
The goal of this study was to investigate whether it is possible to in- duce negative affects in the interaction with IVIS in a driving simulator environ- ment and whether this would be reflected in the driver’s facial expressions. N=29 participants completed a 30-minutes-drive in a high-fidelity driving simulator performing several IVIS tasks usin...
Article
Full-text available
Up to a level of full vehicle automation, drivers will have to be available as a fallback level and take back manual control of the vehicle in case of system limits or failures. Before introducing automated vehicles to the consumer market, the controllability of these control transitions has to be demonstrated. This paper presents a novel procedure...
Article
Objective: Aim of the study was to evaluate the impact of different non-driving related tasks (NDR tasks) on takeover performance in highly automated driving. Background: During highly automated driving, it is allowed to engage in NDR tasks temporarily. However, drivers must be able to take over control when reaching a system limit. There is evi...
Conference Paper
In highly automated driving, the driver is allowed to temporarily engage in non-driving related tasks (NDR-tasks). However, when reaching a system limit, the driver needs to take back vehicle control within a reasonable amount of time. Previous studies found impairments in takeover performance while engaged in NDR-tasks, but little is known about t...
Article
In a driving simulator study we evaluated a speech-based driver assistance system for urban intersections (called Assistance on Demand AoD system) which supports the driver in monitoring and decision making. The system provides recommendations for suitable time gaps to enter the intersection based on the observation of crossing traffic. Following an...
Conference Paper
Full-text available
Driving Automation Systems conduct the driving task to a partial or even full extent. HMI concepts that support the understanding and predictability of the system's behaviour may be beneficial for the safe and efficient use of such systems. We investigated HMI concepts indicating the predicted curvature of the road section in two consecutive studie...
Article
Within the context of highly automated driving, where the automated system takes over the dynamic driving task and supervision activity from the driver is no longer required, new challenges must be considered, like an increasing likelihood for the driver being out of the loop. This might result in a higher engagement in non-driving related (NDR) ta...
Conference Paper
Full-text available
We have previously introduced a novel Assistance On Demand (AOD) concept in the context of an urban speech-based left-turn assistant which supports the driver in monitoring and decision making by providing recommendations for suitable time gaps to enter the intersection. In a first user study participants showed a clear preference for the AOD syste...
Conference Paper
Full-text available
To increase the safety in use of automated vehicles, Human Factors research has focused primarily on driver performance during takeover situations. However, surveys on public opinion on automated vehicles still report a lack of acceptance of the technology. In this review, we give an overview on how taking the changed role of the driver into accoun...
Technical Report
Full-text available
This report documents the Human Factors (HF) recommendations developed and used for the design of demonstrator vehicles within the AdaptIVe project. The proposed HF-recommendations, therefore, mostly address the automation levels (SAE) 1-3, in highway, urban, and close-distance scenarios. The recommendations developed in this work were predominantl...
Article
This report documents the Human Factors (HF) recommendations developed and used for the design of demonstrator vehicles within the AdaptIVe project. The proposed HF-recommendations, therefore, mostly address the automation levels (SAE) 1-3, in highway, urban, and close-distance scenarios. The recommendations developed in this work were predominantl...
Chapter
Seamless Electronics for Automotive Services. Going forward from the last ELIV „Electronics in Vehicles“ in 2015 – the most significant Congress in Automotive Electronics has now seen a substantial upgrade. In line with the feedback given by participants, speakers and journalists we have added new elements and contents to the event, which is benefi...
Conference Paper
We evaluated a system to support the driver in urban intersections (called "Assistance on Demand" AoD system). The system is controlled via speech and supports the driver in monitoring and decision making by providing recommendations for suitable time gaps to enter the intersection. This speech-based control of the system allows the implementation...
Conference Paper
Full-text available
The progress in developing highly automated driving applications and the corresponding opportunities for the driver to take himself out of the loop have raised a couple of questions regarding the effects of highly automated driving on the driver's state. Within this framework a simulator study was conducted at the Wuerzburg Institute for Traffic Sc...
Article
Full-text available
It is assumed that drivers are able to adapt their interaction with secondary tasks to the demands of driving. To do so, they need to be situationally aware of the current driving situation. Three levels are proposed through which drivers adapt their interaction with a secondary task to the demands of driving. On the planning level, more general st...
Article
This chapter considers attention in driving as controlled through three processes: bottom-up control, top-down control and explorative perception. The theoretical background for the three processes is provided. In driving with a visual secondary task, attention is supposed to be mainly controlled through top-down processes, which direct attention t...
Article
Full-text available
This overview article describes the goals, concepts and very preliminary results of the subproject Joint System within the EU-project HAVEit. The goal of HAVEit is to develop and investigate vehicle automation beyond ADAS systems, especially highly automated driving, where the automation is doing a high percentage of the driving, while the driver i...
Article
Full-text available
The paper describes an experiment where anticipatory processes in the interaction with secondary tasks while driving could be explicitly identified and contrasted to control processes during the engagement in the secondary task. A special experimental set-up in a driving simulator environment was created that allows drivers to deliberately decide w...
Article
Full-text available
Visual attention in driving with visual secondary task is compared for two visual secondary tasks. N=40 subjects completed a 1h test drive in a motion-base driving simulator. During the drive, participants either solved an externally paced, highly demanding visual task or a self paced menu system task. The secondary tasks were offered in defined cr...
Conference Paper
As vehicle and computer technology are more and more merging, new forms of assistance and automation in vehicles open up the potential to increasing safety and improving comfort. In HAVEit, an EU-FP7 Integrating Project, car and truck manufacturers, suppliers and research organizations explore highly automated driving applications, where the automa...
Article
Full-text available
Die vorliegende Arbeit diskutiert, inwieweit das im Bereich der Luftfahrt entwickelte Konzept des Situationsbewusstseins auf den Fahrkontext übertragen werden kann. Als zwei wesentliche Merkmale von Situationsbewusstsein werden dabei zum einen antizipative Prozesse der Handlungsplanung sowie kontrollierende Prozesse der Handlungsabsicherung definie...
Article
Full-text available
In this study, the efficiency of different strategies for the interaction with in-vehicle devices was analysed. Twenty-four drivers completed a test course in a motion-based driving simulator containing different critical situations. At predetermined points of the route, an additional menu navigation task was offered to the driver. The driver could...
Article
The EU-funded project HAVEit aims at the realization of highly automated driving for intelligent transport. Within the Joint System approach in HAVEit automation is adapted to the intentions and limits of both of the two members in a Joint system- the driver and a technical co- system. In order to evaluate driver's performance capabilities it is ne...
Chapter
Die Forschung zum Handeln in komplexen Situationen- vor allem in der Luftfahrt — war lange Zeit an Fragen der Wahrnehmung und Aufmerksamkeit bzw. an Konzepten wie Workload orientiert, die sich hauptsächlich auf die fokale Aufgabe und deren Bewältigung durch den Operator beziehen. Daneben besteht eine weitere Anforderung darin, aus den aktuell relev...
Chapter
Im Fahrzeug spielt die Aufmerksamkeit des Fahrers und deren optimale Verteilung auf handlungsrelevante Aspekte der Fahrsituation eine wesentliche Rolle für Fahrsicherheit und Fahrkomfort. Zahlreiche Studien belegen, dass die Aufmerksamkeit des Fahrers insbesondere in Informations- und Kommunikationssituationen (z.B. Telefonieren am Steuer) erheblic...
Article
The applicability of SAGAT method for measuring Situation Awareness in the driving context was analyzed in a driving simulator study. N = 20 subjects drove through a driving course with different specific demanding situations, in which they were asked for various aspects of the driving scene during the freezing of the simulation. In one experimenta...
Article
Within the scope of the research project "Learnability of Driver Information Systems" (commissioned by the Forschungsvereinigung Automobiltechnik e.V. and the Federal Highway Research Institute) the influence of menu structure was analyzed under single-task (study 1) vs. dual-task conditions (using a parallel tracking task in a driving simulator wi...
Article
Full-text available
Kompetenzerwerb und Struktur von Menüsystemen Kompetenzerwerb als Ansatz zur HMI-Gestaltung Mensch-Maschine-Interaktionen innerhalb des Fahrzeugs umfassen ein sich ständig erweiterndes Spektrum von Funktionen. Neben bekannten Funktionen, wie Mobiltelefon und Navigationssystem, wird insbesondere die Integration von Infotainmentfunktionen (z.B. Inter...

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Projects

Projects (5)
Archived project
Dear Colleagues, Today, OEMs and suppliers can rely on commonly agreed and standardized testing and evaluating methods for in-vehicle human–machine interfaces (HMIs). These have traditionally focused on the context of manually driven vehicles and put the evaluation of minimizing distraction effects and enhancing usability at their core (e.g., AAM guidelines or NHTSA visual distraction guidelines). However, advances in automated driving systems (ADS) have already begun to change the driver’s role from actively driving the vehicle to monitoring the driving situation and being ready to intervene in partially automated driving (SAE L2). Higher levels of vehicle automation will likely only require the driver to act as a fallback ready user in case of system limits and malfunctions (SAE L3) or could even act without any fallback within their operational design domain (SAE L4). During the same trip, different levels of automation might be available to the driver (e.g., L2 in urban environments, L3 on highways). These developments require new test and evaluation methods for ADS, as available test methods cannot be easily transferred and adapted. For example, The ADS HMI should be capable of informing the user about the current mode and minimize confusion about the status of the ADS and the user’s current responsibilities (e.g., whether the ADS is functioning properly, ready for use, unavailable for use or requesting a transition of control from the ADS to the user). While ADS might allow new and more comfortable seating positions and engagement in nondriving-related tasks that were not allowed in manual driving, these might generate motion sickness or lower the user’s availability for a transfer of control. As the driving task is no longer actively fulfilled by the driver, distraction by nondriving-related tasks might turn into controlled engagement. ADS might behave differently than manually driven vehicles, which might generate a need for external HMIs or standardized motion patterns to adequately interact with non-equipped traffic participants. This Special Issue welcomes theoretical papers as well as empirical studies that deal with these new challenges by proposing new and innovative test methods in the evaluation of ADS HMIs in areas such as (but not limited to) the topics below: - Mode awareness and mode indicators; - Testing of minimum HMI requirements; - Driver state in the context of ADS (e.g. distraction or drowsiness); - Trust in ADS; - External HMIs for ADS; - Guidelines for HMIs for ADS; - Motion sickness in ADS; - Validity of test settings (on-road, driving simulators, etc.); - Learnability and usability of ADS; - Comfortable and pleasurable user experience of ADS. Dr. Frederik Naujoks Dr. Sebastian Hergeth Dr. Andreas Keinath Dr. Nadja Schömig Katharina Wiedemann Guest Editors Manuscript Submission Information Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website. Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Information is an international peer-reviewed open access monthly journal published by MDPI. Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions. Keywords •Automated driving •Human–machine interface •Test methods •User studies •Evaluation Published Papers This special issue is now open for submission.
Project
Assessing the Human-machine Interface (HMI) of automated vehicles requires new tools and research methods, reaching from the definition of use cases to the selection of suitable behavioural indicators. This project summarizes efforts to stimulate the scientific and technical development in this area.
Project
In the medium term, automated driving will not be possible without human participation. Especially in conditionally automated driving (SAE L3), the drivers do not need to monitor the automation permanently. However, they must still be available as a fallback level in order to intervene in case of system limits and errors and must be able to take over manual control. In this context, it must be assessed whether the drivers are safely able to control such a take-over situation. In scientific literature, the term controllability can mean different potentially safety-relevant aspects when drivers need to react to system limits or failures. In essence, it is substantially identical with driving and road safety. Against this background, the TOC-Rating was developed to be applied in human subject research. The TOC-Rating is a scientifically based expert method for assessing the controllability of take-over situations in conditionally automated driving. Trained raters assess the controllability by means of video material on the basis of a coding sheet including all relevant observation criteria. Taking into account all observation criteria, an overall rating of the controllability is given.The rating thus supports the evaluation of take-over situations and adds another tool to the available methods. The method was developed in the context of the joint research project Ko-HAF.