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Katharina Wiedemann

Katharina Wiedemann
Würzburg Institute for Traffic Sciences (WIVW GmbH)

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39
Publications
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770
Citations
Citations since 2017
36 Research Items
755 Citations
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Publications

Publications (39)
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...
Thesis
Fahrzeughersteller haben die Verfügbarkeit sogenannter hochautomatisierter Fahrfunktionen (SAE Level 3; SAE, 2018) in ihren Modellen angekündigt. Hierdurch wird der Fahrer in der Lage sein, sich permanent von der Fahraufgabe abzuwenden und fahrfremden Tätigkeiten nachzugehen. Allerdings muss er immer noch als Rückfallebene zur Verfügung stehen, um...
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
Objective: This study aimed at investigating the driver’s takeover performance when switching from working on different non–driving related tasks (NDRTs) while driving with a conditionally automated driving function (SAE L3), which was simulated by a Wizard of Oz vehicle, to manual vehicle control under naturalistic driving conditions. Background:...
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...
Presentation
Introduction Within the next years, vehicles will be capable of taking over the driving task in certain environments without the need to be continuously monitored by the user. This so-called conditionally automated driving (L3-automation according to SAE J3016 [1]), unlike highly or fully automated driving, still will require the user as a fallbac...
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
Full-text available
Automated driving systems are getting pushed into the consumer market, with varying degrees of automation. Most often the driver's task will consist of being available as a fall-back level when the automation reaches its limits. These so-called takeover situations have attracted a great body of research, focusing on various human factors aspects (e...
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...
Chapter
Vorwort Sehr geehrte Damen und Herren, Fahrerassistenzsysteme und insbesondere automatisches Fahren definieren die Mobilität der Zukunft in erheblichem Maße. Zahlreiche Systeme sind heute fest im Markt etabliert. Studien belegen, dass durch deren Einführung nicht nur der Fahrkomfort, sondern vor allem die Sicherheit des Fahrers und seiner Umgebung...
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...
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...
Article
This study investigated driver performance during system limits of partially automated driving. Using a motionbased driving simulator, drivers encountered different situations in which a partially automated vehicle could no longer safely keep the lateral guidance. Drivers were distracted by a non-driving related task on a touch display or driving w...
Article
Full-text available
During conditionally automated driving (CAD), driving time can be used for non-driving-related tasks (NDRTs). To increase safety and comfort of an automated ride, upcoming automated manoeuvres such as lane changes or speed adaptations may be communicated to the driver. However, as the driver’s primary task consists of performing NDRTs, they might p...
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...
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 [61] (SAE) 1-3 [76], in highway, urban, and close-distance scenarios. The recommendations developed in this work were pr...
Conference Paper
Full-text available
Conditionally automated driving (CAD) relieves the driver from monitoring current traffic conditions. This type of driving inherently enables the driver to execute different non-driving-related tasks (NDRTs). However, the driver still must be available as a backup option. With this in mind, the classification and evaluation of various NDRTs concern...
Chapter
Full-text available
Cooperative perception of the traffic environment will enable Highly Automated Driving (HAD) functions to provide timelier and more complex Take-Over Requests (TOR) than it is possible with vehicle-localized perception alone. Furthermore, cooperative perception will extend automated vehicles’ capability of performing tactic and strategic maneuvers...
Conference Paper
Full-text available
During highly automated driving, upcoming automated manoeuvres (e.g., lane changes) should be communicated to the driver in order to ensure system transparency. As driving time can be used for non- driving-related tasks (NDRT), such as office work or in-vehicle entertainment, drivers might prefer to be informed in a non-distracting way as interrupt...

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Cited By

Projects

Projects (4)
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.