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Higher levels of automated driving may offer the possibility to sleep in the driver’s seat in the car, and it is foreseeable that drivers will voluntarily or involuntarily fall asleep when they do not need to drive. Post-sleep performance impairments due to sleep inertia, a brief period of impaired cognitive performance after waking up, is a potential safety issue when drivers need to take over and drive manually. The present study assessed whether sleep inertia has an effect on driving and cognitive performance after different sleep durations. A driving simulator study with n = 13 participants was conducted. Driving and cognitive performance were analyzed after waking up from a 10–20 min sleep, a 30–60 min sleep, and after resting without sleep. The study’s results indicate that a short sleep duration does not reliably prevent sleep inertia. After the 10–20 min sleep, cognitive performance upon waking up was decreased, but the sleep inertia impairment faded within 15 min. Although the driving parameters showed no significant difference between the conditions, participants subjectively felt more tired after both sleep durations compared to resting. The small sample size of 13 participants, tested in a within-design, may have prevented medium and small effects from becoming significant. In our study, take-over was offered without time pressure, and take-over times ranged from 3.15 min to 4.09 min after the alarm bell, with a mean value of 3.56 min in both sleeping conditions. The results suggest that daytime naps without previous sleep deprivation result in mild and short-term impairments. Further research is recommended to understand the severity of impairments caused by different intensities of sleep inertia.

Das FlexCAR besteht aus einer autonom gesteuerten Fahrzeugplattform für die Mobilität von morgen, welche Use-Case-gesteuert als Forschungsdemonstrator fungiert, um neue technologische Features unmittelbar aus dem Forschungsstadium nach dem Plug-and-Play–Prinzip gezielt zu implementieren. Damit kann eine frühzeitige Validierung im Hinblick auf ein künftiges Anwendungspotenzial ermöglicht werden. Offene Soft- und Hardwareschnittstellen sind hier berücksichtigt oder werden weiterentwickelt. FlexCAR comprises an autonomously controlled vehicle platform for the mobility of tomorrow. Use case-guided as a research platform, it enables implementing new technological features according to the plug-and-play principle. It allows for an early validation concerning potential future applications. Open software and hardware interfaces are included and will be further developed.

Automated vehicles are entering the roads and automation is applied to cars, trucks, buses, and even motorcycles today. High automation foresees transitions during driving in both directions. The driver and rider state become a critical parameter since reliable automation allows safe intervention and transit control to the automation when manual driving is not performed safely anymore. When the control transits from automation to manual an appropriate driver state needs to be identified before releasing the automated control. The detection of driver states during manual and automated driving and an appropriate design of the human-machine interaction (HMI) are crucial steps to support these transitions. State‐of‐the‐art systems do not take the driver state, personal preferences, and predictions of road conditions into account. The ADAS&ME project, funded by the H2020 Programme of the European Commission, proposes an innovative and fully adaptive HMI framework, able to support driver/rider state monitoring‐based transitions in automated driving. The HMI framework is applied in the target vehicles: passenger car, truck, bus, and motorcycle, and in seven different use cases.

The issue of driving performance after sleeping becomes highly interesting when introducing automated driving in Level 4 (SAE). It is known that fatigue as well as hypovigilance are severe risk factors for traffic accidents while an effective countermeasure is sleeping. In Level 4 automation sleeping while driving becomes a possible scenario, including the issues of transitions. Several seconds for take-over as known from distraction studies are not enough to adjust the seat, regain control and recover after sleeping. Furthermore, when analyzing human performance after sleeping, the phenomenon of sleep inertia may affect reaction time and quality of performance.Take-over time and the effect of sleep inertia are investigated in a driving simulator study with 44 participants. As independent variable, the time after waking-up until taking over is varied: The participants had to take-over the driving task one minute, seven minutes or 15 min after waking up. A control group completed the task without sleeping. Lane keeping, deviation of line during the lane change task, braking time and mental workload served as dependent variables. There were no significant differences in driving performance between the groups when looking at driving performance, safety aspects and mental workload, hence no effect of sleep inertia was measured here. Further studies should investigate individual performance of more outliers and apply even more controlled measures to understand better if and how sleep inertia can become a problem for driving and what countermeasures should be applied. The study also shows, that take-over time of one minute leads to successful, but hectic take-overs, whereas a take-over time of 15 min induces fatigue in some drivers. We conclude that powernaps have a good chance to become a safe reality in Level 4 automation with a suitable take-over time between one and seven minutes. Keywords: Autonomous driving, Sleep inertia, Take-over, Driving performance, Driving simulation

Positive user experiences (PUX) in the vehicle interior will be enabled by choosing the technologies with the potential to provide such experiences. Design for PUX in general exists, but methods to assess and compare technologies regarding their PUX potential are missing. Building on the insight that fulfillment of basic psychological needs may lead to PUX (Hassenzahl et al., 2010), this paper presents the first iteration of the user-centered method Tec4UXNeeds. Tec4UXNeeds combines VR representations of technologies and half-structured interviews to identify PUX potential of technologies: which basic psychological needs a technology may fulfill and in which use cases the technology could be used to enable need fulfillment. The method is applied for two display technologies in a standardized within-subjects study (n = 27). The study investigates whether the method Tech4UX enables participants to describe whether a technology has a potential to fulfill psychological needs for them and whether the method is specific enough to find differences in need fulfillment potential between technologies described by participants.Preliminary results identified distinct levels of need fulfillment for the first and second display technology (Display on Demand & Holography). Data will be analyzed further using qualitative content analysis. The method will be optimized iteratively in the future.

Automated driving is dramatically changing the way we perceive and control cars and lorries. In partially automated driving, the driver is still responsible for the vehicle control, but is strongly supported. In highly automated driving, the driver can give control and responsibility to the automation for a certain time and can get control back, e.g. when the automation encounters limits. However, an intuitive way to interact with these automated modes is largely missing. Vorreiter is addressing this by using the inspiration of a rider and a horse to provide intuitive steering gestures on the steering wheel or an alternative device, which initiate manoeuvres to be executed by the automation and to be supervised, influenced or interrupted by the driver. The gestures are built up in a design-for-all which helps all drivers, including beginners and drivers with disabilities. A consortium of RWTH Aachen University, Fraunhofer IAO, University of Stuttgart, Valeo and Hochschule fur Wirtschaft und Recht Berlin defined a concept, built up prototypes and investigated its impact in workshops and simulator experiments.

With the introduction of ADAS systems and vehicle automation, an interface informing the driver of the automation state is required. This study evaluates the suitability of a visual interface comprising up to 64 LEDs on the steering wheel perimeter; it displays continuous visual feedback about the automation state—including notifications of an unscheduled hand-over due to sudden system failure. Three HMI (Human Machine Interface) designs were evaluated: two versions with visual cues on the steering wheel and one without (baseline). We implemented the designs in a driving simulator and compared the subjective responses of 38 participants to questionnaires measuring user experience, trust, and acceptance. The designs with visual cues improved the participants’ user experience, as well as their trust in, and acceptance of, automated vehicles. Moreover, both designs were well perceived by participants.

Developing proof-of-concept solutions for new integrated rescue support systems is challenging, due to the different restrictions and procedures at different installation sites. One way of dealing with this conflict is the provision of one prototype for a mininumand one for the maximum number of functions. This article presents a support module for the operators of traffic infrastructures, developed with minimum functionalities, which allows for implementing an automated critical event detection and passenger rescue, supported by the SAVE ME system. Here, its functions, the implementation and test results from two pilot tests are described.

Due to their different risk assessment, e.g. running for a ball or pushing each other to the road, children are one of the highly endangered vulnerable road users. Most accidents occur on the way to school and close to the school bus stops. To protect children early information for car drivers may be helpful to slow down traffic before reaching a critical area such as a school bus stop. To enhance the acceptance among car drivers the information should be displayed as soon as possible, for example once children are present at the bus stop. Information about children as a new message in automotive Human-Machine-Interfaces (HMI) should be based on existing display and information concepts like integrated icons in dashboards or highlighted points of interests on the navigation map. Using an iterative design process with different design loops and evaluations a user-centered HMI is developed. This paper describes the development of a highly usable and accepted automotive HMI displaying road signs to protect children at school bus stops.

Whenever an emergency situation occurs, a correct response of the rescue teams and an optimal communication and coordination among them is required to assure that all the people needing help are assisted within a short period of time. This paper presents an approach for the development of innovative HMIs within SAVE ME project to save the lives of travellers and rescuers, giving particular emphasis to the most vulnerable people. The emergency response system detects natural and man-made disaster events in public transport terminals/vehicles and critical infrastructures and supports quick and optimal mass evacuation guidance.

Qualitative and quantitative data, collected during a usability evaluation of two innovative prototypes of a small display touch screen device, have been used to perform a multi-level assessment of the questionnaires used within the trial. The use of different validation methods is depicted and discussed concerning their advantages and disadvantages. The conclusions from the validation study are depicted, revealing that the usage of the ISOmetrics for testing uncommon prototypes may result in insufficient validity of the instrument.

For more than one decade the European Commission has been focusing on the enhancement of road safety by funding research on Advanced Driver Assistance Systems (ADAS) and Intelligent Vehicle Information Systems (IVIS) in the field of automotive. However, the application of such technologies in Powered-Two-Wheelers (PTW) is currently lacking behind. While in the automotive sector extended knowledge has been generated also on the Human-Machine Interface (HMI) for ADAS and IVIS this does by far not apply for the PTW sector. This paper presents the SAFERIDER (Advanced telematics for enhancing the safety and comfort of motorcycle riders) project outline and focuses on the new HMI concept and haptic interface devices that are developed within the project.

GOOD ROUTE is a European project developing a cooperative system for routing, monitoring, re-routing, enforcement and driver support of dangerous goods vehicles, based upon dynamic, real time data, in order to minimise the Societal Risks related to their movements, whereas still generating the most cost efficient solution for all actors involved in their logistic chain. In this paper the theoretical background for the Human-Machine Interface of the GOOD ROUTE system is discussed, different actors are characterised and their user needs are described. Basic functionalities and elements as well as the preliminary guidelines that endorse the GOOD ROUTE system approach are presented.

Automated driving is no longer a future scenario. Several automotive OEM have already presented automated vehicles, which do not require driver's constant attention on the road. But, there are still some challenges to solve before series vehicles can pass from assisted driving to highly automated driving [1; 2]. A principal research question to deal with is how to design Take-Over-Requests (TOR) with respect to the human machine interface (HMI) and reaction times to comply with a TOR. On this account, a driving simulator study with 44 drivers has been conducted at the Fraunhofer Institute for Industrial Engineering. The study took place in a highly automated driving vehicle which controlled longitudinal and lateral control on a highway scenario. Approaching a construction site different TOR strategies were presented. Within this study the time users needed to react on a TOR was measured for a highway scenario. The drivers were fully distracted by a secondary task, a challenging quiz game on a mobile phone. The different TOR strategies comprised a variation of the location for TOR presentation (integrated mobile phone or in-vehicle HMI) as well as a variation of the TOR modality (TOR with brake jerk/without brake jerk). This paper will present and discuss the results in terms of reaction times and driver behavior strategies to comply with the TOR. It delivers advice on the design of transition strategies between automated and manual driving.