Marcel Walch

Exploring the design space of graphical passwords on smartphones

Smartphones have emerged as a likely application area for graphical passwords, because they are easier to input on touchscreens than text passwords. Extensive research on graphical passwords and the capabilities of modern smartphones result in a complex design space for graphical password schemes on smartphones. We analyze and describe this design space in detail. In the process, we identify and highlight interrelations between usability and security characteristics, available design features, and smartphone capabilities. We further show the expressiveness and utility of the design space in the development of graphical passwords schemes by implementing five different existing graphical password schemes on one smartphone platform. We performed usability and shoulder surfing experiments with the implemented schemes to validate identified relations in the design space. From our results, we derive a number of helpful insights and guidelines for the design of graphical passwords.

Towards Cooperative Driving: Involving the Driver in an Autonomous Vehicle's Decision Making

Although there are already fully autonomous vehicles on the roads for testing purposes, a rollout is far away. Autonomous vehicles are still not able to handle everyday driving and remain reliant on the driver when they reach their system limitations. One suggested approach to this problem is handing over the control entirely to the driver, which might become annoying when such situations occur frequently. In contrast, we suggest the usage of cooperative interfaces to avoid full handovers in situations in which the system needs the driver, for instance to approve or monitor a specific maneuver. A driving simulator study with 32 participants revealed that they felt comfortable choosing how the system should handle a situation. They reportedly assessed the situations first instead of relying blindly on the system and were able to handle every situation safely. We report lessons learned regarding cooperative interaction and interfaces, and their in-lab evaluation.

MIBA: multitouch image-based authentication on smartphones

Graphical password schemes can provide better usability than text passwords, especially on smartphones where typing complex passwords on a virtual keyboard can be tedious. However, in order to achieve password strength comparable to text passwords, graphical password schemes require multiple rounds and, therefore, have longer entry times. We propose MIBA as an image-based authentication method that leverages multitouch in order to increase the password space by supporting multiple fingers for click point selection. We outline the MIBA concept, report on practical constraints for multitouch click point selection, and discuss preliminary results that indicate short entry times and the usability of MIBA.

homeBLOX: making home automation usable

Home automation aims to increase convenience of residential living. The homeBLOX system uses a process-driven execution model to enable complex automation tasks with heterogeneous devices, while providing a user interface that abstracts from lower-level complexity. Complex automation tasks are created as sequences consisting of events and actions linked to physical and virtual devices, which are translated into BPEL code for execution. We outline the key concepts, architecture, and prototype of our system.

homeBLOX: introducing process-driven home automation

Home automation promises more convenience for residential living. We propose process-driven home automation as an approach to reduce the difficulty of specifying automation tasks without restricting users in terms of customizability and complexity of supported scenarios. Our graph-based user interface abstracts from the complexity of process specification, while created sequences are automatically translated into BPEL code for execution. Our homeBLOX architecture extends a process engine with the capabilities to communicate with heterogeneous smart devices, integrate virtual devices, and support different home automation protocols. We report on initial user tests with our automation interface and demonstrate the customizability and expressiveness of our system based on realized example use cases.

From Car-Driver-Handovers to Cooperative Interfaces: Visions for Driver–Vehicle Interaction in Automated Driving

As long as automated vehicles are not able to handle driving in every possible situation, drivers will still have to take part in the driving task from time to time. Recent research focused on handing over control entirely when automated systems reach their boundaries. Our overview on research in this domain shows that handovers are feasible, however, they are not a satisfactory solution since human factor issues such as reduced situation awareness arise in automated driving. In consequence, we suggest to implement cooperative interfaces to enable automated driving even with imperfect automation. We recommend to consider four basic requirements for driver–vehicle cooperation: mutual predictability, directability, shared situation representation, and calibrated trust in automation. We present research that can be seen as a step towards cooperative interfaces in regard to these requirements. Nevertheless, these systems are only solutions for parts of future cooperative interfaces and interaction concepts. Future design of interaction concepts in automated driving should integrate the cooperative approach in total in order to achieve safe and comfortable automated mobility.

Exploring End User Programming Needs in Home Automation

Home automation faces the challenge of providing ubiquitous, unobtrusive services while empowering users with approachable configuration interfaces. These interfaces need to provide sufficient expressiveness to support complex automation, and notations need to be devised that enable less tech-savvy users to express such scenarios. Rule-based and process-oriented paradigms have emerged as opposing ends of the spectrum; however, their underlying concepts have not been studied comparatively. We report on a contextual inquiry study in which we collected qualitative data from 18 participants in 12 households on the current potential and acceptance of home automation, as well as explored the respective benefits and drawbacks of these two notation paradigms for end users. Results show that rule-based notations are sufficient for simple automation tasks but not flexible enough for more complex use cases. The resulting insights can inform the design of interfaces for smart homes to enable usable real-world home automation for end users.

Elaborating Feedback Strategies for Maintaining Automation in Highly Automated Driving

Human errors are a major reason for traffic accidents. One of the aims of the introduction of automated driving functions in vehicles is to prevent such accidents as such systems are supposed to be more reliable, react faster with higher precision. Therefore, we assume that an increase of automation features will also increase safety. However, when drivers are not willing to relinquish control to the vehicle, safety benefits of automated vehicles do not take effect. Therefore, convincing drivers to actively make use of the automation when appropriate can increase traffic safety. In this paper we investigate the influence of system feedback in proactive, safety critical takeover situations in automated driving. In contrast to handover, which is initiated by the system, proactive takeover is initiated by the driver, whos intention for steering the car is the reason for driving manually. We compare auditory feedback with audio-visual feedback realized as a virtual co-driver in a user study. We conducted a virtual reality simulator study (n=38) to investigate how system feedback influences the willingness of drivers to relinquish control to the vehicle. There were three conditions of system feedback: in condition none no feedback was given, in condition audio spoken feedback was given, and in condition co-driver additionally to audio feedback, a virtual co-driver on the front passenger seat was displayed. Our research provides evidence that system feedback can lead to an increase of willingness to maintain automation and to follow its safety related advices.

Evaluating VR Driving Simulation from a Player Experience Perspective

The majority of HCI research in the field of automotive interfaces and driver-vehicle interaction is conducted utilizing driving simulators. High-fidelity simulators are expensive; in consequence, many researchers use consumer gaming hardware and flat screens as an alternative. In recent years VR devices have become affordable and are applied already in some driving studies. It has not been shown whether driving simulations can use VR to increase immersion in low-cost setups. We conducted a pilot study with 20 participants using a racing game as simulation software. The results of this pilot study indicate that using a VR headset can potentially dissociate participants to a higher degree from the real world compared to the use of flat screens. However, participants felt a higher discomfort using the VR HMD. Despite expectations, todays VR technology does not appear to be a generally better choice than flat screens for driving simulator studies.

Carvatar: Increasing Trust in Highly-Automated Driving Through Social Cues

While driving in highly automated new problems occur which are not present in manual driving. Highly automated cars have different internal states which take into account, what was detected, were the car is and to which maneuvers this could lead. One problem is that the driver may not be able to see in which state the car is currently because the functionality is too complex. If drivers are not able to compare the cars actions to the actions they would have performed themselves they might have trouble trusting the system. It is not apparent what the car recognizes and which future actions are planned. Our avatar uses social cues and anthropomorphism to translate the cars state into human behavior and expressions which can be interpreted intuitively by the driver. The driver is therefore more aware of the situation and might gain more trust in the system.