The Role of Task and Situational Characteristics on the Dependability of Human-Technology Interaction

While the impact of "human error" on failures of complex human-technology systems has widely been demonstrated and accepted, the relevance of situational and task-related characteristics on human performance has not yet been considered sufficiently. For this purpose and on the example of electrically powered wheel chair control this paper analyzes the effects of situational characteristics ( e.g., turns to the left/right in the backward/forward driving mode) on the impact of fine motor abilities on human performance. A study with 23 participants is described in the paper, during which relevant data such as the subjects' precision and aiming capacity, the number of collisions caused while driving as an indicator for human performance, and the situational characteristics were measured. The data analyses demonstrate an influence of especially the number of turns driven to the right in the backward mode on the impact of the precision ability on the number of safety-critical collisions. The results highlight the necessity not only to develop a wheelchair system which is adaptable to the user’s fine motor abilities, but also to the situational characteristics in order to increase the dependability of the human-technology system at hand

Dependable System Design for Assistance Systems for Electrically Powered Wheelchairs

In this paper a system design approach is proposed, which is based on a user needs assessment and a flexible and adaptable architecture for dependable system integration. The feasibility of the approach is shown on the example of an assistance system for electrically powered wheelchairs. The system requirements correspond to the cognitive and motor abilities of the wheelchair users. For the wheelchair system built up based on a commercial powered wheelchair several behaviors have been realized such as collision avoidance, local navigation and path planning well known from robotic systems, which are enhanced by human-interfacing components. Furthermore, the system design will be high lighted which is based on robotic systems engineering. Due to the fundamental properties of the system architecture the resulting assistance system is inherently dependable, flexible, and adaptable. Corresponding to the current situation and the users’ abilities the system changes the level of assistance during real-time operation. The resulting system behavior is evaluated using system performance and usability tests

The Impact of Individual Differences in Fine Motor Abilities on Wheelchair Control Behavior and Especially on Safety-Critical Collisions with Objects in the Surroundings

In order to significantly reduce the number of safety-critical collisions of wheelchair users with objects spread in their environment, a study has been conducted which relates wheelchair user's fine motor abilities with the collisions while driving through a standardized course in a realistic office environment. The conducted inferential statistics demonstrate that especially the participants' aiming capacity can sign significantly predict the collisions occurring while driving through the course. A graphical and qualitative analysis of these effects demonstrates in addition that specific maneuvering tasks influence this relationship and that especially driving next to an object without colliding requires a high level of aiming capacity. The results demonstrate the need to develop a wheelchair system which adapts its assistive functionality to the aiming capacity and the difficulty of the maneuvering task in order to provide as much help as necessary without risking the degradation of the wheelchair user's skills

Modeling Driving Behavior at Roundabouts: Impact of Roundabout Layout and Surrounding Traffic on Driving Behavior

Driving behavior prediction at roundabouts is an important challenge to improve driving safety by supporting drivers with intelligent assistance systems. To predict the driving behavior effciently steering wheel status was proven to have robust predictability based on a Support Vector Machine algorithm. Previous research has not considered potential effects of roundabout layout and surrounding traffic on driving behavior, but that consideration can certainly improve the prediction results. Therefore, this study investigated how roundabout layout and surrounding traffic impact driving behavior of an ego car. A simulator study was conducted to collect driving behavior data with different roundabout layout settings and different surrounding cyclist position settings. The local minima/maxima of the steering angle was found to have a logarithmic relationship with the roundabout geometric feature. The impact of the surrounding traffic on the ego driver behavior was also found: When there were surrounding cyclists, the recognition rate of ego driver behavior patterns reached 100% later than when there was no surrounding traffic. In conclusion, driving behavior at roundabouts is effected by both roundabout layout and surrounding traffic, and the relationship can be expressed in a quantitative way