Human learning of the vehicle steering task is identified as an important process, the understanding of which may aid the design and development of vehicle dynamic behaviour. Existing driver models are reviewed and it is apparent that little attention has been given to the learning process

This paper investigates the relationship between “error feedback ” (when tracking or trajectory errors are made) and user performance in steering tasks. We conducted experiments to examine feedback presented as visual, auditory and tactile modalities, both individually and in combinations

Fisheye views use distortion to provide both local detail and global context in a single continuous view. However, the distorted presentation can make it more difficult to interact with the data; it is therefore not clear whether fisheye views are good choices for interactive tasks. To investigate

Path steering is a primitive 3D interaction task that requires the user to navigate through a path of a given length and width. In a previous paper, we have conducted controlled experiments in which users operated a pen input device to steer a cursor through a 3D path subject to fixed path

Although two papers [8, 9] present studies on steering tasks, they used feedback as “affirmative ” feedback for guidance and affirmation. Affirmative feedback has been shown to be beneficial especially for the older and/or visually impaired population as it confirms that they are on the right track

to estimate the steering wheel angle required to follow a desired path. To provide a physiologically realistic steering manoeuvre, a musculoskeletal arm model considering the neuromuscular system is included in the driver model. This driver model can provide insights into task performance and energy

Oriented filters are useful in many early vision and image processing tasks. One often needs to apply the same filter, rotated to different angles under adaptive control, or wishes to calculate the filter response at various orientations. We present an efficient architecture to synthesize filters

discussed. GSAT is best viewed as a model-finding procedure. Its good performance suggests that it may be advantageous to reformulate reasoning tasks that have traditionally been viewed as theorem-proving problems as model-finding tasks.

evidence that rotation and scale are significant factors in interaction performance. We propose a model based on these factors that can be employed to predict the time required for a task of tracing and staying inside a non-linear shape. Contrary to our initial hypothesis, moderate translation changes did

expressions. These have been successfully applied to diverse tasks such as design, diagnosis, truth maintenance, scheduling, spatiotemporal reasoning, logic programming and user interface. Constraint networks are graphical representations used to guide strategies for solving constraint satisfaction problems