In order to foster situated learning in a virtual community of practice, we developed a multi-user, real-time, 3D car-driving simulation environment. In such a situation-based learning environment, the availability of enough appropriate learning situations is crucial for success. However, we experienced that often a collaborative usage of the system does not result in a large number of these cr...

Due to limited operational space, in dynamic driving simulators it is common practice to implement motion cueing algorithms that tilt the simulator cabin to reproduce sustained accelerations. In order to avoid conflicting inertial cues, the tilt rate is kept below drivers’ perceptual thresholds, which are typically derived from the results of classical vestibular research where additional senso...

This contribution presents an approach for a scientific driving simulator platform for the representation and evaluation of new driver assistance and information systems. We will give a short introduction to the used gaming engine and then present the developed components of our new driving simulation platform. For a most realistic driving behavior, we implemented an own physics-component basin...

In this paper, we apply tools from inverse reinforcement learning (IRL) to the problem of learning from (unlabeled) demonstration trajectories of behavior generated by varying “intentions” or objectives. We derive an EM approach that clusters observed trajectories by inferring the objectives for each cluster using any of several possible IRL methods, and then uses the constructed clusters to qu...

A driving simulator was used to assess performance in younger and older drivers (M ages 18 and 71 years). The impacts of three challenges were assessed: visibility (clear day, fog), traffic density (low, high) and wayfinding (no challenge, drivers challenged to use signs and landmarks to find their destination). Performance was measured in terms of hazard RT, collisions, wayfinding errors (miss...

Driving simulators have been widely used to investigate driver behavior and psychophysiological responses. In this paper, we proposed to use multiple participant-operated driving simulators which communicate with each other so the platoon formed by the simulators can demonstrate realistic effects of driver-driver interaction in simulation scenarios. In our preliminary experiment, three driving ...

In our study, we generate rules to determine whether or not a driver is cognitively distracted, using collected data about the driver’s eye movements and driving data by Inductive Logic Programming (ILP). We assigned a mental arithmetic task to the research participants to cause cognitive distraction and then learned the rules of the cognitive distraction using the cognitively distracted state ...

In a driving simulator study, we explore the feasibility of using pupil diameter to estimate how the cognitive load of the driver changes during a spoken dialogue with a remote conversant. We confirm that it is feasible to use pupil diameter to differentiate between parts of the dialogue that increase the cognitive load of the driver, and those that decrease it. Our long term goal is to build a...

A study in the static driving simulator examines whether the use of an Emissive Projection Display (EPD) causes significant effects on attention and cognitive load in addition to the driving task. Moreover, a comparison with a conventional Head-Up Display (HUD) is drawn. Conclusions regarding the driver’s stress resulting parallel to the driving task are objectively determined by reaction times...

Cell phone conversations distract drivers. This research explores the possibility of reducing distracting by providing callers with a remote display of the driver’s traffic. We asked whether providing such contextual information would change the caller’s conversation such that drivers would be less distracted. In Experiment 1 we examined this question in a low-fidelity driving simulator; in Exp...