Driving simulators have been used since the beginning of the 1930s to assist researchers in assessing driver behaviour without putting the driver in harm’s way. The current manuscript describes the implementation of a toolbox for automated driving research on the widely used STISIM platform. The toolbox presented in this manuscript allows researchers to conduct flexible research into automated driving, enabling independent use of longitudinal control, and a combination of longitudinal and lateral control, and is available as an open source download through GitHub. The toolbox allows the driver to adjust parameters such as set speed (in 5 kph increments) and time-headway (in steps of 1, 1.5, and 2 s) as well as automation mode dynamically, while logging additional variables that STISIM does not provide out-of-the-box (time-headway, time to collision). Moreover, the toolbox presented in this manuscript has gone through validation trials showing accurate speed, time-headway, and lane tracking, as well as transitions of control between manual and automated driving.@en

This paper summarizes our results from survey research and driving simulator experiments on auditory, vibrotactile, and visual take-over requests in highly automated driving. Our review shows that vibrotactile takeover requests in the driver’s seat yielded relatively high ratings of self-reported usefulness and satisfaction. Auditory take-over requests in the form of beeping sound were regarded as useful but not satisfactory, and it was found that the beep rate corresponds to perceived urgency. Visual-only feedback (LEDs) was regarded by participants as neither useful nor satisfactory. Augmented visual feedback was found to support effective steering and braking actions, and may be a useful compliment to vibrotactile take-over requests. The present findings may be used in the design of take-over requests.@en