The arrival of highly automated vehicles introduces a new interaction between the vehicle and driver. System limitations during highly automated driving require the driver to be ready to take back control at request.
Previous studies on the take-over process concluded that the driver requires a transition period to stabilize vehicle control after resuming manual control. These studies used traded control to instantaneously transfer control back to the driver, causing an abrupt switch in control authority. Therefore, this study explores Haptic Shared Control as a different transition approach. By varying the level of haptic authority, a smooth connection between automation system and driver can be realized. The aim of this study is to investigate if Haptic Shared Control improves the take-over performance compared to the traded control approach. A total of 30 participants drove two trials in a driving simulator, one for each transition approach. Each trial consisted of 10 take-over scenarios divided into two levels of time-criticality. During autonomous driving the participants were engaged in a secondary task. The take-over performance was assessed based on safety performance, lateral vehicle control, controller performance and subjective measures.
Results showed a significant decrease in the standard deviation of the lateral position evaluated over the mean trajectory per participant for the Haptic Shared Control approach compared to traded control. Haptic Shared Control also showed a significant decrease for the mean lateral obstacle clearance. The analyses on torque conflicts revealed a significant increase for critical take-over maneuver compared to non-critical take-over maneuvers.
This suggests that haptic shared control can assist the driver in stabilizing lateral vehicle control after resuming manual control. On the other hand, the driver is limited in performing a sharp evasive maneuver, and this relationship is discussed. More research is needed on using an adaptable human compatible reference.

Research in the motorcycle industry is lagging behind research in the automotive industry. Especially with respect to safety, more research is needed, since motorcycles are overrepresented in the number of road casualties and injuries. Important tools in vehicle research are vehicle simulators. The use of motorcycle simulators enables manufacturers to develop new motorcycle technologies and could make motorcycles safer. Unfortunately, few motorcycle simulators are available, and even fewer are used in the development of new motorcycles and motorcycle safety systems.
This thesis evaluates the Cruden’s six Degrees of Freedom (DoF) motorcycle simulator and shows that it can be used in motorcycle research. To back up this claim, it is showed that a 15-DoF multibody dynamics motorcycle model is used and that the motion platform is capable of having the rider experience dynamics associated with this dynamics model. Furthermore, a human research approach shows that participants experience the same speed perception corresponding as in real-life and that the motion platform is necessary to achieve the highest performance form the rider with respect to lane deviation. Also workload and presence in the virtual environment were significantly better with platform motion. The influence of body tracking has also been investigated but has not demonstrated significant results with respect to the rider’s performance.