Up until today, high fidelity dynamic motorcycle riding simulators (DMRS) lack behind the rideability and accessibility of real motorcycles. This is a limiting factor when it comes to the applicability of such simulators in the development processes of motorcycle manufacturers, suppliers and research institutes. Extensive training of the study participants can help to overcome issues with a simulator’s rideability and accessibility and therefore enables valid studies. However, it decreases the test efficiency due to the timely effort and weakens the trust of managers and decision makers into the results gained on the simulator. One approach to increase the rideability of DMRS is to introduce a technology, that allows utilizing rider motion as an input to the simulation, instead of only implementing a steering input. This approach is called “Dual Loop Rider Control” (DLRC) and is realized on the DESMORI simulator by measuring the rider induced roll torque that takes any coupling torque between the rider and the motorcycle frame around the vehicle’s longitudinal axis into account (Pleß, 2016). The objective of the paper at hand is to discuss if and how the applicability and performance of DLRC in dynamic riding maneuvers can be rated. Scales and ratings known from literature, that are for example applied for the analysis of motorcycle handling, are not sufficient for this purpose. For instance, the Lane-Change-Roll Index will decrease when implementing DLRC and utilizing leaning (vs. riding with steering input only). Typically, such lower steer torque efforts would indicate improved handling ratings. But ultimately, they have no relevance in terms of rideability, accessibility and realism of the simulator, as these qualities cannot be boiled down to lower steering efforts. Thus, there is the need for new objective performance measures. It is hypothesized that an increased rideability of the simulator is observable in a higher precision and repeatability when performing a lane change maneuver. A set of characteristic values describing this maneuver is presented to objectively evaluate the performance of the simulator. The values result from a curve fitting of the vehicle trajectory to a hyperbolic tangent function. In order to investigate the effects of DLRC on these characteristic values, the lane change maneuver is tested at velocities between 30 km/h and 100 km/h in three different configurations: pure steering control, pure leaning control and DLRC. The collected data highlights the effectiveness of the added leaning input and indicates slight improvements in rideability of the lane change maneuver. However, the objective performance ratings still don’t suffice to draw a precise picture of the gain in rideability through DLRC.

Whenever driving simulators are used in research and development, to a certain extent the generalizability of the gained results is subject to discussion. Typically, a simulator gets validated in a rather effortful and complex process to prove the adequacy of the use of this specific simulator as research tool for a given research question. Traditionally, there is a differentiation between a simulator’s physical validity and its behavioral validity. Whilst the first focusses on the simulator’s behavior and the presence of specific cues and operating elements, the latter focusses on the driver’s perception and consequently behavior. Furthermore, the degree of accordance between vehicle and simulator forms a category of validity, namely, absolute, and relative validity. Whilst absolute validity describes an absolute numerical accordance of measurable dimensions between vehicle and simulator (e.g., certain forces, accelerations), relative validity describes a correlational accordance. Independent of the addressed dimension, simulator validation is a highly complex process, which is specific to the respective research question for which the simulator gets validated (e.g., training race riders vs. assessing distraction caused by human-machine interfaces, HMI). Regarding single-track vehicle simulator concepts for which there is less experience from previous research, a rather broad validation procedure would be a useful tool to assess a simulator’s overall characteristics and therefore to assess its potential fields of application on a wider basis. This paper addresses this gap and presents such a methodological validation approach applied to motorcycle riding simulators. The main assumption of the method is that complex riding tasks can be divided into smaller units that allow for discrimination of specific rider input characteristics, the so-called minimal scenarios. These minimal scenarios are riding tasks such as ‘starting from standstill’ or ‘initiating a curve at constant velocity’. Furthermore, it is assumed that minimal scenarios can be reorganized to more complex riding tasks. This is intended to describe the variety of potential applications with a necessary minimum of elementary tasks to reduce the validation effort for a global assessment of the simulator’s capabilities. This more generic result can also be regarded as a limitation. The proposed empirical evidence from participant studies on a static, a dynamic motorcycle riding simulator as well as a reference ride on a real motorcycle suggests that the validation approach can be beneficial.

Whenever driving simulators are used in research and development, to a certain extent the generalizability of the gained results is subject to discussion. Typically, a simulator gets validated in a rather effortful and complex process in order to prove the adequacy of the use of this specific simulator as research tool for a given research question. This paper proposes a new methodological approach to assess a simulator’s overall characteristics and therefore to assess its potential fields of application on a wider basis. The methodology was developed focusing on motorcycle riding simulators.