In the passenger car and truck sector, assistance systems that intervene in emergency situations and thus help to improve vehicle safety have already been successfully used for many years. Although motorcyclists are subject to a high risk of suffering severe or fatal injuries in road traffic, systems that actively intervene in emergency situations are not yet available in the motorcycle sector. One reason for this is that passenger car systems cannot easily be adapted due to the motorcycle specific single-track vehicle dynamics. There are characteristic challenges that set limits to the possible application of actively intervening assistance systems. Exceeding these limits when applying an assistance system on a motorcycle could result in the occurrence of new critical situations that are no longer controllable for the rider. Still, previous research concludes that assistance systems for motorcycles have the potential to increase riding safety and identifies autonomous emergency braking systems for motorcycles (MAEB) as one of the most promising technologies (Savino et al., 2013). One major challenge in MAEB studies is the conflict of goals between the aim to optimize the effectiveness of MAEB by identifying maximum possible decelerations that can be applied in a safe way and the wish to evaluate ‘natural’ rider reactions to an autonomous braking intervention. For the latter, riders should not anticipate the autonomous deceleration in order to achieve unbiased results. Obviously, it is ethically unacceptable to determine feasible deceleration limits with unprepared study participants. Approaching these limits carries the risk of provoking critical situations. During the research described in the paper at hand, a multi-phase approach was developed, in order to overcome the trade-off between achieving maximum effectiveness of braking interventions by identifying maximum feasible decelerations on the one hand and on the other hand evaluating unbiased reactions of unprepared riders. While other research groups focus on urban riding scenarios at velocities up to 50 km/h in their MAEB research (e.g., Lucci et al., 2021), the investigations described here concentrate on higher velocities as they occur in rural scenarios. Throughout the research described in this paper, the developed investigation method was exemplarily applied to a prototype MAEB system. The paper provides an overview of the major results of all three phases of MAEB assessment. The method proves to be appropriate and delivers promising results regarding the applicability of autonomous emergency braking systems for motorcycles in the evaluated scenarios. The reproducibility of the measured rider reactions creates confidence that the corresponding effects are predictable, which means that the rider behavior does not represent a completely incalculable safety-critical factor for the application of MAEB. The successful application of the method leads to the conclusion that it can serve as a basis for the release of systems that intervene in the longitudinal dynamics. It gives manufacturers and system suppliers the opportunity to systematically prove that their systems are controllable for end users and can be applied without causing additional risks. Thus, the method can contribute to the future use of safety-enhancing assistance systems for motorcycles.

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. Since decades, there is plenty of research regarding the methods to validate simulators mainly from the automotive domain (e.g., Blaauw, 1982; Blana, 1996). 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 (e.g., Cossalter, Lot, Massaro, & Sartori, 2011; Grottoli, Mulder, & Happee, 2022), a rather broad validation procedure could be a useful tool in order to assess a simulator’s overall characteristics and therefore to assess its potential fields of application on a wider basis. This paper 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 in order to reduce the validation effort for a global assessment of the simulator’s capabilities (Hammer, Pleß, Will, Neukum, & Merkel, 2021). 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.

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 enables valid studies, but decreases the test efficiency 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 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 means of a roll torque measurement 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 lean-ing (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. A set of characteristic values describing this maneuver is presented, that aims at objectively rating 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.

This paper describes the development of an investigation method to prove the applicability of autonomous emergency braking systems for motorcycles. The method allows to show that MAEB can be used without causing incalculable risks and thus it can contribute to the future use of safety-enhancing assistance systems on motorcycles.

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.