Group affiliations

• myCopter - Enabling Technologies for Personal Air Transportation Systems
• Cybernetics Approach to Perception and Action

myCopter

Enabling technologies for personal air transport systems

http://www.mycopter.eu

The volume of road transportation continues to increase and the implied financial and environmental impact fuels public concern. Individual drivers spend considerable time in congested urban agglomerations or highly frequented highways, which leads to significant losses to the European economy.

A Personal Air Transport System (PATS) has been proposed as a radical solution to congestion and as an alternative to current transport systems. A PATS would use Personal Aerial Vehicles (PAV) to bridge the gap between relatively slow cars in a road-based door-to-door system and an air transport system that provides fast and longer journeys to specific locations. Previous projects related to PAVs have focused on the design of the vehicle itself. However, the surrounding issues such as the concept of operations, business models and target users have not been comprehensively considered. This is a necessary requirement for PATS to be operated commercially.

The myCopter project approaches the development of a PATS by investigating the technologies that are needed to enable the operational infrastructure required for the use of PAVs on a large scale. At the Max Planck Institute for Biological Cybernetics, the interaction between the pilot and a vehicle will be investigated. Even though it is likely that a PAV will be autonomous to a high degree, the pilot will be expected to interact with the vehicle. Thus, human-machine interfaces (HMI) should consider the perceptual and cognitive capabilities of the PAV user. We will introduce novel concepts for the interaction between human and the vehicle, and the benefits of, e.g., synthetic vision displays and force feedback will be evaluated in motion simulators.

Multimodel identification of human control behaviour

Human cognitive behaviour can be subdivided into three levels:

1) knowledge-based behaviour that describes high-level problem solving;

2) rule-based behaviour that is determined by rules and behaviour learned in the past; and

3) skill-based behaviour that involves elementary human information processing and basic control tasks.

Considering skill-based behaviour in a simulator environment can provide an objective means to assess the influence of various simulator settings on human control behaviour. By taking a cybernetic approach, skill-based behaviour can be assessed in experimental simulator trials. In this approach, a mathematical model is fit to the measured response of a pilot and changes in the identified parameters serve as a measure for adaptation of human behaviour. By performing tasks in which a pilot tracks a target, while at the same time rejecting a disturbance, a distinction can be identified between the contribution of visual and vestibular senses. Observed changes in the performance measures derived from the measured response of the pilot can be now correlated with changes in identified control behaviour.

The Influence of Simulator Motion System Characteristics on Pilot Control Behavior

Introduction

Full flight simulators are widely being used for training of pilots as they provide a cost-effective alternative over aircraft. However, a compromise must always be found between the amount of motion cueing that needs to be presented to the pilot for effective training and the available workspace of the simulator. In the literature, contradictory reports are found on the effect of motion cues on pilot performance in the simulator.

Goals

The objective of this project is to investigate the influence of simulator motion system quality on human control behavior in closed-loop control tasks [1]. This is done by using a simulated model of the MPI Stewart platform on the SIMONA Research Simulator (SRS) in closed-loop control experiments in which the model parameters that represent motion system characteristics are changed systematically.

Methods

The characteristics of both simulators were determined systematically in selected degrees of freedom [2, 3]. We created a dynamic model of the MPI Stewart platform that was analyzed and compared with the baseline simulator measurements. Measurements for validation of the implementation of the model on the SRS showed that the dynamics of the MPI Stewart platform could be represented well in terms of dynamic range, time delay, and noise characteristics [3].

Results

We performed a closed-loop aircraft pitch control task with nine participants on the SRS [4]. The motion system of the simulator provided the pitch and heave motion cues related to the control task without motion cueing. The most important motion system characteristics of the MPI Stewart platform were simulated on the SRS and the settings of the model were varied independently to represent either the SRS or the MPI Stewart platform. We found that the limited bandwidth of the MPI Stewart platform influenced pilot performance significantly and affected the parameters of the estimated pilot model to a degree that the motion cues were barely used at all. Instead, the participants relied on visual cues for information regarding phase lead concerning the aircraft state. The crossover frequencies and phase margins of the pilot-aircraft open-loop response functions showed decreased performance and increased stability due to the lower bandwidth motion cues.

Conclusion

In this project, we showed that simulator motion system bandwidth has a significant effect on pilot performance and control strategy. Contrary to the motion system bandwidth, the time delay and noise characteristics of the simulators did not have a significant effect on the identified pilot control behavior due to their small influence on the experimental task.

References

1. Nieuwenhuizen, F. M., P. M.T. Zaal, M. Mulder, M. M. van Paassen and J. A. Mulder: Modeling Human Multi-Channel Perception and Control Using Linear Time-Invariant Models. Journal of Guidance, Control, and Dynamics 31(4), 999-1013 (07 2008).
2. Nieuwenhuizen, F. M., K. Beykirch, M. Mulder, M. M. Van Paassen, J. L.G. Bonten and H. H. Bülthoff: Performance Measurements on the MPI Stewart Platform. AIAA Modeling and Simulation Technologies Conference and Exhibit (AIAA 2008), 1-11, American Institute of Aeronautics and Astronautics, Reston, VA, USA (08 2008).
3. Nieuwenhuizen F. M., M. M van Paassen, K. Beykirch, M. Mulder and H. H. Bülthoff: Towards Simulating a Mid-size Stewart Platform on a Large Hexapod Simulator. AIAA Modeling and Simulation Technologies Conference and Exhibit 2009 (AIAA 2010), 1-10, American Institute of Aeronautics and Astronautics, Reston, VA, USA.
4. Nieuwenhuizen, F. M., M. Mulder, M. M. van Paassen and H. H. Bülthoff: The Influence of Motion System Characteristics on Pilot Control Behaviour. AIAA Modeling and Simulation Technologies Conference and Exhibit (AIAA 2011), 1-15, American Institute of Aeronautics and Astronautics, Reston, VA, USA (08 2011).

Frank is a Research Scientist at the Max Planck Institute for Biological Cybernetics on the EU-project "myCopter - Enabling Technologies for Personal Aerial Vehicles" that started in January 2011 (www.mycopter.eu). He is also responsible for management of the project and its dissemination activities.

Frank undertook his Ph.D. research in collaboration with Delft University of Technology. His research focused on investigating the effects of simulator motion system characteristics on pilot control behavioural. He used several techniques to identify pilot behaviour in closed-loop control tasks and assess the influence of motion system properties on human control behaviour.

Frank was born in Haarlem, The Netherlands in March 1981. In September 1999 he started studying at the Faculty of Aerospace Engineering in Delft and graduated in December 2005 on the development of a novel identification technique for pilot control behaviour and its application in an experiment on perception of visual and motion cues during control of self-motion in optic flow environments.