Motion cueing literature#

This page contains a list of motion cueing related literature not published by any of the MPMCA authors, but very much worth reading. Do you want to get your publication listed? Send us a message.

  1. Pham, D.-A., Pham, T. N., & Nguyen, D.-T. (2023). Novel model predictive control-based motion cueing algorithm for compensating centrifugal acceleration in kuka robocoaster-based driving simulators. Science Progress, 106(4), 00368504231204759. https://doi.org/10.1177/00368504231204759 ↩

  2. Chadha, A., Jain, V., Lazcano, A. M. R., & Shyrokau, B. (2023). Computationally-efficient motion cueing algorithm via model predictive control. 2023 Ieee International Conference on Mechatronics (Icm), 1–6. https://doi.org/10.1109/ICM54990.2023.10101964 ↩

  3. Lamprecht, A., Steffen, D., Nagel, K., Haecker, J., & Graichen, K. (2022). Online model predictive motion cueing with real-time driver prediction. IEEE Transactions on Intelligent Transportation Systems, 23(8), 12414–12428. https://doi.org/10.1109/TITS.2021.3114003 ↩

  4. Kolff, M., Venrooij, J., Schwienbacher, M., Pool, D., & Mulder, M. (2022, October). Motion cueing quality comparison of driving simulators using oracle motion cueing. Driving Simulation Conference 2022 Europe. https://research.tudelft.nl/files/143790909/2022\_Kolff\_ProcDSC.pdf ↩

  5. Biemelt, P., Link, C., Gausemeier, S., & Trächtler, A. (2020). A model-based online reference prediction strategy for model predictive motion cueing algorithms. IFAC-PapersOnLine, 53(2), 6082–6088. https://doi.org/https://doi.org/10.1016/j.ifacol.2020.12.1681 ↩

  6. Kolff, M., Venrooij, J., Pool, D. and, & Mulder, M. (2020, October). Comparison of quality metrics between motion cueing algorithms in a virtual test environment. Driving Simulation Conference 2020 Europe. https://research.tudelft.nl/files/86424946/DSC\_2020\_Paper\_BMW\_VTE\_FINAL.PDF ↩

  7. Ellensohn, F., Spannagl, M., Agabekov, S., Venrooij, J., Schwienbacher, M., & Rixen, D. (2020). A hybrid motion cueing algorithm. Control Engineering Practice, 97, 104342. https://doi.org/https://doi.org/10.1016/j.conengprac.2020.104342 ↩

  8. Koyuncu, A. B., Erçelik, E., Comulada-Simpson, E., Venrooij, J., Kaboli, M., & Knoll, A. (2020). A novel approach to neural network-based motion cueing algorithm for a driving simulator. 2020 Ieee Intelligent Vehicles Symposium (Iv), 2118–2125. https://doi.org/10.1109/IV47402.2020.9304825 ↩

  9. Cleij, D. (2020). Measuring, modelling and minimizing perceived motion incongruence: For vehicle motion simulation [PhD thesis, Delft University of Technology]. https://doi.org/10.4233/uuid:45fd3f70-2ba6-43fa-a2c4-018967bfdc88 ↩

  10. Erler, P. (2020). Untersuchung von vorausschauenden motion-cueing-algorithmen in einem neuartigen längsdynamischen fahrsimulator (pp. XIII, 165Seiten). Shaker. https://doi.org/https://doi.org/10.25534/tuprints-00011838 ↩

  11. Cleij, D., Venrooij, J., Pretto, P., Katliar, M., Bülthoff, H., Steffen, D., Hoffmeyer, F., & Schöner, H.-P. (2019). Comparison between filter- and optimization-based motion cueing algorithms for driving simulation. Transportation Research Part F: Traffic Psychology and Behaviour, 61, 53–68. https://doi.org/https://doi.org/10.1016/j.trf.2017.04.005 ↩

  12. Ellensohn, F., Schwienbacher, M., Venrooij, J., & Rixen, D. (2019). Motion cueing algorithm for a 9-dof driving simulator: MPC with linearized actuator constraints. SAE International Journal of Connected and Automated Vehicles, 2(3), 145–155. https://doi.org/https://doi.org/10.4271/12-02-03-0010 ↩

  13. Ellensohn, F., Venrooij, J., Schwienbacher, M., & Rixen, D. (2019). Experimental evaluation of an optimization-based motion cueing algorithm. Transportation Research Part F: Traffic Psychology and Behaviour, 62, 115–125. https://doi.org/https://doi.org/10.1016/j.trf.2018.12.004 ↩

  14. Lamprecht, A., Steffen, D., Haecker, J., & Graichen, K. (2019). Optimal control based reference generation for model predictive motion cueing algorithms. 2019 Ieee Conference on Control Technology and Applications (Ccta), 203–208. https://doi.org/10.1109/CCTA.2019.8920421 ↩

  15. Lamprecht, A., Steffen, D., Haecker, J., & Graichen, K. (2019). Comparison between a filter- and an mpc-based mca in an offline simulator study. In A. Kemeny, F. Colombet, F. Merienne, & S. Espié (Eds.), Proceedings of the driving simulation conference 2019 europe vr (pp. 101–107). Driving Simulation Association. ↩

  16. Mulder, M., Pool, D., van der El, K., Drop, F., & van Paassen, M. (2019). Manual control with pursuit displays: New insights, new models, new issues. IFAC-PapersOnLine, 52(19), 139–144. https://doi.org/https://doi.org/10.1016/j.ifacol.2019.12.125 ↩

  17. Mohammadi, A., Asadi, H., Mohamed, S., Nelson, K., & Nahavandi, S. (2019). Multiobjective and interactive genetic algorithms for weight tuning of a model predictive control-based motion cueing algorithm. IEEE Transactions on Cybernetics, 49(9), 3471–3481. https://doi.org/10.1109/TCYB.2018.2845661 ↩

  18. Asadi, H., Lim, C. P., Mohammadi, A., Mohamed, S., Nahavandi, S., & Shanmugam, L. (2018). A genetic algorithm–based nonlinear scaling method for optimal motion cueing algorithm in driving simulator. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 232, 1025–1038. https://doi.org/10.1177/0959651818772940 ↩

  19. Biemelt, P., Henning, S., Rüddenklau, N., Gausemeier, S., & Trächtler, A. (2018). A model predictive motion cueing strategy for a 5-degree-of-freedom driving simulator with hybrid kinematics. In A. Kemeny, F. Colombet, F. Merienne, & S. Espié (Eds.), Proceedings of the driving simulation conference 2018 europe vr (pp. 79–85). Driving Simulation Association. ↩

  20. Cleij, D., Venrooij, J., Pretto, P., Pool, D. M., Mulder, M., & Bülthoff, H. H. (2018). Continuous subjective rating of perceived motion incongruence during driving simulation. IEEE Transactions on Human-Machine Systems, 48(1), 17–29. https://doi.org/10.1109/THMS.2017.2717884 ↩

  21. Lamprecht, A., Haecker, J., & Graichen, K. (2018). Constrained motion cueing for driving simulators using a real-time nonlinear mpc scheme. 2018 Ieee/Rsj International Conference on Intelligent Robots and Systems (Iros), 7466–7471. https://doi.org/10.1109/IROS.2018.8594246 ↩

  22. Fang, Z., Tsushima, M., Kitahara, E., Machida, N., Wautier, D., & Kemeny, A. (2017). Fast mpc based motion cueing algorithm for a 9DOF driving simulator with yaw table. In A. Kemeny, F. Colombet, F. Merienne, & S. Espié (Eds.), Proceedings of the driving simulation conference 2017 europe vr (pp. 73–80). Driving Simulation Association. ↩

  23. Venrooij, J., Cleij, D., Katliar, M., Pretto, P., Bülthoff, H., Steffen, D., Hoffmeyer, F., & Schöner, H.-P. (2016, September). Comparison between filter- and optimization-based motion cueing in the daimler driving simulator. Driving Simulation Conference 2016 Europe. https://www.researchgate.net/profile/Joost-Venrooij/publication/308078848\_Comparison\_between\_filter-\_and\_optimization-based\_motion\_cueing\_in\_the\_Daimler\_Driving\_Simulator/links/57d95eff08ae5f03b49a04d2/Comparison-between-filter-and-optimization-based-motion-cueing-in-the-Daimler-Driving-Simulator.pdf ↩

  24. Mohammadi, A., Asadi, H., Mohamed, S., Nelson, K., & Nahavandi, S. (2016, December). Future reference prediction in model predictive control based driving simulators. Australasian Conference on Robotics and Automation (Acra2016). ↩

  25. Beghi, A., Bruschetta, M., & Maran, F. (2012). A real time implementation of mpc based motion cueing strategy for driving simulators. 2012 Ieee 51st Ieee Conference on Decision and Control (Cdc), 6340–6345. https://doi.org/10.1109/CDC.2012.6426119 ↩

  26. Dagdelen, M., Reymond, G., Kemeny, A., Bordier, M., & Maïzi, N. (2009). Model-based predictive motion cueing strategy for vehicle driving simulators. Control Engineering Practice, 17(9), 995–1003. https://doi.org/https://doi.org/10.1016/j.conengprac.2009.03.002 ↩

  27. Dagdelen, M., Reymond, G., Kemeny, A., Bordier, M., & Maı̈ki, N. (2004). MPC based motion cueing algorithm: Development and application to the ultimate driving simulator. DSC 2004 Europe (Driving Simulation Conference), 221–233. ↩