Obstacle Avoidance Path Planning based on Output Constrained Model Predictive Control
- 46 Downloads
Image processing and control technologies have been widely studied and autonomous vehicles have become an active research area. For autonomous driving, it is essential to generate a safe obstacle avoidance path considering the surrounding environment. This paper devised an algorithm based on a real-time output constrained model predictive control for obstacle avoidance path planning in high speed driving situations. The proposed algorithm was compared with the normal model predictive control algorithm by simulation, including operation times to verify robustness for high speed driving situations. We used the ISO 2631-1 comfort level standard to quantify driver comfort fo r both cases.
KeywordsComfort level model predictive control obstacle avoidance path planning vehicle dynamics
Unable to display preview. Download preview PDF.
- K. P. Carroll, S. R. McClaran, E. L. Nelson, D. M. Barnett, D. K. Friesen, and G. N. William, “AUV path planning: an A* approach to path planning with consideration of variable vehicle speeds and multiple, overlapping, timedependent exclusion zones,” Proceedings of the IEEE 1992 Symposium on Autonomous Underwater Vehicle Technology, AUV’92, pp. 79–84, 1992.CrossRefGoogle Scholar
- C. Wang, L. Wang, J. Qin, Z. Wu, L. Duan, Z. Li, M. Cao, X. Ou, X. Su, W. Li, Z. Lu, M. Li, Y. Wang, J. Long, M. Huang, Y. Li, and Q. Wang, “Path planning of automated guided vehicles based on improved A-Star algorithm,” Proceedings of the 2015 IEEE International Conference on Information and Automation, pp. 2071–2076, 2015.CrossRefGoogle Scholar
- J. M. Maestre and R. R. Negenborn, Distributed Model Predictive Control Made Easy, Springer, vol. 69, 2014.Google Scholar
- X. Qian, A. De Lav Fortelle, and F. Moutarde, “A hierarchical model predictive control framework for on-road formation control of autonomous vehicles,” Proceeding of the IEEE Intelligent Vehicles Symposium (IV), pp. 376–381, 2016.Google Scholar
- H. J. Kim, D. H. Shim, and S. Sastry, “Nonlinear model predictive tracking control for rotorcraft-based unmanned aerial vehicles,” Proceedings of the IEEE American Control Conference, vol. 5, pp. 3576–3581, 2002.Google Scholar
- I. O. for Standardization, Mechanical vibration and shock-Evaluation of human exposure to whole-body vibration-Part 1: General requirements. The Organization, 1997.Google Scholar
- M. Nolte, M. Rose, T. Stolte, and M. Maurer, “Model predictive control based trajectory generation for autonomous vehicles-an architectural approach,” arXiv preprint arXiv:1708.02518, 2017.Google Scholar
- E. F. Camacho and C. B. Alba, Model Predictive Control, Springer Science & Business Media, 2013.Google Scholar
- T. D. Gillespie, Vehicle Dynamics, Warren Dale, 1997.Google Scholar
- H. Pacejka, Tire and Vehicle Dynamics, Elsevier, 2005.Google Scholar