Abstract
This paper presents a framework for motion planning of autonomous vehicles, it is characterized by its efficient computation and its safety guarantees. An optimal control based approach generates comfortable and physically feasible maneuvers of the vehicle. Therefore, a combined optimization of the lateral and longitudinal movements in street-relative coordinates with carefully chosen cost functionals and terminal state sets is performed. The collision checking of the trajectories during the planning horizon is also performed in street-relative coordinates. It provides continuous collision checking, which covers nearly all situations based on an algebraic solution and has a constant response time. Finally, the problem of safety assessment for partial trajectories beyond the planning horizon is addressed. Therefore, the Inevitable Collision States (ICS) are used, extending the safety assessment to an infinite time horizon. To solve the ICS computation nonlinear programming is applied. An example implementation of the proposed framework is applied to simulation scenarios that demonstrates its efficiency and safety capabilities.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsNotes
- 1.
no restrictions such as obstacles.
References
Althoff, M., Mergel, A.: Comparison of Markov chain abstraction and Monte Carlo simulation for the safety assessment of autonomous cars. IEEE Trans. Intell. Transp. Syst. PP(99):1–11 (2011).
Althoff, D., Werling, M., Kaempchen, N., Buss, D.M.: Lane-based safety assessment of road scenes using inevitable collision states. Proceedings of the IEEE Intelligent Vehicles Symposium, Wollherr, In (2012)
Bronstein, M., Cohen, A.M., Cohen, H., Eisenbud, D., Sturmfels, B.: Solving Polynomial Equations. vol. 14, pp. 51–63. Springer, Berlin (2005).
Fraichard, T., Asama, H.: Inevitable collision states. A step towards safer robots? Adv. Robot. 18, 1001–1024 (2004)
Fraichard, T.: A short paper about motion safety. In: Proceedings of the IEEE International Conference on Robotics and Automation, pp. 1140–1145 (2007)
Petti, S., Fraichard, T.: Safe motion planning in dynamic environments. Proceedings of the IEEE International Conference on Intelligent Robots and Systems, In (2005)
Resende, P., Nashashibi, F.: Real-time dynamic trajectory planning for highly automated driving in highways. Proceedings of Intelligent Transportation Systems, In (2010)
Stewart, I.: Galois Theory. Chapman and Hall, London (1973)
Werling, M., Kammel, S., Ziegler, J., Gröll, L.: Optimal trajectories for time-critical street scenarios using discretized terminal manifolds. Int. J. Robot. Res. 31(3):346–359 (2012)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Althoff, D., Buss, M., Lawitzky, A., Werling, M., Wollherr, D. (2012). On-line Trajectory Generation for Safe and Optimal Vehicle Motion Planning. In: Levi, P., Zweigle, O., Häußermann, K., Eckstein, B. (eds) Autonomous Mobile Systems 2012. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32217-4_11
Download citation
DOI: https://doi.org/10.1007/978-3-642-32217-4_11
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-32216-7
Online ISBN: 978-3-642-32217-4
eBook Packages: EngineeringEngineering (R0)