Real time integrated vehicle dynamics control and trajectory planning with MPC for critical maneuvers

Yi, Boliang; Gottschling, Stefan; Ferdinand, Jens; Simm, Norbert; Bonarens, Frank; Stiller, Christoph

doi:10.1109/ivs.2016.7535446

Cited by 32 publications

(15 citation statements)

References 4 publications

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“…The generally non-convex motion planning problem can be approximated as a convex problem, e.g., by linearizing the non-linear, non-holonomic vehicle dynamics [44], [45] and separating the motion into a longitudinal and a lateral component [46]. The resulting convex optimization problems can be efficiently solved with global convergence as succesfully shown in [47]- [51].…”

Section: A Literature Overviewmentioning

confidence: 99%

Fail-Safe Motion Planning for Online Verification of Autonomous Vehicles Using Convex Optimization

Pek

Althoff

2021

IEEE Trans. Robot.

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Section: A Literature Overviewmentioning

confidence: 99%

Fail-Safe Motion Planning for Online Verification of Autonomous Vehicles Using Convex Optimization

Pek

Althoff

2021

IEEE Trans. Robot.

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“…A similar approach utilizing more advanced collision avoidance constraints is described by Gutjahr and Werling [17]. Yi et al [18] propose an approach to MPC-based trajectory planning for critical driving maneuvers. They introduce a quadratic MPC problem for considering friction limits in evasion maneuvers.…”

Section: Related Workmentioning

confidence: 99%

“…Further research will focus on the integration of tire dynamics (e.g. as proposed by Yi et al [18]). Additionally we will extend the implementation of the self-aware MPC approach to vehicle dynamics control at the lower stabilization level (e.g.…”

Section: Conclusion and Future Researchmentioning

confidence: 99%

Model predictive control based trajectory generation for autonomous vehicles — An architectural approach

Nolte

Rose

Stolte

et al. 2017

2017 IEEE Intelligent Vehicles Symposium (IV)

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Abstract-Research in the field of automated driving has created promising results in the last years. Some research groups have shown perception systems which are able to capture even complicated urban scenarios in great detail. Yet, what is often missing are general-purpose path-or trajectory planners which are not designed for a specific purpose. In this paper we look at path-and trajectory planning from an architectural point of view and show how model predictive frameworks can contribute to generalized pathand trajectory generation approaches for generating safe trajectories even in cases of system failures.c 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

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“…In addition to rules [13][14][15] the stand-on vessel should keep her speed and course. However, if it is apparent that the giveway vessel is not taking action to avoid collision, the stand-on vessel is required to apply actions to best avoid collision.…”

Section: The International Regulations For Preventing Collisionsmentioning

confidence: 99%

“…Constrained optimization in the form of model predictive control (MPC) has already been applied for automotive COLAV [12,13]. The use of MPC for ASV COLAV has been investigated in [10], however only using brute-force techniques by discretization of the search space in a finite number of control inputs.…”

Section: Introductionmentioning

confidence: 99%

MPC-Based mid-level collision avoidance for asvs using nonlinear programming

Eriksen

Breivik

2017

2017 IEEE Conference on Control Technology and Applications (CCTA)

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Abstract-In this paper, we present a mid-level collision avoidance algorithm for autonomous surface vehicles (ASVs) based on model predictive control (MPC) using nonlinear programming. The algorithm enables avoidance of both static and moving obstacles, and following of a desired nominal trajectory if there is no danger of collision. We compare two alternative objective functions, where one is a quadratic function and the other is a nonlinear function designed to produce maneuvers observable for other vessels in compliance with rule 8 of the International Regulations for Preventing Collisions at Sea (COLREGS). The algorithm is implemented in the CASADI framework and uses the IPOPT solver. The performance of the algorithm is evaluated through simulations which show promising results. Furthermore, the algorithm is considered computationally feasible to run in real time. This algorithm serves as a base algorithm for further development in order to ensure full COLREGS compliance.

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Real time integrated vehicle dynamics control and trajectory planning with MPC for critical maneuvers

Cited by 32 publications

References 4 publications

Fail-Safe Motion Planning for Online Verification of Autonomous Vehicles Using Convex Optimization

Fail-Safe Motion Planning for Online Verification of Autonomous Vehicles Using Convex Optimization

Model predictive control based trajectory generation for autonomous vehicles — An architectural approach

MPC-Based mid-level collision avoidance for asvs using nonlinear programming

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