Gratzer, A. L., Broger, M. M., Schirrer, A., & Jakubek, S. (2023). Flatness-Based Mixed-Integer Obstacle Avoidance MPC for Collision-Safe Automated Urban Driving. In 2023 9th International Conference on Control, Decision and Information Technologies (CoDIT) (pp. 1844–1849). IEEE. https://doi.org/10.1109/CoDIT58514.2023.10284415
2023 9th International Conference on Control, Decision and Information Technologies (CoDIT)
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Event date:
3-Jul-2023 - 6-Jul-2023
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Event place:
Rom, Italy
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Number of Pages:
6
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Publisher:
IEEE
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Peer reviewed:
Yes
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Keywords:
obstacle avoidance; model predictive control (MPC); flatness-based control; mixed-integer programming; motion planning; trajectory planning
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Abstract:
Safe and efficient obstacle avoidance is a challenging feature in the urban automated driving context. This paper proposes an optimal flatness-based modular obstacle-avoidance model-predictive control strategy. Exploiting differential flatness, a unified obstacle-avoidance MPC formulation in the linearized flat coordinates is devised, based on the well-known mixed-integer Big-M formulation to resolve the non-convex avoidance constraints. Various choices of flat outputs (Cartesian vs. Frenet path coordinates) can be utilized with appropriate transformations, allowing a unified, efficient, and globally optimal solution of the obstacle-avoidance MPC problem. The resulting control law is tested in a multi-agent traffic simulation and shows excellent performance in a typical complex urban intersection scenario.
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Project title:
Intelligent Intersection: 880830 (FFG - Österr. Forschungsförderungs- gesellschaft mbH)
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Research Areas:
Sustainable and Low Emission Mobility: 10% Modeling and Simulation: 30% Automation and Robotics: 60%