A Long-Short-Term Mixed-Integer Formulation for Highway Lane Change Planning
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arXiv
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| Autores principales: | , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| _version_ | 1866916236270501888 |
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| author | Reiter, Rudolf Nurkanovic, Armin Bernadini, Daniele Diehl, Moritz Bemporad, Alberto |
| author_facet | Reiter, Rudolf Nurkanovic, Armin Bernadini, Daniele Diehl, Moritz Bemporad, Alberto |
| contents | This work considers the problem of optimal lane changing in a structured multi-agent road environment. A novel motion planning algorithm that can capture long-horizon dependencies as well as short-horizon dynamics is presented. Pivotal to our approach is a geometric approximation of the long-horizon combinatorial transition problem which we formulate in the continuous time-space domain. Moreover, a discrete-time formulation of a short-horizon optimal motion planning problem is formulated and combined with the long-horizon planner. Both individual problems, as well as their combination, are formulated as MIQP and solved in real-time by using state-of-the-art solvers. We show how the presented algorithm outperforms two other state-of-the-art motion planning algorithms in closed-loop performance and computation time in lane changing problems. Evaluations are performed using the traffic simulator SUMO, a custom low-level tracking model predictive controller, and high-fidelity vehicle models and scenarios, provided by the CommonRoad environment. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_02979 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Long-Short-Term Mixed-Integer Formulation for Highway Lane Change Planning Reiter, Rudolf Nurkanovic, Armin Bernadini, Daniele Diehl, Moritz Bemporad, Alberto Robotics Systems and Control This work considers the problem of optimal lane changing in a structured multi-agent road environment. A novel motion planning algorithm that can capture long-horizon dependencies as well as short-horizon dynamics is presented. Pivotal to our approach is a geometric approximation of the long-horizon combinatorial transition problem which we formulate in the continuous time-space domain. Moreover, a discrete-time formulation of a short-horizon optimal motion planning problem is formulated and combined with the long-horizon planner. Both individual problems, as well as their combination, are formulated as MIQP and solved in real-time by using state-of-the-art solvers. We show how the presented algorithm outperforms two other state-of-the-art motion planning algorithms in closed-loop performance and computation time in lane changing problems. Evaluations are performed using the traffic simulator SUMO, a custom low-level tracking model predictive controller, and high-fidelity vehicle models and scenarios, provided by the CommonRoad environment. |
| title | A Long-Short-Term Mixed-Integer Formulation for Highway Lane Change Planning |
| topic | Robotics Systems and Control |
| url | https://arxiv.org/abs/2405.02979 |