Multilayer Graph-Based Trajectory Planning for Race Vehicles in Dynamic Scenarios
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Abstract (arXiv)
Trajectory planning at high velocities and at the handling limits is a challenging task. In order to cope with the requirements of a race scenario, we propose a far-sighted two step, multi-layered graph-based trajectory planner, capable to run with speeds up to 212~km/h. The planner is designed to generate an action set of multiple drivable trajectories, allowing an adjacent behavior planner to pick the most appropriate action for the global state in the scene. This method serves objectives such as race line tracking, following, stopping, overtaking and a velocity profile which enables a handling of the vehicle at the limit of friction. Thereby, it provides a high update rate, a far planning horizon and solutions to non-convex scenarios. The capabilities of the proposed method are demonstrated in simulation and on a real race vehicle.
Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). First posted on arXiv 18 May 2020.
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Citing papers per year: 2021: 1; 2022: 3; 2023: 2; 2024: 4; 2025: 1; 2026: 3.
14 papers.
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- 2022Autonomous Vehicles on the Edge: A Survey on Autonomous Vehicle Racingcited by 56
- 2021Learn-to-Race: A Multimodal Control Environment for Autonomous Racingcited by 23
- 2024FRENETIX: A High-Performance and Modular Motion Planning Framework for Autonomous Drivingcited by 14
- 2022Indy Autonomous Challenge -- Autonomous Race Cars at the Handling Limitscited by 10
- 2022Motion Planning and Control for Multi Vehicle Autonomous Racing at High Speedscited by 8
- 2023er.autopilot 1.0: The Full Autonomous Stack for Oval Racing at High Speedscited by 2
- 2024A Simulation Benchmark for Autonomous Racing with Large-Scale Human Datacited by 2
- 2024Fast and Modular Autonomy Software for Autonomous Racing Vehiclescited by 2
- 2026EgoDyn-Bench: Evaluating Ego-Motion Understanding in Vision-Centric Foundation Models for Autonomous Drivingcited by 2
- 2023Partial End-to-end Reinforcement Learning for Robustness Against Modelling Error in Autonomous Racingcited by 1
- 2024An Online Spatial-Temporal Graph Trajectory Planner for Autonomous Vehiclescited by 1
- 2025Reinforcement Learning-based Dynamic Adaptation for Sampling-Based Motion Planning in Agile Autonomous Drivingcited by 0
- 2026Driving Context-guided Model Predictive Planning and Control for Autonomous Car Racing at the Limit and Beyond11 Sep 2026
- 2026EgoDyn-Bench: Evaluating Ego-Motion Understanding in Vision-Centric Foundation Models for Autonomous Driving22 Apr 2026
- 2026LLM-Driven Scenario-Aware Planning for Autonomous Driving29 Jan 2026
- 2025Reinforcement Learning-based Dynamic Adaptation for Sampling-Based Motion Planning in Agile Autonomous Driving12 Oct 2025
- 2024Fast and Modular Autonomy Software for Autonomous Racing Vehicles27 Aug 2024
- 2024A Simulation Benchmark for Autonomous Racing with Large-Scale Human Data23 Jul 2024
- 2024An Online Spatial-Temporal Graph Trajectory Planner for Autonomous Vehicles18 Apr 2024
- 2024FRENETIX: A High-Performance and Modular Motion Planning Framework for Autonomous Driving2 Feb 2024
- 2023Partial End-to-end Reinforcement Learning for Robustness Against Modelling Error in Autonomous Racing11 Dec 2023
- 2023er.autopilot 1.0: The Full Autonomous Stack for Oval Racing at High Speeds27 Oct 2023
- 2022Motion Planning and Control for Multi Vehicle Autonomous Racing at High Speeds22 Jul 2022
- 2022Autonomous Vehicles on the Edge: A Survey on Autonomous Vehicle Racing14 Feb 2022
- 2022Autonomous Vehicles on the Edge: A Survey on Autonomous Vehicle Racingcited by 56
- 2024FRENETIX: A High-Performance and Modular Motion Planning Framework for Autonomous Drivingcited by 14
- 2024An Online Spatial-Temporal Graph Trajectory Planner for Autonomous Vehiclescited by 1
- 2025Reinforcement Learning-based Dynamic Adaptation for Sampling-Based Motion Planning in Agile Autonomous Drivingcited by 0
- 2026LLM-Driven Scenario-Aware Planning for Autonomous Drivingcited by 0
- 2026Driving Context-guided Model Predictive Planning and Control for Autonomous Car Racing at the Limit and Beyondcited by 0
- 2026Driving Context-guided Model Predictive Planning and Control for Autonomous Car Racing at the Limit and Beyond11 Sep 2026
- 2026LLM-Driven Scenario-Aware Planning for Autonomous Driving29 Jan 2026
- 2025Reinforcement Learning-based Dynamic Adaptation for Sampling-Based Motion Planning in Agile Autonomous Driving12 Oct 2025
- 2024An Online Spatial-Temporal Graph Trajectory Planner for Autonomous Vehicles18 Apr 2024
- 2024FRENETIX: A High-Performance and Modular Motion Planning Framework for Autonomous Driving2 Feb 2024
- 2022Autonomous Vehicles on the Edge: A Survey on Autonomous Vehicle Racing14 Feb 2022
- 2021Learn-to-Race: A Multimodal Control Environment for Autonomous Racingcited by 23
- 2022Indy Autonomous Challenge -- Autonomous Race Cars at the Handling Limitscited by 10
- 2022Motion Planning and Control for Multi Vehicle Autonomous Racing at High Speedscited by 8
- 2023er.autopilot 1.0: The Full Autonomous Stack for Oval Racing at High Speedscited by 2
- 2024A Simulation Benchmark for Autonomous Racing with Large-Scale Human Datacited by 2
- 2024Fast and Modular Autonomy Software for Autonomous Racing Vehiclescited by 2
- 2023Partial End-to-end Reinforcement Learning for Robustness Against Modelling Error in Autonomous Racingcited by 1
- 2024Fast and Modular Autonomy Software for Autonomous Racing Vehicles27 Aug 2024
- 2024A Simulation Benchmark for Autonomous Racing with Large-Scale Human Data23 Jul 2024
- 2023Partial End-to-end Reinforcement Learning for Robustness Against Modelling Error in Autonomous Racing11 Dec 2023
- 2023er.autopilot 1.0: The Full Autonomous Stack for Oval Racing at High Speeds27 Oct 2023
- 2022Motion Planning and Control for Multi Vehicle Autonomous Racing at High Speeds22 Jul 2022
- 2022Indy Autonomous Challenge -- Autonomous Race Cars at the Handling Limits8 Feb 2022
- 2021Learn-to-Race: A Multimodal Control Environment for Autonomous Racing22 Mar 2021