We are pleased to announce that our new paper, "FRENETIX: A High-Performance and Modular Motion Planning Framework for Autonomous Driving," has been published in IEEE Access.

In this paper, we present FRENETIX, a modular motion planning framework designed to enhance the safety and efficiency of autonomous vehicles. Our sampling-based trajectory planning algorithm addresses the complexities of urban navigation, ensuring optimized trajectory comfort, safety, and path precision in both static and highly dynamic environments. To further improve performance, we have implemented the core algorithm in C++, significantly reducing computation times and enhancing real-time capabilities. The modular architecture of FRENETIX allows for the easy integration of various modules, making it adaptable and scalable for different autonomous driving scenarios.

The functionality of our framework has been demonstrated on a real vehicle, showcasing its robustness and reliability in real-world conditions.

The paper is available as open-source and can be accessed here. Additionally, the associated code is accessible for those interested in exploring or building upon our work: Frenetix-Motion-Planner.