Generic Trajectory Planning Algorithm for Urban Autonomous Driving

Thibaud Duhautbout (1, 2) , Reine Talj (1) , Véronique Cherfaoui (1) , François Aioun (2) , Franck Guillemard (2)

1 Heudiasyc - Heuristique et Diagnostic des Systèmes Complexes [Compiègne]
2 Stellantis - PSA Centre Technique de Vélizy

In this paper, a new local planning algorithm for urban autonomous driving is presented. Our main contribution is to define a fully algorithmic method, based on a geometrical representation of the environment, to compute predictive speed profiles on multiple paths, to ensure safety and comfort with respect to the scene and its predicted evolution. Simulation results are provided to evaluate the behaviour of the proposed algorithm on various scenarios. Those results show a good, comfortable and safe reaction of the vehicle to its static and dynamic environment with processing times compatible with real-time control. Environment Sensors Perception (sensor data fusion) Road network (HD map) Destination Global planning (Route planning in the road network) Decision (high-level semantic analysis) Local planning (generation of a local trajectory) Control Actuators Vehicle mission path useful data decision path D + Qlat static obstacles visibility limits dynamic obstacles predictions reference trajectory vehicle state

Domaines: Automatique / Robotique

Thibaud Duhautbout, Reine Talj, Véronique Cherfaoui, François Aioun, Franck Guillemard. Generic Trajectory Planning Algorithm for Urban Autonomous Driving. 20th International Conference on Advanced Robotics (ICAR 2021), Dec 2021, Ljubljana, Slovenia. pp.607-612. ⟨hal-03456575⟩