Simulated Annealing-optimized Trajectory Planning within Non-Collision Nominal Intervals for Highway Autonomous Driving
Laurène Claussmann, Marc Revilloud, Sébastien Glaser · 2019
This article considers the problem of near-optimal trajectory generation for autonomous vehicles on highways. The goal is to select a predictive reference trajectory in the free evolution space, while avoiding both generating a pre-calculated set of candidate trajectories and decoupling path and velocity optimizations. Moreover, this trajectory aims at optimizing a decision process based on multi-criteria functions, which are not straightforward to design and can have a blackbox formulation. The main idea of this article is to use the decision evaluation function in the trajectory generator with a Simulated Annealing (SA) approach. The parameters of a sigmoid trajectory are optimized within Non-Collision Nominal Intervals (NCNI), which are defined as collision-free intervals under nominal conditions using a velocity-space representation.