Spline-Based Motion Planning for Automated Driving. Issue 1 (July 2017) - Götte, Christian; Keller, Martin; Nattermann, Till; Haß, Carsten; Glander, Karl-Heinz; Bertram, Torsten
Abstract: The paper at hand proposes an efficient trajectory planning approach for automated vehicles. The concept of potential field based online trajectory optimization is enhanced by a spline-based interpolation strategy, valid for normal driving functions. The resulting benefits of the developed Timed Elastic Spline (TES) approach concern improvements in computational efficiency and faster convergence and thus effect the computation time. An optimization algorithm is applied to generate the optimal trajectory considering the objectives of collision avoidance and comfort. The results show the performance of the developed algorithm, which is designed to solve a broad range of traffic scenarios. Additionally measurements indicate that the algorithm is suitable for real time application.