Abstract
This paper presents an approach for plan generation, selection and pruning of trajectories for autonomous driving, capable of dealing with dynamic complex environments, such as driving in urban scenarios. The planner first discretizes the plan space and searches for the best trajectory and velocity profile of the vehicle. The main contributions of this work are the use of \(G^{2}\)-splines for path generation and a method that takes into account accelerations and passenger comfort for generating and pruning velocity profiles based on 3rd order splines, both fulfilling kinodynamic constraints. The proposed methods have been implemented in a motion planner in MATLAB and tested through simulation in different representative scenarios, involving obstacles and other moving vehicles. The simulations show that the planner performs correctly in different dynamic scenarios, maintaining the passenger comfort.
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References
Paden, B., Cáp, M., Zheng Yong, S., Yershov, D., Frazzoli, E.: A survey of motion planning and control techniques for self-driving urban vehicles. IEEE Trans. Intell. Veh. 1(1), 33–55 (2016)
Katrakazas, C., Quddus, M., Chen, W.-H., Deka, L.: Real-time motion planning methods for autonomous on-road driving: State-of-the-art and future research directions. Transp. Res. Part C 60, 416–442 (2015)
Bautista, D.G., Rastelli, J.P., Lattarulo, R., Milanés, V., Nashashibi, F.: Continuous curvature planning with obstacle avoidance capabilities in urban scenarios. In: 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1430–1435 (2014)
Ferguson, D., Howard, T.M., Likhachev, M.: Motion Planning in urban environments, Part I and II. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 1063–1069, 1070–1076 (2008)
Gu, T., Dolan, J.M.: On-road motion planning for autonomous vehicles. In: International Conference on Intelligent Robotics and Applications (ICIRA), vol. 3, pp. 588–597 (2012)
Xu, W., Wei, J., Dolan, J.M., Zhao, H., Zha, H.: A real-time motion planner with trajectory optimization for autonomous vehicles. In: IEEE International Conference on Robotics and Automation (ICRA), pp. 2061–2067 (2012)
Bianco, C.G., Piazzi, A.: Optimal trajectory planning with quintic \(G^{2}\)- splines. In: Proceedings of the IEEE Intelligent Vehicles Symposium, pp. 620–625 (2000)
Hoffmann, G.M., Tomlin, C.J., Montemerlo, M., Thrun, S.: Autonomous automobile trajectory tracking for off-road driving: controller design, experimental validation and racing. In: American Control Conference (ACC), pp. 2296–2301 (2007)
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Talamino, J.P., Sanfeliu, A. (2018). Path and Velocity Trajectory Selection in an Anticipative Kinodynamic Motion Planner for Autonomous Driving. In: Ollero, A., Sanfeliu, A., Montano, L., Lau, N., Cardeira, C. (eds) ROBOT 2017: Third Iberian Robotics Conference. ROBOT 2017. Advances in Intelligent Systems and Computing, vol 694. Springer, Cham. https://doi.org/10.1007/978-3-319-70836-2_36
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DOI: https://doi.org/10.1007/978-3-319-70836-2_36
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