Sheng Zhang
ABSTRACT
Speed planning ensures safety and ride comfort, and gives a reasonable driving speed for unmanned ground vehicles. Most velocity planning methods based on arc-length of a given local path are inconvenient when considering comfort constraints such as jerk and safe constraints such as lateral acceleration. In this paper, an innovative method is proposed to establish a speed curve model of multiple segment quadratic curves with respect to time domain, and the adjustment method which is dividing quadratic curves units and preinstalling jerk of local velocity curves under the constraint of different velocity correlation variables is described. In practice, the velocity profile satisfying the constraint is obtained through three steps. The first is multiple iterations which are necessary to change the speed profile. The second is jerk boundary adjustment including safety and comfort. The third step is assigning the velocity value to each point of the local path. Furthermore, Simulation result of unmanned vehicle road entrance ramp merging scenario shows the effectiveness of the proposed method through presetting driving conditions and constraints.
- J. Ziegler, P. Bender, T. Dang, and C. Stiller, “Trajectory planning for bertha – a local, continuous method,” in IEEE Intelligent Vehicles Symposium (IV), 2014, pp. 450–457.Google Scholar
Cross Ref
- M. McNaughton, C. Urmson, J. M. Dolan, and J.-W. Lee, “Motion planning for autonomous driving with a conformal spatiotemporal lattice,” in IEEE International Conference on Robotics and Automation (ICRA), 2011, pp. 4889–4895.Google ScholarCross Ref
- Z. Zhu, E. Schmerling, and M. Pavone, “A convex optimization approach to smooth trajectories for motion planning with car-like robots,” in IEEE 54th Annual Conference on Decision and Control (CDC), 2015, pp. 835–842.Google Scholar
- T. Gu, “Improved trajectory planning for on-road self-driving vehicles via combined graph search, optimization & topology analysis,” Ph.D. dissertation, Carnegie Mellon University, 2017.Google Scholar
- X. Li, Z. Sun, D. Cao, Z. He, and Q. Zhu, “Real-time trajectory planning for autonomous urban driving: Framework, algorithms, and verifications,” IEEE/ASME Transactions on Mechatronics, vol. 21, no. 2, pp. 740–753, apr 2016.Google ScholarCross Ref
- C. Liu, W. Zhan, and M. Tomizuka, “Speed profile planning in dynamic environments via temporal optimization,” in IEEE Intelligent Vehicles Symposium (IV), 2017, pp. 154–159.Google ScholarDigital Library
- T. Lipp and S. Boyd, “Minimum-time speed optimisation over a fixed path,” International Journal of Control, vol. 87, no. 6, pp. 1297–1311, feb 2014.Google ScholarCross Ref
- D. Verscheure, B. Demeulenaere, J. Swevers, J. De Schutter, and M. Diehl, “Time-optimal path tracking for robots: A convex optimization approach,” IEEE Transactions on Automatic Control, vol. 54, no. 10, pp. 2318–2327, oct 2009.Google ScholarCross Ref
- Luca Consolini,Mattia Laurini,Marco Locatelli,Andrea Minari. A solution of the minimum-time speed planning problem based on lattice theory[J]. Journal of the Franklin Institute,2020,357(12).Google Scholar
- S. Balasubramanian, A. Melendezcalderon, A. Robybrami, and E. Burdet, “On the analysis of movement smoothness,” Journal of NeuroEngineering and Rehabilitation, vol. 12, no. 1, p. 112, dec 2015.Google ScholarCross Ref
- Fuguo Xu,Tielong Shen. Look-Ahead Traffic-Based Optimal Velocity Planning for Parallel HEVs[J]. IFAC PapersOnLine,2019,52(5).Google Scholar
- Talamino Jordi Pérez,Sanfeliu Alberto. Anticipatory kinodynamic motion planner for computing the best path and velocity trajectory in autonomous driving[J]. Robotics and Autonomous Systems,2019,114.Google Scholar
- Robotics; Studies from University of Parma Reveal New Findings on Robotics (Optimal Time-complexity Speed Planning for Robot Manipulators)[J]. Journal of Robotics & Machine Learning,2020.Google Scholar
- Yu Zhang, Huiyan Chen, Steven L, Speed Planning for Autonomous Driving via Convex Optimization[C]// 2018 IEEE International Conference on Intelligent Transportation Systems (ITSC). IEEE, 2018.Google Scholar
- Said M. Easa,Maksym Diachuk. Optimal Speed Plan for the Overtaking of Autonomous Vehicles on Two-Lane Highways[J]. Infrastructures,2020,5(5).Google Scholar
Index Terms
- A Speed Planning Method Based on Time Domain of Unmanned Ground Vehicle
Recommendations
Smooth path and speed planning for an automated public transport vehicle
This paper presents a path and speed planner for automated public transport vehicles in unstructured environments. Since efficiency and comfort are two of the key issues in promoting this kind of transportation system, they are dealt with explicitly in ...
Human-like motion planning of autonomous vehicle based on probabilistic trajectory prediction
AbstractMotion planning for autonomous vehicles becomes more challenging when both driver comfort and collision risk are considered. To overcome this challenge, a human-like motion planning strategy based on the probabilistic prediction in a ...
Highlights- Relying on the structural-LSTM network, the trajectory of surrounding vehicles with uncertainty is predicted.
Modelling the vertical dynamics of unmanned ground vehicle with rocker suspension
2017 IEEE International Conference on Mechatronics and Automation (ICMA)In this paper, the vertical dynamic characteristics of unmanned ground vehicle (UGV) with rocker suspension are studied. A mathematical model is established to investigate the vertical dynamic characteristics of three-axle UGV with rocker suspension. This ...
Comments