Real - Time Trajectory and Velocity Planning for Autonomous Vehicles
-
Published:2021-06-30
Issue:5
Volume:10
Page:439-448
-
ISSN:2249-8958
-
Container-title:Regular issue
-
language:en
-
Short-container-title:IJEAT
Author:
Dey Hrishikesh1, Ranadive Rithika1, Chaudhari Abhishek1
Affiliation:
1. Department of Electronics Engineering, VES Institute of Technology, Mumbai (Maharashtra), India.
Abstract
Path planning algorithm integrated with a velocity profile generation-based navigation system is one of the most important aspects of an autonomous driving system. In this paper, a real-time path planning solution to obtain a feasible and collision-free trajectory is proposed for navigating an autonomous car on a virtual highway. This is achieved by designing the navigation algorithm to incorporate a path planner for finding the optimal path, and a velocity planning algorithm for ensuring a safe and comfortable motion along the obtained path. The navigation algorithm was validated on the Unity 3D Highway-Simulated Environment for practical driving while maintaining velocity and acceleration constraints. The autonomous vehicle drives at the maximum specified velocity until interrupted by vehicular traffic, whereas then, the path planner, based on the various constraints provided by the simulator using µWebSockets, decides to either decelerate the vehicle or shift to a more secure lane. Subsequently, a splinebased trajectory generation for this path results in continuous and smooth trajectories. The velocity planner employs an analytical method based on trapezoidal velocity profile to generate velocities for the vehicle traveling along the precomputed path. To provide smooth control, an s-like trapezoidal profile is considered that uses a cubic spline for generating velocities for the ramp-up and ramp-down portions of the curve. The acceleration and velocity constraints, which are derived from road limitations and physical systems, are explicitly considered. Depending upon these constraints and higher module requirements (e.g., maintaining velocity, and stopping), an appropriate segment of the velocity profile is deployed. The motion profiles for all the use-cases are generated and verified graphically.
Publisher
Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP
Subject
Computer Science Applications,General Engineering,Environmental Engineering
Reference23 articles.
1. 1. K. Chu, M. Lee, and M. Sunwoo, "Local path planning for off-road autonomous driving with avoidance of static obstacles," IEEE Transactions on Intelligent Transportation Systems, vol. 13, no. 4, pp. 1599-1616, 2012. 2. 2. C. L. Bianco, A. Piazzi, and M. Romano, "Velocity planning for autonomous vehicles," in IEEE Intelligent Vehicles Symposium, 2004. IEEE, 2004, pp. 413-418. 3. 3. S. Thrun, "Toward robotic cars," Communications of the ACM, vol. 53, no. 4, pp. 99-106, 2010. 4. 4. L. D. Burns, "A vision of our transport future," Nature, vol. 497, no. 7448, pp. 181-182, 2013. 5. 5. J. Kim, K. Jo, D. Kim, K. Chu, and M. Sunwoo, "Behavior and path planning algorithm of autonomous vehicle a1 in structured environments," IFAC Proceedings Volumes, vol. 46, no. 10, pp. 36-41, 2013.
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|