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Path Planning for Autonomous Platoon Formation
| Content Provider | MDPI |
|---|---|
| Author | Ganaoui-Mourlan, Ouafae El Camp, Stephane Hannagan, Thomas Arora, Vaibhav Neuville, Martin De Kousournas, Vaios |
| Copyright Year | 2021 |
| Description | In the context of automated highway systems (AHS), this work proposes an approach that enables a vehicle to autonomously join a platoon with optimized trajectory in the presence of dynamical traffic obstacles. A notable aspect is the use of Model Predictive Control (MPC) optimization of the planned path, in conjunction with a variant of the Rapidly-exploring Random Trees (RRT*) algorithm for the purpose of platoon formation. This combination efficiently explores the space of possible trajectories, returning trajectories that are smoothened out with respect to the dynamic constraints of the vehicle, while at the same time allowing for real-time implementation. The implementation we propose takes into consideration both localization and mapping through relevant sensors and V2V communication. The complete algorithm is tested over various nominal and worst-case scenarios, qualifying the merits of the proposed methodology. |
| Starting Page | 4668 |
| e-ISSN | 20711050 |
| DOI | 10.3390/su13094668 |
| Journal | Sustainability |
| Issue Number | 9 |
| Volume Number | 13 |
| Language | English |
| Publisher | MDPI |
| Publisher Date | 2021-04-22 |
| Access Restriction | Open |
| Subject Keyword | Sustainability Transportation Science and Technology Autonomous Vehicle Platoon Formation Path Planning Model Predictive Control Rrt Rrt* Optimization |
| Content Type | Text |
| Resource Type | Article |
