Decision-making and planning methods for autonomous vehicles based on multistate estimations and game theory
A core issue inherent to decision-making and path-planning tasks is managing the uncertainties in the motion of dynamic obstacles. Therefore, this article proposes a new decision-making and path-planning framework, based on game theory, that considers the multistate future actions of surrounding veh...
Saved in:
Main Authors: | Yuan, Quan, Yan, Fuwu, Yin, Zhishuai, Lv, Chen, Hu, Jie, Wu, Dongmei, Li, Yue |
---|---|
Other Authors: | School of Mechanical and Aerospace Engineering |
Format: | Article |
Language: | English |
Published: |
2024
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/173920 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Toward trustworthy decision-making for autonomous vehicles: a robust reinforcement learning approach with safety guarantees
by: He, Xiangkun, et al.
Published: (2024) -
Occlusion-free road segmentation leveraging semantics for autonomous vehicles
by: Wang, Kewei, et al.
Published: (2020) -
Toward personalized decision making for autonomous vehicles: a constrained multi-objective reinforcement learning technique
by: He, Xiangkun, et al.
Published: (2023) -
An improved kinematic model predictive control for high-speed path tracking of autonomous vehicles
by: Tang, Luqi, et al.
Published: (2021) -
TRAJECTORY PREDICTION OF DYNAMIC OBSTACLES FOR AUTONOMOUS VEHICLES
by: CHONG YUE LINN
Published: (2020)