Modeling adaptive platoon and reservation based autonomous intersection control: a deep reinforcement learning approach
As a strategy to reduce travel delay and enhance energy efficiency, platooning of connected and autonomous vehicles (CAVs) at non-signalized intersections has become increasingly popular in academia. However, few studies have attempted to model the relation between the optimal platoon size and the t...
Saved in:
Main Authors: | Li, Duowei, Wu, Jianping, Zhu, Feng, Chen, Tianyi, Wong, Yiik Diew |
---|---|
Other Authors: | School of Civil and Environmental Engineering |
Format: | Conference or Workshop Item |
Language: | English |
Published: |
2022
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/158101 https://heart2022.com/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Modeling adaptive platoon and reservation-based intersection control for connected and autonomous vehicles employing deep reinforcement learning
by: Li, Duowei, et al.
Published: (2023) -
Simulation and modeling for full self-driving platoons with human factors in smart city
by: Meng, Qunyao
Published: (2024) -
Analytical analysis of the effect of maximum platoon size of connected and automated vehicles
by: Zhou, Jiazu, et al.
Published: (2022) -
Transferable deep reinforcement learning framework for autonomous vehicles with joint radar-data communications
by: Nguyen, Quang Hieu, et al.
Published: (2023) -
Autonomous cruise control using neural networks in platooning
by: Huang, S.N., et al.
Published: (2014)