Research on Integrated Control Strategy for Highway Merging Bottlenecks Based on Collaborative Multi-Agent Reinforcement Learning
The merging behavior of vehicles at entry ramps and the speed differences between ramps and mainline traffic cause merging traffic bottlenecks. Current research, primarily focusing on single traffic control strategies, fails to achieve the desired outcomes. To address this issue, this paper explores...
Saved in:
Main Authors: | Juan Du, Anshuang Yu, Hao Zhou, Qianli Jiang, Xueying Bai |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2025-01-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/15/2/836 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Hadoop bottleneck detection algorithm based on information gain
by: Zaole TAN, et al.
Published: (2016-07-01) -
Design and Prototype of an Automatic Highway Streetlight Intensity Control System.
by: Wafula, Moses
Published: (2024) -
IALight: Importance-Aware Multi-Agent Reinforcement Learning for Arterial Traffic Cooperative Control
by: Lu WEI, et al.
Published: (2025-02-01) -
RECYCLING - VECTOR OF THE CIRCULAR ECONOMY. SYSTEM ANALYSIS FROM THE BOTTLENECK THEORY PERSPECTIVE
by: Elena Mihaela ILIESCU, et al.
Published: (2024-05-01) -
Genetic Variation and Bottleneck Tests in Iraqi Native Cows of Babylon Province by STR Markers
by: Hayder R. Alnajm, et al.
Published: (2024-12-01)