A Deep Reinforcement Learning Approach for Ramp Metering Based on Traffic Video Data
Ramp metering that uses traffic signals to regulate vehicle flows from the on-ramps has been widely implemented to improve vehicle mobility of the freeway. Previous studies generally update signal timings in real-time based on predefined traffic measurements collected by point detectors, such as tra...
Saved in:
Main Authors: | Bing Liu, Yu Tang, Yuxiong Ji, Yu Shen, Yuchuan Du |
---|---|
Format: | article |
Language: | EN |
Published: |
Hindawi-Wiley
2021
|
Subjects: | |
Online Access: | https://doaj.org/article/0baf461d79f44bb9a8d2b843de871cb9 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Way to Automatically Generate Lane Level Traffic Data from Video in the Intersections
by: Zhongguo Yang, et al.
Published: (2021) -
Modeling Tourists’ Departure Time considering the Influence of Multisource Traffic Information
by: Shijun Yu, et al.
Published: (2021) -
The Impact of Automated Vehicles on Traffic Flow and Road Capacity on Urban Road Networks
by: Ji Eun Park, et al.
Published: (2021) -
Relieving the Congestion around a School via Automatic Vehicle Identification Technology-Based Traffic Measures
by: Bo Li, et al.
Published: (2021) -
Study on the Optimization of Hub-and-Spoke Logistics Network regarding Traffic Congestion
by: Wei Xu, et al.
Published: (2021)