Freeway Traffic Speed Prediction under the Intelligent Driving Environment: A Deep Learning Approach
The intelligent transportation system (ITS) has been proven capable of effectively addressing traffic congestion issues. For vehicles to perform effectively and improve mobility under the intelligent driving environment, real-time prediction of traffic speed is undoubtedly essential. Considering the...
Saved in:
Main Authors: | Chengying Hua, Wei (David) Fan |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2022-01-01
|
Series: | Journal of Advanced Transportation |
Online Access: | http://dx.doi.org/10.1155/2022/6888115 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Speed Distribution Prediction of Freight Vehicles on Mountainous Freeway Using Deep Learning Methods
by: Yuren Chen, et al.
Published: (2020-01-01) -
Traffic Flow Modeling of Freeway Variable Speed Limit Control Based on the Big Data of Driving Behavior
by: Xu Qu, et al.
Published: (2020-01-01) -
Variable Speed Limit Control Method of Freeway Mainline in Intelligent Connected Environment
by: Xingju Wang, et al.
Published: (2021-01-01) -
Freeway Traffic Speed Estimation of Mixed Traffic Using Data from Connected and Autonomous Vehicles with a Low Penetration Rate
by: Shanglu He, et al.
Published: (2020-01-01) -
A Comprehensive Review on Traffic Control Modeling for Obtaining Sustainable Objectives in a Freeway Traffic Environment
by: Muhammad Sameer Sheikh, et al.
Published: (2022-01-01)