Truck Traffic Speed Prediction Under Non-Recurrent Congestion: Based on Optimized Deep Learning Algorithms and GPS Data

Truck Traffic Speed Prediction Under Non-Recurrent Congestion: Based on Optimized Deep Learning Algorithms and GPS Data

Due to the restriction of traffic management measure in large cities, large heavy-haul trucks can only travel on the circuits and expressways around the city, which often causes congestion in these areas. It is necessary to study the travel speed prediction of trucks on the urban ring road and provi...

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Bibliographic Details
Main Authors: Jiandong Zhao, Yuan Gao, Zhenzhen Yang, Jiangtao Li, Yingzi Feng, Ziyan Qin, Zhiming Bai
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
GPS data
GRU model
optimization algorithm
traffic congestion
traffic speed prediction
Online Access:https://ieeexplore.ieee.org/document/8598930/

Internet

https://ieeexplore.ieee.org/document/8598930/

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