Short-term traffic forecasting: An LSTM network for spatial-temporal speed prediction
Traffic forecasting remains an active area of research in the transport and data science
fields. Decision-makers rely on traffic forecasting models for both policy-making and …
fields. Decision-makers rely on traffic forecasting models for both policy-making and …
Unidirectional and bidirectional LSTM models for short‐term traffic prediction
This paper presents the development and evaluation of short‐term traffic prediction models
using unidirectional and bidirectional deep learning long short‐term memory (LSTM) neural …
using unidirectional and bidirectional deep learning long short‐term memory (LSTM) neural …
Transferability improvement in short-term traffic prediction using stacked LSTM network
Short-term traffic flow forecasting is a key element in Intelligent Transport Systems (ITS) to
provide proactive traffic state information to road network operators. A variety of methods to …
provide proactive traffic state information to road network operators. A variety of methods to …
Utilizing attention-based multi-encoder-decoder neural networks for freeway traffic speed prediction
A Abdelraouf, M Abdel-Aty… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Speed prediction is a crucial yet complicated task for intelligent transportation systems. The
challenge derives from the complex spatiotemporal dependencies of traffic parameters. In …
challenge derives from the complex spatiotemporal dependencies of traffic parameters. In …
Data-driven short-term forecasting for urban road network traffic based on data processing and LSTM-RNN
W Xiangxue, X Lunhui, C Kaixun - Arabian Journal for Science and …, 2019 - Springer
A short-term traffic flow prediction framework is proposed for urban road networks based on
data-driven methods that mainly include two modules. The first module contains a set of …
data-driven methods that mainly include two modules. The first module contains a set of …
A combined deep learning method with attention‐based LSTM model for short‐term traffic speed forecasting
Short‐term traffic speed prediction is a promising research topic in intelligent transportation
systems (ITSs), which also plays an important role in the real‐time decision‐making of traffic …
systems (ITSs), which also plays an important role in the real‐time decision‐making of traffic …
Multi-lane short-term traffic forecasting with convolutional LSTM network
Short-term traffic prediction consists a crucial component in intelligent transportation
systems. With the explosion of automated traffic monitoring sensors and the flourishing of …
systems. With the explosion of automated traffic monitoring sensors and the flourishing of …
Short‐term traffic speed forecasting based on attention convolutional neural network for arterials
Q Liu, B Wang, Y Zhu - Computer‐Aided Civil and Infrastructure …, 2018 - Wiley Online Library
As an important part of the intelligent transportation system (ITS), short‐term traffic prediction
has become a hot research topic in the field of traffic engineering. In recent years, with the …
has become a hot research topic in the field of traffic engineering. In recent years, with the …
Predicting short-term traffic flow by long short-term memory recurrent neural network
Y Tian, L Pan - 2015 IEEE international conference on smart …, 2015 - ieeexplore.ieee.org
Intelligent Transportation System (ITS) is a significant part of smart city, and short-term traffic
flow prediction plays an important role in intelligent transportation management and route …
flow prediction plays an important role in intelligent transportation management and route …
Development and evaluation of bidirectional LSTM freeway traffic forecasting models using simulation data
Long short-term memory (LSTM) models provide high predictive performance through their
ability to recognize longer sequences of time series data. More recently, bidirectional deep …
ability to recognize longer sequences of time series data. More recently, bidirectional deep …