Enhancing transportation systems via deep learning: A survey
Abstract Machine learning (ML) plays the core function to intellectualize the transportation
systems. Recent years have witnessed the advent and prevalence of deep learning which …
systems. Recent years have witnessed the advent and prevalence of deep learning which …
A survey on security attacks in VANETs: Communication, applications and challenges
Over the past few decades, the intelligent transportation system (ITS) have emerged with
new technologies and becomes the data-driven ITS, because the substantial amount of data …
new technologies and becomes the data-driven ITS, because the substantial amount of data …
Big data analytics in intelligent transportation systems: A survey
Big data is becoming a research focus in intelligent transportation systems (ITS), which can
be seen in many projects around the world. Intelligent transportation systems will produce a …
be seen in many projects around the world. Intelligent transportation systems will produce a …
Optimized graph convolution recurrent neural network for traffic prediction
Traffic prediction is a core problem in the intelligent transportation system and has broad
applications in the transportation management and planning, and the main challenge of this …
applications in the transportation management and planning, and the main challenge of this …
Deep learning for short-term traffic flow prediction
NG Polson, VO Sokolov - Transportation Research Part C: Emerging …, 2017 - Elsevier
We develop a deep learning model to predict traffic flows. The main contribution is
development of an architecture that combines a linear model that is fitted using ℓ 1 …
development of an architecture that combines a linear model that is fitted using ℓ 1 …
Long short-term memory neural network for traffic speed prediction using remote microwave sensor data
Neural networks have been extensively applied to short-term traffic prediction in the past
years. This study proposes a novel architecture of neural networks, Long Short-Term Neural …
years. This study proposes a novel architecture of neural networks, Long Short-Term Neural …
A gradient boosting method to improve travel time prediction
Y Zhang, A Haghani - Transportation Research Part C: Emerging …, 2015 - Elsevier
Tree based ensemble methods have reached a celebrity status in prediction field. By
combining simple regression trees with 'poor'performance, they usually produce high …
combining simple regression trees with 'poor'performance, they usually produce high …
Travel time prediction with LSTM neural network
Travel time is one of the key concerns among travelers before starting a trip and also an
important indicator of traffic conditions. However, travel time acquisition is time delayed and …
important indicator of traffic conditions. However, travel time acquisition is time delayed and …
Short-term traffic forecasting: Where we are and where we're going
EI Vlahogianni, MG Karlaftis, JC Golias - Transportation Research Part C …, 2014 - Elsevier
Since the early 1980s, short-term traffic forecasting has been an integral part of most
Intelligent Transportation Systems (ITS) research and applications; most effort has gone into …
Intelligent Transportation Systems (ITS) research and applications; most effort has gone into …
Dynamic graph convolution network for traffic forecasting based on latent network of Laplace matrix estimation
Traffic forecasting is a challenging problem in the transportation research field as the
complexity and non-stationary changing of the traffic data, thus the key to the issue is how to …
complexity and non-stationary changing of the traffic data, thus the key to the issue is how to …