Spatiotemporal traffic forecasting: review and proposed directions
A Ermagun, D Levinson - Transport Reviews, 2018 - Taylor & Francis
This paper systematically reviews studies that forecast short-term traffic conditions using
spatial dependence between links. We extract and synthesise 130 research papers …
spatial dependence between links. We extract and synthesise 130 research papers …
A hybrid deep learning based traffic flow prediction method and its understanding
Deep neural networks (DNNs) have recently demonstrated the capability to predict traffic
flow with big data. While existing DNN models can provide better performance than shallow …
flow with big data. While existing DNN models can provide better performance than shallow …
Feature selection and extraction in spatiotemporal traffic forecasting: a systematic literature review
D Pavlyuk - European Transport Research Review, 2019 - Springer
A spatiotemporal approach that simultaneously utilises both spatial and temporal
relationships is gaining scientific interest in the field of traffic flow forecasting. Accurate …
relationships is gaining scientific interest in the field of traffic flow forecasting. Accurate …
Evaluation of short‐term freeway speed prediction based on periodic analysis using statistical models and machine learning models
Accurate prediction of traffic information (ie, traffic flow, travel time, traffic speed, etc.) is a key
component of Intelligent Transportation System (ITS). Traffic speed is an important indicator …
component of Intelligent Transportation System (ITS). Traffic speed is an important indicator …
Road2vec: Measuring traffic interactions in urban road system from massive travel routes
Good characterization of traffic interactions among urban roads can facilitate traffic-related
applications, such as traffic control and short-term forecasting. Most studies measure the …
applications, such as traffic control and short-term forecasting. Most studies measure the …
Forecasting vehicular traffic flow using MLP and LSTM
DD Oliveira, M Rampinelli, GZ Tozatto… - Neural Computing and …, 2021 - Springer
This work presents an analysis of Artificial Neural Network (ANN) based forecasting models
for vehicular traffic flow. The forecasting was performed for three periods of time: 1 week, 1 …
for vehicular traffic flow. The forecasting was performed for three periods of time: 1 week, 1 …
Link traffic speed forecasting using convolutional attention-based gated recurrent unit
G Khodabandelou, W Kheriji, FH Selem - Applied Intelligence, 2021 - Springer
Traffic speed forecasting becomes a thriving research area in modern transportation
systems. The intensification of travel flow volumes due to fast urbanization, vehicle path …
systems. The intensification of travel flow volumes due to fast urbanization, vehicle path …
Lane-level traffic speed forecasting: A novel mixed deep learning model
Lane-level traffic state prediction is one of the most essential issues in the connected
automated vehicle highway systems. Accurate and timely traffic state prediction of the lane …
automated vehicle highway systems. Accurate and timely traffic state prediction of the lane …
Short-term prediction of demand for ride-hailing services: A deep learning approach
L Chen, P Thakuriah, K Ampountolas - Journal of Big Data Analytics in …, 2021 - Springer
As ride-hailing services become increasingly popular, being able to accurately predict
demand for such services can help operators efficiently allocate drivers to customers, and …
demand for such services can help operators efficiently allocate drivers to customers, and …
Spatiotemporal short-term traffic forecasting using the network weight matrix and systematic detrending
A Ermagun, D Levinson - Transportation Research Part C: Emerging …, 2019 - Elsevier
This study examines the spatiotemporal dependency between traffic links. We model the
traffic flow of 140 traffic links in a sub-network of the Minneapolis-St. Paul highway system for …
traffic flow of 140 traffic links in a sub-network of the Minneapolis-St. Paul highway system for …