Short-term speed predictions exploiting big data on large urban road networks

G Fusco, C Colombaroni, N Isaenko - Transportation Research Part C …, 2016 - Elsevier
Big data from floating cars supply a frequent, ubiquitous sampling of traffic conditions on the
road network and provide great opportunities for enhanced short-term traffic predictions …

Long-term urban traffic speed prediction with deep learning on graphs

JQ James, C Markos, S Zhang - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Traffic speed prediction is among the foundations of advanced traffic management and the
gradual deployment of internet of things sensors is empowering data-driven approaches for …

Short-term traffic predictions on large urban traffic networks: Applications of network-based machine learning models and dynamic traffic assignment models

G Fusco, C Colombaroni, L Comelli… - … Conference on Models …, 2015 - ieeexplore.ieee.org
The paper discusses the issues to face in applications of short-term traffic predictions on
urban road networks and the opportunities provided by explicit and implicit models. Different …

Short‐term highway traffic flow prediction based on a hybrid strategy considering temporal–spatial information

L Li, S He, J Zhang, B Ran - Journal of Advanced …, 2016 - Wiley Online Library
Short‐term traffic flow prediction is fundamental for the intelligent transportation system and
is proved to be a challenge. This paper proposed a hybrid strategy that is general and can …

Traffic speed prediction for urban transportation network: A path based deep learning approach

J Wang, R Chen, Z He - Transportation Research Part C: Emerging …, 2019 - Elsevier
Traffic prediction, as an important part of intelligent transportation systems, plays a critical
role in traffic state monitoring. While many studies accomplished traffic forecasting task with …

Traffic estimation and prediction based on real time floating car data

C De Fabritiis, R Ragona… - 2008 11th international …, 2008 - ieeexplore.ieee.org
The knowledge of the actual current state of the road traffic and its short-term evolution for
the entire road network is a basic component of ATIS (advanced traveler information …

Multistep traffic speed prediction: A deep learning based approach using latent space mapping considering spatio-temporal dependencies

S Modi, J Bhattacharya, P Basak - Expert Systems with Applications, 2022 - Elsevier
Traffic management in a city has become a major problem due to the increasing number of
vehicles on roads. Intelligent Transportation System (ITS) can help the city traffic managers …

A comparison of machine learning methods for the prediction of traffic speed in urban places

C Bratsas, K Koupidis, JM Salanova… - Sustainability, 2019 - mdpi.com
Rising interest in the field of Intelligent Transportation Systems combined with the increased
availability of collected data allows the study of different methods for prevention of traffic …

Managing spatial graph dependencies in large volumes of traffic data for travel-time prediction

A Salamanis, DD Kehagias… - IEEE Transactions …, 2015 - ieeexplore.ieee.org
The exploration of the potential correlations of traffic conditions between roads in large
urban networks, which is of profound importance for achieving accurate traffic prediction …

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 …