Traffic prediction using artificial intelligence: Review of recent advances and emerging opportunities

M Shaygan, C Meese, W Li, XG Zhao… - … research part C: emerging …, 2022 - Elsevier
Traffic prediction plays a crucial role in alleviating traffic congestion which represents a
critical problem globally, resulting in negative consequences such as lost hours of additional …

Edge intelligence in intelligent transportation systems: A survey

T Gong, L Zhu, FR Yu, T Tang - IEEE Transactions on Intelligent …, 2023 - ieeexplore.ieee.org
Edge intelligence (EI) is becoming one of the research hotspots among researchers, which
is believed to help empower intelligent transportation systems (ITS). ITS generates a large …

Eta prediction with graph neural networks in google maps

A Derrow-Pinion, J She, D Wong, O Lange… - Proceedings of the 30th …, 2021 - dl.acm.org
Travel-time prediction constitutes a task of high importance in transportation networks, with
web map** services like Google Maps regularly serving vast quantities of travel time …

Deep learning for spatio-temporal data mining: A survey

S Wang, J Cao, SY Philip - IEEE transactions on knowledge …, 2020 - ieeexplore.ieee.org
With the fast development of various positioning techniques such as Global Position System
(GPS), mobile devices and remote sensing, spatio-temporal data has become increasingly …

Deep learning on traffic prediction: Methods, analysis, and future directions

X Yin, G Wu, J Wei, Y Shen, H Qi… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Traffic prediction plays an essential role in intelligent transportation system. Accurate traffic
prediction can assist route planing, guide vehicle dispatching, and mitigate traffic …

Urban traffic prediction from spatio-temporal data using deep meta learning

Z Pan, Y Liang, W Wang, Y Yu, Y Zheng… - Proceedings of the 25th …, 2019 - dl.acm.org
Predicting urban traffic is of great importance to intelligent transportation systems and public
safety, yet is very challenging because of two aspects: 1) complex spatio-temporal …

A survey of traffic prediction: from spatio-temporal data to intelligent transportation

H Yuan, G Li - Data Science and Engineering, 2021 - Springer
Intelligent transportation (eg, intelligent traffic light) makes our travel more convenient and
efficient. With the development of mobile Internet and position technologies, it is reasonable …

Ridesourcing systems: A framework and review

H Wang, H Yang - Transportation Research Part B: Methodological, 2019 - Elsevier
With the rapid development and popularization of mobile and wireless communication
technologies, ridesourcing companies have been able to leverage internet-based platforms …

Traffic graph convolutional recurrent neural network: A deep learning framework for network-scale traffic learning and forecasting

Z Cui, K Henrickson, R Ke… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Traffic forecasting is a particularly challenging application of spatiotemporal forecasting, due
to the time-varying traffic patterns and the complicated spatial dependencies on road …

Deep learning for intelligent transportation systems: A survey of emerging trends

M Veres, M Moussa - IEEE Transactions on Intelligent …, 2019 - ieeexplore.ieee.org
Transportation systems operate in a domain that is anything but simple. Many exhibit both
spatial and temporal characteristics, at varying scales, under varying conditions brought on …