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Traffic prediction using artificial intelligence: Review of recent advances and emerging opportunities
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 …
critical problem globally, resulting in negative consequences such as lost hours of additional …
Edge intelligence in intelligent transportation systems: A survey
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 …
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 …
web map** services like Google Maps regularly serving vast quantities of travel time …
Deep learning for spatio-temporal data mining: A survey
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 …
(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 …
prediction can assist route planing, guide vehicle dispatching, and mitigate traffic …
Urban traffic prediction from spatio-temporal data using deep meta learning
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 …
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
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 …
efficient. With the development of mobile Internet and position technologies, it is reasonable …
Ridesourcing systems: A framework and review
With the rapid development and popularization of mobile and wireless communication
technologies, ridesourcing companies have been able to leverage internet-based platforms …
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
Traffic forecasting is a particularly challenging application of spatiotemporal forecasting, due
to the time-varying traffic patterns and the complicated spatial dependencies on road …
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 …
spatial and temporal characteristics, at varying scales, under varying conditions brought on …