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 …
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 …
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 …
[HTML][HTML] How machine learning informs ride-hailing services: A survey
In recent years, online ride-hailing services have emerged as an important component of
urban transportation system, which not only provide significant ease for residents' travel …
urban transportation system, which not only provide significant ease for residents' travel …
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 …
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 …
Constgat: Contextual spatial-temporal graph attention network for travel time estimation at baidu maps
The task of travel time estimation (TTE), which estimates the travel time for a given route and
departure time, plays an important role in intelligent transportation systems such as …
departure time, plays an important role in intelligent transportation systems such as …
Spatio-temporal meta learning for urban traffic prediction
Predicting urban traffic is of great importance to intelligent transportation systems and public
safety, yet is very challenging in three aspects: 1) complex spatio-temporal correlations of …
safety, yet is very challenging in three aspects: 1) complex spatio-temporal correlations of …
HetETA: Heterogeneous information network embedding for estimating time of arrival
The estimated time of arrival (ETA) is a critical task in the intelligent transportation system,
which involves the spatiotemporal data. Despite a significant amount of prior efforts have …
which involves the spatiotemporal data. Despite a significant amount of prior efforts have …
DeepGBM: A deep learning framework distilled by GBDT for online prediction tasks
Online prediction has become one of the most essential tasks in many real-world
applications. Two main characteristics of typical online prediction tasks include tabular input …
applications. Two main characteristics of typical online prediction tasks include tabular input …