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Estimation and prediction of the OD matrix in uncongested urban road network based on traffic flows using deep learning
In this article, we propose a new method for OD (Origin–Destination) matrix prediction
based on traffic data using deep learning. The input values of the developed model were …
based on traffic data using deep learning. The input values of the developed model were …
Spatio‐Temporal Segmented Traffic Flow Prediction with ANPRS Data Based on Improved XGBoost
Traffic prediction is highly significant for intelligent traffic systems and traffic management.
eXtreme Gradient Boosting (XGBoost), a scalable tree lifting algorithm, is proposed and …
eXtreme Gradient Boosting (XGBoost), a scalable tree lifting algorithm, is proposed and …
Real-time forecasting of metro origin-destination matrices with high-order weighted dynamic mode decomposition
Forecasting short-term ridership of different origin-destination pairs (ie, OD matrix) is crucial
to the real-time operation of a metro system. However, this problem is notoriously difficult …
to the real-time operation of a metro system. However, this problem is notoriously difficult …
[HTML][HTML] Traffic flow density model and dynamic traffic congestion model simulation based on practice case with vehicle network and system traffic intelligent …
The massive increase in the number of vehicles has set a precedent in terms of congestion,
being one of the important factors affecting the flow of traffic, but there are also effects on the …
being one of the important factors affecting the flow of traffic, but there are also effects on the …
Impact of traffic flow rate on the accuracy of short-term prediction of origin-destination matrix in urban transportation networks
Information about spatial distribution (OD flows) is a key element in traffic management
systems in urban transport networks that enables efficient traffic control and decisions to …
systems in urban transport networks that enables efficient traffic control and decisions to …
Spatiotemporal Virtual Graph Convolution Network for Key Origin‐Destination Flow Prediction in Metro System
J Yang, X Han, T Ye, Y Tang, W Feng… - Mathematical …, 2022 - Wiley Online Library
Short‐term Origin‐Destination (OD) flow prediction plays a major part in the realization of
Smart Metro. It can help traffic managers implement dynamic control strategies to improve …
Smart Metro. It can help traffic managers implement dynamic control strategies to improve …
PURP: A Scalable System for Predicting Short-Term Urban Traffic Flow Based on License Plate Recognition Data
Accurate and efficient urban traffic flow prediction can help drivers identify road traffic
conditions in real-time, consequently hel** them avoid congestion and accidents to a …
conditions in real-time, consequently hel** them avoid congestion and accidents to a …
Assignment matrix free algorithms for on-line estimation of dynamic origin-destination matrices
Dynamic Traffic Assignment (DTA) models represent fundamental tools to forecast traffic
flows on road networks, assessing the effects of traffic management and transport policies …
flows on road networks, assessing the effects of traffic management and transport policies …
A DeepLearning framework for dynamic estimation of origin-destination sequence
OD matrix estimation is a critical problem in the transportation domain. The principle method
uses the traffic sensor measured information such as traffic counts to estimate the traffic …
uses the traffic sensor measured information such as traffic counts to estimate the traffic …
Dynamic route flow estimation in road networks using data from automatic number of plate recognition sensors
The traffic flow on road networks is dynamic in nature. Hence, a model for dynamic traffic
flow estimation should be a very useful tool for administrations to make decisions aimed at …
flow estimation should be a very useful tool for administrations to make decisions aimed at …