Estimation and prediction of the OD matrix in uncongested urban road network based on traffic flows using deep learning

T Pamuła, R Żochowska - Engineering Applications of Artificial Intelligence, 2023‏ - Elsevier
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 …

Spatio‐Temporal Segmented Traffic Flow Prediction with ANPRS Data Based on Improved XGBoost

B Sun, T Sun, P Jiao - Journal of Advanced Transportation, 2021‏ - Wiley Online Library
Traffic prediction is highly significant for intelligent traffic systems and traffic management.
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

Z Cheng, M Trépanier, L Sun - Transportation science, 2022‏ - pubsonline.informs.org
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 …

[HTML][HTML] Traffic flow density model and dynamic traffic congestion model simulation based on practice case with vehicle network and system traffic intelligent …

E Zadobrischi, LM Cosovanu, M Dimian - Symmetry, 2020‏ - mdpi.com
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 …

Impact of traffic flow rate on the accuracy of short-term prediction of origin-destination matrix in urban transportation networks

R Żochowska, T Pamuła - Remote Sensing, 2024‏ - mdpi.com
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 …

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 …

PURP: A Scalable System for Predicting Short-Term Urban Traffic Flow Based on License Plate Recognition Data

S Zhang, Q Jiang, H Li, B Cao… - Big Data Mining and …, 2023‏ - ieeexplore.ieee.org
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 …

Assignment matrix free algorithms for on-line estimation of dynamic origin-destination matrices

M Castiglione, G Cantelmo, M Qurashi… - Frontiers in Future …, 2021‏ - frontiersin.org
Dynamic Traffic Assignment (DTA) models represent fundamental tools to forecast traffic
flows on road networks, assessing the effects of traffic management and transport policies …

A DeepLearning framework for dynamic estimation of origin-destination sequence

Z **ong, D Lian, E Chen, G Chen, X Cheng - arxiv preprint arxiv …, 2023‏ - arxiv.org
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 …

Dynamic route flow estimation in road networks using data from automatic number of plate recognition sensors

S Sánchez-Cambronero, F Álvarez-Bazo, A Rivas… - Sustainability, 2021‏ - mdpi.com
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 …