An interdisciplinary survey on origin-destination flows modeling: Theory and techniques
Origin-destination (OD) flow modeling is an extensively researched subject across multiple
disciplines, such as the investigation of travel demand in transportation and spatial …
disciplines, such as the investigation of travel demand in transportation and spatial …
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 …
based on traffic data using deep learning. The input values of the developed model were …
[HTML][HTML] A hybrid modelling framework for the estimation of dynamic origin–destination flows
The dynamic origin–destination flow estimation (DODE) problem requires scalable methods
for large scale traffic networks and consistent techniques for capturing both uncongested …
for large scale traffic networks and consistent techniques for capturing both uncongested …
Network-wide speed–flow estimation considering uncertain traffic conditions and sparse multi-type detectors: A KL divergence-based optimization approach
SJ Liu, WHK Lam, ML Tam, H Fu, HW Ho… - … Research Part C …, 2024 - Elsevier
Accurate monitoring and sensing network-wide traffic conditions under uncertainty is vital for
addressing urban transportation obstacles and promoting the evolution of intelligent …
addressing urban transportation obstacles and promoting the evolution of intelligent …
A method of time-varying demand distribution estimation for high-speed railway networks with user equilibrium model
Time-varying demand distribution (TDD) is a critical input data for operation and
management in HSR systems. This paper proposed a bi-level model to estimate the TDD …
management in HSR systems. This paper proposed a bi-level model to estimate the TDD …
O–D matrix estimation based on data-driven network assignment
N Tsanakas, D Gundlegård… - … B: Transport Dynamics, 2023 - Taylor & Francis
Time-dependent Origin-Destination (OD) matrices are an essential input to transportation
models. A cost-efficient and widely used approach for estimating OD matrices involves the …
models. A cost-efficient and widely used approach for estimating OD matrices involves the …
Towards better traffic volume estimation: Jointly addressing the underdetermination and nonequilibrium problems with correlation-adaptive GNNs
Traffic volume is an indispensable ingredient to provide fine-grained information for traffic
management and control. However, due to the limited deployment of traffic sensors …
management and control. However, due to the limited deployment of traffic sensors …
Meta-Peering: Automating ISP Peering Decision Process
Peering between Internet Service Providers (ISPs) is playing an increasingly critical role in
Internet traffic exchange. As content delivery networks continue to expand, major content …
Internet traffic exchange. As content delivery networks continue to expand, major content …
Time-dependent estimation of origin–destination matrices using partial path data and link counts
M Vahidi, Y Shafahi - Transportation, 2023 - Springer
The precise estimation of time-varying demand matrices using traffic data is an essential
step for planning, scheduling, and evaluating advanced traffic management systems. This …
step for planning, scheduling, and evaluating advanced traffic management systems. This …
Dynamic origin–destination flow estimation for urban road network solely using probe vehicle trajectory data
Dynamic origin–destination (OD) flow is a fundamental input for dynamic network models
and simulators. Numerous studies have conducted dynamic OD estimations based on fixed …
and simulators. Numerous studies have conducted dynamic OD estimations based on fixed …