Review of data fusion methods for real-time and multi-sensor traffic flow analysis
SA Kashinath, SA Mostafa, A Mustapha… - IEEE …, 2021 - ieeexplore.ieee.org
Recently, development in intelligent transportation systems (ITS) requires the input of
various kinds of data in real-time and from multiple sources, which imposes additional …
various kinds of data in real-time and from multiple sources, which imposes additional …
[HTML][HTML] Traffic state estimation of urban road networks by multi-source data fusion: Review and new insights
Accurate traffic state (ie, flow, speed, density, etc.) on an urban road network is important
information for urban traffic control and management strategies. However, due to the …
information for urban traffic control and management strategies. However, due to the …
Estimating key traffic state parameters through parsimonious spatial queue models
As an active performance evaluation method, the fluid-based queueing model plays an
important role in traffic flow modeling and traffic state estimation problems. A critical …
important role in traffic flow modeling and traffic state estimation problems. A critical …
I-24 MOTION: An instrument for freeway traffic science
Abstract The Interstate-24 MObility Technology Interstate Observation Network (I-24
MOTION) is a new instrument for traffic science located near Nashville, Tennessee. I-24 …
MOTION) is a new instrument for traffic science located near Nashville, Tennessee. I-24 …
A physics-informed deep learning paradigm for traffic state and fundamental diagram estimation
Traffic state estimation (TSE) bifurcates into two main categories, model-driven and data-
driven (eg, machine learning, ML) approaches, while each suffers from either deficient …
driven (eg, machine learning, ML) approaches, while each suffers from either deficient …
Predicting traffic demand during hurricane evacuation using Real-time data from transportation systems and social media
In recent times, hurricanes Matthew, Harvey, and Irma have disrupted the lives of millions of
people across multiple states in the United States. Under hurricane evacuation, efficient …
people across multiple states in the United States. Under hurricane evacuation, efficient …
Physics-informed deep learning for traffic state estimation based on the traffic flow model and computational graph method
Traffic state estimation (TSE) is a critical task for intelligent transportation systems. However,
it is extremely challenging because the traffic data quality is often affected by the installation …
it is extremely challenging because the traffic data quality is often affected by the installation …
Physics-informed deep learning for traffic state estimation: A hybrid paradigm informed by second-order traffic models
Traffic state estimation (TSE) reconstructs the traffic variables (eg, density or average
velocity) on road segments using partially observed data, which is important for traffic …
velocity) on road segments using partially observed data, which is important for traffic …
Freeway traffic control: A survey
Freeway traffic control is a broad research area, not only interesting for its applicative
perspective, but also highly motivating for theoretical investigations. This research topic has …
perspective, but also highly motivating for theoretical investigations. This research topic has …
Hybrid deep learning models for traffic prediction in large-scale road networks
Traffic prediction is an important component in Intelligent Transportation Systems (ITSs) for
enabling advanced transportation management and services to address worsening traffic …
enabling advanced transportation management and services to address worsening traffic …