A Gaussian-process-based data-driven traffic flow model and its application in road capacity analysis
To estimate the accurate fundamental relationship in traffic flow, this paper proposes a novel
framework that extends classical fundamental diagram (FD) models to incorporate more …
framework that extends classical fundamental diagram (FD) models to incorporate more …
[HTML][HTML] Model on empirically calibrating stochastic traffic flow fundamental diagram
This paper addresses two shortcomings of the data-driven stochastic fundamental diagram
for freeway traffic. The first shortcoming is related to the least-squares methods which have …
for freeway traffic. The first shortcoming is related to the least-squares methods which have …
Fitting empirical fundamental diagrams of road traffic: A comprehensive review and comparison of models using an extensive data set
DM Bramich, M Menéndez… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Understanding the inter-relationships between traffic flow, density, and speed through the
study of the fundamental diagram of road traffic is critical for traffic modelling and …
study of the fundamental diagram of road traffic is critical for traffic modelling and …
Bayesian calibration of traffic flow fundamental diagrams using Gaussian processes
Modeling the relationship between vehicle speed and density on the road is a fundamental
problem in traffic flow theory. Recent research found that using the least-squares (LS) …
problem in traffic flow theory. Recent research found that using the least-squares (LS) …
Recent developments in traffic flow modeling using macroscopic fundamental diagram
This paper presents an overview of the recent developments in traffic flow modelling and
analysis using macroscopic fundamental diagram (MFD) as well as their applications. In …
analysis using macroscopic fundamental diagram (MFD) as well as their applications. In …
On the stochastic fundamental diagram for freeway traffic: Model development, analytical properties, validation, and extensive applications
In this research, we apply a new calibration approach to generate stochastic traffic flow
fundamental diagrams. We first prove that the percentile based fundamental diagrams are …
fundamental diagrams. We first prove that the percentile based fundamental diagrams are …
Automatic calibration of fundamental diagram for first‐order macroscopic freeway traffic models
Despite its importance in macroscopic traffic flow modeling, comprehensive method for the
calibration of fundamental diagram is very limited. Conventional empirical methods adopt a …
calibration of fundamental diagram is very limited. Conventional empirical methods adopt a …
Dynamic data-driven local traffic state estimation and prediction
Traffic state prediction is a key problem with considerable implications in modern traffic
management. Traffic flow theory has provided significant resources, including models based …
management. Traffic flow theory has provided significant resources, including models based …
[HTML][HTML] A fundamental diagram based hybrid framework for traffic flow estimation and prediction by combining a Markovian model with deep learning
Accurate traffic congestion estimation and prediction are critical building blocks for smart trip
planning and rerouting decisions in transportation systems. Over the decades, there have …
planning and rerouting decisions in transportation systems. Over the decades, there have …
Data fusion algorithm for macroscopic fundamental diagram estimation
L Ambühl, M Menendez - Transportation Research Part C: Emerging …, 2016 - Elsevier
A promising framework that describes traffic conditions in urban networks is the macroscopic
fundamental diagram (MFD), relating average flow and average density in a relatively …
fundamental diagram (MFD), relating average flow and average density in a relatively …