Traffic state estimation (TSE) refers to the process of the inference of traffic state variables
(ie, flow, density, speed and other equivalent variables) on road segments using partially …

Macroscopic traffic flow models are of paramount importance to traffic surveillance and
control. Before their employments in applications, the models need to be calibrated and …

An historical overview of the development of traffic flow models is proposed in the form of a
model tree. The model tree shows the genealogy of four families: the fundamental relation …

Despite the wide implementation of machine learning (ML) technique in traffic flow modeling
recently, those data-driven approaches often fall short of accuracy in the cases with a small …

We prove the well-posedness of entropy weak solutions of a scalar conservation law with
non-local flux arising in traffic flow modeling. The result is obtained providing accurate L^ ∞ …

This book shows the history of traffic flow modelling from the perspective of modern day
applications. Traffic flow models describe how vehicles travel over roads, at which speeds …

A key qualitative requirement for highway traffic models is the ability to replicate a type of
traffic jam popularly referred to as a phantom jam, shock wave or stop-and-go wave. Despite …

The Aw-Rascle-Zhang (ARZ) model can be interpreted as a generalization of the Lighthill-
Whitham-Richards (LWR) model, possessing a family of fundamental diagram curves, each …

With the growing popularity of the Internet-of-Vehicles (IoV), it is of pressing necessity to
understand transportation traffic patterns and their impact on wireless network designs and …

Traffic flow dynamics are complex and nonlinear, and depend on the interactions of many
vehicles moving together. Especially, the stochastic driving behavior is a significant reason …