This paper presents a review and classification of traffic assignment models for strategic
transport planning purposes by using concepts analogous to genetics in biology. Traffic …

Estimating and predicting traffic conditions in arterial networks using probe data has proven
to be a substantial challenge. Sparse probe data represent the vast majority of the data …

Node models for macroscopic simulation have attracted relatively little attention in the
literature. Nevertheless, in dynamic network loading (DNL) models for congested road …

This paper focuses on the analytical probabilistic modeling of vehicular traffic. It formulates a
stochastic node model. It then formulates a network model by coupling the node model with …

We address the controversial issue of traffic flow modeling, whether first-order, second-
order, or other traffic models are best supported by empirical facts and theoretical …

Abstract The Newell-Daganzo merge model is not only very simple but also accurately
reproduces experimental findings. However, the capacity downstream of the merge is an …

In this study, we develop a stochastic dynamic network loading (DNL) model for the mixed
traffic with autonomous vehicles (AVs) and human-driven vehicles (HVs). The source of …

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 …

Bottlenecks in urban traffic network are sticking points in restricting network collectivity traffic
efficiency. To identify network bottlenecks effectively is a foundational work for improving …

This paper is concerned with the study of a model case of first order Hamilton-Jacobi
equations posed on a “junction”, that is to say the union of a finite number of half-lines with a …