The fact that road transportation negatively affects the quality of the environment and
deteriorates its bearing capacity has drawn a wide range of concerns among researchers. In …

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 …

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 …

This paper investigates optimal decision-making for traffic management under demand and
supply uncertainties by stochastic dynamic programming. Traffic flow dynamics under …

In this paper, we propose a regional dynamic traffic assignment framework for macroscopic
fundamental diagram (MFD) models that explicitly accounts for trip length distributions. The …

In this paper a novel iterative algorithm is presented for the link transmission model, a fast
macroscopic dynamic network loading scheme. The algorithm's solutions are defined on a …

This study introduces the dynamic congestion pricing (DCP) problem with the consideration
of the actual travel distance and time delay (ie a joint distance and time-delay toll, JDTDT) in …

Static traffic assignment models are still widely applied for strategic transport planning
purposes in spite of the fact that such models produce implausible traffic flows that exceed …

Pedestrian flow models are useful for the design and operation of pedestrian spaces. This
article describes a macroscopic model of pedestrian flows through networks composed of …

Macroscopic traffic flow models are suited for large scale, network wide applications where
the macro-characteristics of the flow are of prime interest. A clear understanding of the …