In this paper, we review trajectory data-based traffic flow studies that have been conducted
over the last 15 years. Our purpose is to provide a roadmap for readers who have an interest …

Recent decades have seen considerable growth in computer capabilities, data collection
technology and communication mediums. This growth has had considerable impact on our …

It has been well recognized that human driver's limits, heterogeneity, and selfishness
substantially compromise the performance of our urban transport systems. In recent years, in …

In this paper, we propose a deep neural network-based car-following model that has two
distinctive properties. First, unlike most existing car-following models that take only the …

This paper proposes a recurrent neural network based microscopic car following model that
is able to accurately capture and predict traffic oscillation. Neural network models have …

In this paper, we propose a car-following model with consideration of the reliability of inter-
vehicle communication (IVC) to study each vehicle's speed, headway, fuel consumption and …

This work examines the impact of heavy vehicle movements on measured traffic
characteristics in detail. Although the number of heavy vehicles within the traffic stream is …

Car-following (CF) models are fundamental in the replication of traffic flow and thus they
have received considerable attention. This attention needs to be reflected upon at particular …

Microscopic traffic models (MTMs) are widely used for assessing the impacts of (connected)
autonomous vehicles ((C) AVs). These models utilize car‐following (CF) and lane‐changing …

A car-following (CF) model can reproduce various micro traffic phenomena and plays a
crucial role in traffic theory. In this study, we combine Markov theory and a gated recurrent …