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 …

Over the past decades there has been a considerable development in the modeling of car-
following (CF) behavior as a result of research undertaken by both traffic engineers and …

Connected and automated vehicles (CAVs) promise to significantly improve road traffic. To a
certain extent, this situation is similar to the expectations at the end of the last century about …

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 …

Abstract Recently released Autonomous Vehicle (AV) trajectory datasets can potentially
catalyze research progress on AV-oriented traffic flow analysis. This paper aims to …

With the advent and advancement of connected and automated vehicle technologies, it is
now possible to control connected and automated vehicles (CAVs) in mixed traffic flows to …

This paper shows that the behavior of driver models, either individually or entangled in
stochastic traffic simulation, is affected by the accuracy of empirical vehicle trajectories. To …

Car-following behavior modeling is of great importance for traffic simulation and analysis.
Considering the multi-steps decision-making process in human driving, we propose a …

Emergency vehicles (EVs) play a crucial role in providing timely help for the general public
in saving lives and avoiding property loss. However, very few efforts have been made for EV …

Abstract A recent study (Li, 2020) analytically predicted tradeoffs between automated vehicle
(AV) following characteristics on safety, mobility, and stability using a parsimonious linear …