Symbiotic simulation systems that incorporate data-driven methods (such as machine/deep
learning) are effective and efficient tools for just-in-time (JIT) operational decision making …

With the growing popularity of digital twin and autonomous driving in transportation, the
demand for simulation systems capable of generating high-fidelity and reliable scenarios is …

With the increasing popularity of Digital Twin, there is an opportunity to employ deep
learning models in symbiotic simulation system. Symbiotic simulation can replicate multiple …

In traditional traffic simulation studies, vehicle behavior has typically been modeled using
complex analytical frameworks, which often struggle to encompass the full range of …

In microscopic traffic simulation, it is apparent that there is a dilemma between physics-
based and learning-based models for modelling car-following behaviours. The former can …

In recent years, exploring autonomous vehicles has become an emerging research topic
due to the massive opportuni-ties to deploy deep learning models in real-world …

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 …

Car-following behavior has been extensively studied using physics-based models, such as
Intelligent Driving Model (IDM). These models successfully interpret traffic phenomena …

Online traffic simulation that feeds from online information to simulate vehicle movement in
real-time has recently seen substantial advancement in the development of intelligent …

A realistic long-term microscopic traffic simulator is necessary for understanding how
microscopic changes affect traffic patterns at a larger scale. Traditional simulators that model …