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 …

Microscopic traffic flow models enable predictions of traffic operations, which allows traffic
engineers to assess the efficiency and safety effects of roadway designs. Modeling vehicle …

The ability of automated vehicles (AV) to avoid accidents in complex traffic environments is
the focus of considerable public attention. Intel has proposed a mathematical model called …

Simultaneous perturbation stochastic approximation (SPSA) is an efficient and well
established optimization method that approximates gradients from successive objective …

A mathematical framework and a solution approach are presented for the simultaneous
calibration of the demand and supply parameters and inputs to microscopic traffic simulation …

How to calibrate the parameters of car-following models based on observed traffic data is a
vital problem in traffic simulation. Usually, the core of calibration is cast into an optimization …

This paper investigates the impact of vehicular trajectory completeness on car-following (CF)
model calibration and validation. Synthetic data with different levels of trajectory …

Calibration of car-following models against trajectory data has been widely applied as the
basis for studies ranging from model investigation and benchmarking to parameter …

This paper presents several metaheuristic algorithms to calibrate a microscopic traffic
simulation model. The genetic algorithm (GA), Tabu Search (TS), and a combination of the …

Agent-based microscopic traffic simulation models are gaining popularity over traditional trip-
based traffic models due to their superiority in modeling household member interaction, car …