5 papers
An Empirical Markov Chain Car-Following (MC-CF) Model
Sungyong Chung, Yanlin Zhang, Nachuan Li +2
Car-following behavior is fundamental to traffic flow theory, yet traditional models often fail to capture the stochasticity of naturalistic driving. This paper proposes an empiric…
Using Drift Diffusion Model to Analyze Cars' Lane Change Decisions behind Heavy Vehicles
Nachuan Li, Hani S. Mahmassani, Soyoung Ahn +1
Heavy vehicles (HVs) pose a significant challenge to maintaining a smooth traffic flow on the freeway because they are slower moving and create large blind spots. It is therefore d…
Can the Waymo Open Motion Dataset Support Realistic Behavioral Modeling? A Validation Study with Naturalistic Trajectories
Yanlin Zhang, Sungyong Chung, Nachuan Li +4
The Waymo Open Motion Dataset (WOMD) has become a popular resource for data-driven modeling of autonomous vehicles (AVs) behavior. However, its validity for behavioral analysis rem…
Predicting Vehicles' Longitudinal Trajectories and Lane Changes on Highway On-Ramps
Nachuan Li, Riley Fischer, Wissam Kontar +1
Vehicles on highway on-ramps are one of the leading contributors to congestion. In this paper, we propose a prediction framework that predicts the longitudinal trajectories and lan…
A Prioritized Trajectory Planning Algorithm for Connected and Automated Vehicle Mandatory Lane Changes
Nachuan Li, Austen Z. Fan, Riley Fischer +2
We introduce a prioritized system-optimal algorithm for mandatory lane change (MLC) behavior of connected and automated vehicles (CAV) from a dedicated lane. Our approach applies a…