7 papers
Interaction-aware Lane-Changing Early Warning System in Congested Traffic
Yue Zhang, Xinzhi Zhong, Soyoung Ahn +2
Lane changes (LCs) in congested traffic are complex, multi-vehicle interactive events that pose significant safety concerns. Providing early warnings can enable more proactive driv…
Constructing the fundamental diagrams of traffic flow from large-scale vehicle trajectory data
Zhengbing He, Cathy Wu
For decades, researchers and practitioners typically measure macroscopic traffic flow variables, i.e., density, flow, and speed, using time or space cuts, and then construct the fu…
When Context Is Not Enough: Modeling Unexplained Variability in Car-Following Behavior
Chengyuan Zhang, Zhengbing He, Cathy Wu +1
Modeling car-following behavior is fundamental to microscopic traffic simulation, yet traditional deterministic models often fail to capture the full extent of variability and unpr…
A Review of Stop-and-Go Traffic Wave Suppression Strategies: Variable Speed Limit vs. Jam-Absorption Driving
Zhengbing He, Jorge Laval, Yu Han +3
The main form of freeway traffic congestion is the familiar stop-and-go wave, characterized by wide moving jams that propagate indefinitely upstream provided enough traffic demand.…
A Survey on Data-Driven Modeling of Human Drivers' Lane-Changing Decisions
Linxuan Huang, Dong-Fan Xie, Li Li +1
Lane-changing (LC) behavior, a critical yet complex driving maneuver, significantly influences driving safety and traffic dynamics. Traditional analytical LC decision (LCD) models,…
NeuralMOVES: A lightweight and microscopic vehicle emission estimation model based on reverse engineering and surrogate learning
Edgar Ramirez-Sanchez, Catherine Tang, Yaosheng Xu +4
The transportation sector significantly contributes to greenhouse gas emissions, necessitating accurate emission models to guide mitigation strategies. Despite its field validation…