1 citations · 2 across the 11 of their papers we have counts for
12 papers
Toward Controllability-Aware Performance Measures: A Case Study on Controllable Highway Congestion
Shreyaa Raghavan, Edgar Ramirez-Sanchez, Zhengbing He +1
Advancements in emerging intelligent transportation systems (ITS) have shown immense benefit in reducing congestion, emissions, and accidents and enable lower-cost alternatives to…
Platooning Connected, Autonomous, and Human-Driven Vehicles: A Deep Reinforcement Learning-based Approach
Zhen Qina, Dong-Fan Xie, Heng Ma +2
Conventionally, existing vehicle platooning approaches are designed for connected vehicles, typically including connected autonomous vehicles and connected human-driven vehicles. N…
Transforming Police-Car Swerving for Mitigating Isolated Stop-and-Go Traffic Waves: A Practice-Oriented Jam-Absorption Driving Strategy
Zhengbing He
Stop-and-go traffic waves, a major form of freeway congestion, impose severe and persistent adverse impacts, including reduced traffic efficiency, increased safety risks, and eleva…
Probability-Aware Parking Selection
Cameron Hickert, Sirui Li, Zhengbing He +1
Current navigation systems conflate time-to-drive with the true time-to-arrive by ignoring parking search duration and the final walking leg. Such underestimation can significantly…
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…
A Survey on Large Language Model-empowered Autonomous Driving
Yuxuan Zhu, Shiyi Wang, Wenqing Zhong +7
Artificial intelligence (AI) plays a crucial role in autonomous driving (AD) research, propelling its development towards intelligence and efficiency. Currently, the development of…
On the quantification of the spatiotemporal impact of a single discretionary lane change on upstream traffic safety and efficiency
Kangning Hou, Jia Zou, Fangfang Zheng +2
Lane-changing is a critical driving maneuver, and understanding its effects on traffic safety and efficiency is essential for effective traffic management and optimization. However…