256 citations · 700 across the 14 of their papers we have counts for
14 papers
ROCO: A Roundabout Traffic Conflict Dataset
Depu Meng, Owen Sayer, Rusheng Zhang +3
Traffic conflicts have been studied by the transportation research community as a surrogate safety measure for decades. However, due to the rarity of traffic conflicts, collecting…
"Curse of rarity" for autonomous vehicles
Henry X. Liu, Shuo Feng
In this paper, we reveal that the rarity of safety-critical events in high-dimensional driving environments is the root cause of the safety challenge for autonomous vehicle develop…
Real-time Full-stack Traffic Scene Perception for Autonomous Driving with Roadside Cameras
Zhengxia Zou, Rusheng Zhang, Shengyin Shen +4
We propose a novel and pragmatic framework for traffic scene perception with roadside cameras. The proposed framework covers a full-stack of roadside perception pipeline for infras…
A hierarchical behavior prediction framework at signalized intersections
Zhen Yang, Rusheng Zhang, Henry X. Liu
Road user behavior prediction is one of the most critical components in trajectory planning for autonomous driving, especially in urban scenarios involving traffic signals. In this…
A probabilistic model for missing traffic volume reconstruction based on data fusion
Xintao Yan, Yan Zhao, Henry X. Liu
Traffic volume information is critical for intelligent transportation systems. It serves as a key input to transportation planning, roadway design, and traffic signal control. Howe…
Corner Case Generation and Analysis for Safety Assessment of Autonomous Vehicles
Haowei Sun, Shuo Feng, Xintao Yan +1
Testing and evaluation is a crucial step in the development and deployment of Connected and Automated Vehicles (CAVs). To comprehensively evaluate the performance of CAVs, it is of…
A Learning-based Stochastic Driving Model for Autonomous Vehicle Testing
Lin Liu, Shuo Feng, Yiheng Feng +2
In the simulation-based testing and evaluation of autonomous vehicles (AVs), how background vehicles (BVs) drive directly influences the AV's driving behavior and further impacts t…
Distributionally Consistent Simulation of Naturalistic Driving Environment for Autonomous Vehicle Testing
Xintao Yan, Shuo Feng, Haowei Sun +1
Microscopic traffic simulation provides a controllable, repeatable, and efficient testing environment for autonomous vehicles (AVs). To evaluate AVs' safety performance unbiasedly,…
Impact Evaluation of Falsified Data Attacks on Connected Vehicle Based Traffic Signal Control
Shihong Ed Huang, Wai Wong, Yiheng Feng +3
Connected vehicle (CV) technology enables data exchange between vehicles and transportation infrastructure and therefore has great potentials to improve current traffic signal cont…
Testing Scenario Library Generation for Connected and Automated Vehicles: An Adaptive Framework
Shuo Feng, Yiheng Feng, Haowei Sun +2
How to generate testing scenario libraries for connected and automated vehicles (CAVs) is a major challenge faced by the industry. In previous studies, to evaluate maneuver challen…
Testing Scenario Library Generation for Connected and Automated Vehicles, Part II: Case Studies
Shuo Feng, Yiheng Feng, Haowei Sun +3
Testing scenario library generation (TSLG) is a critical step for the development and deployment of connected and automated vehicles (CAVs). In Part I of this study, a general meth…
Testing Scenario Library Generation for Connected and Automated Vehicles, Part I: Methodology
Shuo Feng, Yiheng Feng, Chunhui Yu +2
Testing and evaluation is a critical step in the development and deployment of connected and automated vehicles (CAVs), and yet there is no systematic framework to generate testing…
Various methods for queue length and traffic volume estimation using probe vehicle trajectories
Yan Zhao, Jianfeng Zheng, Wai Wong +3
The rapid development of connected vehicle technology and the emergence of ride-hailing services have enabled the collection of a tremendous amount of probe vehicle trajectory data…
Traffic state estimation using stochastic Lagrangian dynamics
Fangfang Zheng, Saif Eddin Jabari, Henry X. Liu +1
This paper proposes a new stochastic model of traffic dynamics in Lagrangian coordinates. The source of uncertainty is heterogeneity in driving behavior, captured using driver-spec…