43 citations · 102 across the 22 of their papers we have counts for
26 papers
SceneFactory-3D: Lifting 2D Traffic Scenes into 3D Physical Counterfactuals for Scalable Physically Grounded Safety Evaluation
Yicheng Zhu, Linfeng Tian, Tianmu Zhao +4
Scalable driving simulators typically execute vehicle commands using prescribed behavioral or kinematic rules, overlooking the physics of tire-road interfaces, thereby limiting the…
TerrainForge: Physics-Grounded Road Geometry Editing for Counterfactual Autonomous Driving
Yang Chen, Yicheng Zhu, zhenning Li +2
Road geometry (e.g., crests, sags, and speed humps) and surface conditions (e.g., wet or icy pavement) affect how vehicles move, what drivers and onboard cameras observe, and how m…
SIREN-Bench: Behavior-Driven Generation and Evaluation of Emergency-Vehicle Interactions
Yicheng Zhu, Tianmu Zhao, Haoxin Leng +3
Emergency vehicles (EMVs) can reorganize surrounding traffic as civilian vehicles brake, change lanes, or form rescue corridors in response to their passage. Evaluating these safet…
muSync-GS: Physics-Synchronized Driving Video Synthesis for Weather and Geometric Road Hazards
Yang Chen, Yicheng Zhu, Tao Li +1
High-quality driving data are essential for autonomous-driving systems and generative world models. However, rare and safety-critical scenarios involving adverse weather, braking u…
From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction
Xinyi Ning, Zilin Bian, Dachuan Zuo +2
Accurate and reliable vehicle trajectory prediction is essential for safe autonomous driving. Recent studies have incorporated safety risk into trajectory prediction to quantify da…
Dynamic Deployment of Mobile Charging Trucks During Natural Disaster Evacuation: An Offline-to-Online Framework
Rui Ma, Zilin Bian, Kaan Ozbay
During large-scale evacuations, concentrated electric vehicle (EV) charging demand can overload fixed charging stations (FCSs), leading to prolonged waiting time and increased risk…
SceneFactory: GPU-Accelerated Multi-Agent Driving Simulation with Physics-Based Vehicle Dynamics
Yicheng Zhu, Yang Chen, Tao Li +1
Autonomous-driving simulators typically trade physical fidelity for scalable parallelism. Physics-based platforms such as CARLA and MetaDrive provide articulated vehicle dynamics a…
Distributed Online Convex Optimization with Nonseparable Costs and Constraints
Zhaoye Pan, Haozhe Lei, Fan Zuo +2
This paper studies distributed online convex optimization with time-varying coupled constraints, motivated by distributed online control in network systems. Most prior work assumes…
STRAP: Spatial-Temporal Risk-Attentive Vehicle Trajectory Prediction for Autonomous Driving
Xinyi Ning, Zilin Bian, Dachuan Zuo +1
Accurate vehicle trajectory prediction is essential for ensuring safety and efficiency in fully autonomous driving systems. While existing methods primarily focus on modeling obser…
Composite Safety Potential Field for Highway Driving Risk Assessment
Dachuan Zuo, Zilin Bian, Fan Zuo +1
In the era of rapid advancements in vehicle safety technologies, driving risk assessment has become a focal point of attention. Technologies such as collision warning systems, adva…
Traffic Adaptive Moving-window Service Patrolling for Real-time Incident Management during High-impact Events
Haozhe Lei, Ya-Ting Yang, Tao Li +4
This paper presents the Traffic Adaptive Moving-window Patrolling Algorithm (TAMPA), designed to improve real-time incident management during major events like sports tournaments a…
Aligning Vision to Language: Annotation-Free Multimodal Knowledge Graph Construction for Enhanced LLMs Reasoning
Junming Liu, Siyuan Meng, Yanting Gao +7
Multimodal reasoning in Large Language Models (LLMs) struggles with incomplete knowledge and hallucination artifacts, challenges that textual Knowledge Graphs (KGs) only partially…
When language and vision meet road safety: leveraging multimodal large language models for video-based traffic accident analysis
Ruixuan Zhang, Beichen Wang, Juexiao Zhang +3
The increasing availability of traffic videos functioning on a 24/7/365 time scale has the great potential of increasing the spatio-temporal coverage of traffic accidents, which wi…
A multi-dimension and high-granularity equity measurement for transportation services through accessibility and reliability
Mengke, Ma, Zilin Bian +4
Transportation equity research has traditionally emphasized service accessibility and destination reachability while often overlooking the critical aspects of service quality, such…
Real-time Accident Anticipation for Autonomous Driving Through Monocular Depth-Enhanced 3D Modeling
Haicheng Liao, Yongkang Li, Chengyue Wang +7
The primary goal of traffic accident anticipation is to foresee potential accidents in real time using dashcam videos, a task that is pivotal for enhancing the safety and reliabili…
Multi-level Traffic-Responsive Tilt Camera Surveillance through Predictive Correlated Online Learning
Tao Li, Zilin Bian, Haozhe Lei +5
In urban traffic management, the primary challenge of dynamically and efficiently monitoring traffic conditions is compounded by the insufficient utilization of thousands of survei…
Digital Twin-based Driver Risk-Aware Intelligent Mobility Analytics for Urban Transportation Management
Tao Li, Zilin Bian, Haozhe Lei +6
Traditional mobility management strategies emphasize macro-level mobility oversight from traffic-sensing infrastructures, often overlooking safety risks that directly affect road u…
Informed along the road: roadway capacity driven graph convolution network for network-wide traffic prediction
Zilin Bian, Jingqin Gao, Kaan Ozbay +3
While deep learning has shown success in predicting traffic states, most methods treat it as a general prediction task without considering transportation aspects. Recently, graph n…
Traffic Prediction considering Multiple Levels of Spatial-temporal Information: A Multi-scale Graph Wavelet-based Approach
Zilin Bian, Jingqin Gao, Kaan Ozbay +1
Although traffic prediction has been receiving considerable attention with a number of successes in the context of intelligent transportation systems, the prediction of traffic sta…
A-TEAM: Advanced Traffic Event Analysis and Management Platform for Transportation Data-Driven Problem Solving
Zilin Bian, Dachuan Zuo, Jingqin Gao +2
The rapid growth in terms of the availability of transportation data provides great potential for the introduction of emerging data-driven methodologies into transportation-related…
Learning When to See for Long-term Traffic Data Collection on Power-constrained Devices
Ruixuan Zhang, Wenyu Han, Zilin Bian +2
Collecting traffic data is crucial for transportation systems and urban planning, and is often more desirable through easy-to-deploy but power-constrained devices, due to the unava…
The Effects of the COVID-19 Pandemic on Transportation Systems in New York City and Seattle, USA
Jingqin Gao, Jingxing Wang, Zilin Bian +8
This paper continues to highlight trends in mobility and sociability in New York City (NYC), and supplements them with similar data from Seattle, WA, two of the cities most affecte…
Initial Impacts of COVID-19 on Transportation Systems: A Case Study of the U.S. Epicenter, the New York Metropolitan Area
Jingqin Gao, Suzana Duran Bernardes, Zilin Bian +2
The novel Coronavirus COVID-19 spreading rapidly throughout the world was recognized by the World Health Organization (WHO) as a pandemic on March 11, 2020. One month into the COVI…
Agent-based Simulation Model and Deep Learning Techniques to Evaluate and Predict Transportation Trends around COVID-19
Ding Wang, Fan Zuo, Jingqin Gao +11
The COVID-19 pandemic has affected travel behaviors and transportation system operations, and cities are grappling with what policies can be effective for a phased reopening shaped…