Publications (59)
Robust Platoon Control in Mixed Traffic Flow Based on Tube Model Predictive Control
Shuo Feng, Ziyou Song, Zhaojian Li +2
The design of cooperative adaptive cruise control is critical in mixed traffic flow, where connected and automated vehicles (CAVs) and human-driven vehicles (HDVs) coexist. Compare…
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…
Exploring Contextual Relationships for Cervical Abnormal Cell Detection
Yixiong Liang, Shuo Feng, Qing Liu +5
Cervical abnormal cell detection is a challenging task as the morphological discrepancies between abnormal and normal cells are usually subtle. To determine whether a cervical cell…
Y-AR: A Mixed Reality CAD Tool for 3D Wire Bending
Shuo Feng, Bo Liu, Yifan +7
Wire bending is a technique used in manufacturing to mass-produce items such as clips, mounts, and braces. Recent advances in programmable wire bending have made this process incre…
Towards provable probabilistic safety for scalable embodied AI systems
Linxuan He, Lingxiang Fan, Qing-Shan Jia +13
Embodied AI systems, comprising AI models and physical plants, are increasingly prevalent across various applications. Due to the rarity of system failures, ensuring their safety i…
Correctness Learning: Deductive Verification Guided Learning for Human-AI Collaboration
Zhao Jin, Lu Jin, Yizhe Luo +5
Despite significant progress in AI and decision-making technologies in safety-critical fields, challenges remain in verifying the correctness of decision output schemes and verific…
Gravitational and Autoregressive Analysis Spatial Diffusion of COVID-19 in Hubei Province, China
Yanguang Chen, Yajing Li, Yuqing Long +1
The spatial diffusion of epidemic disease follows distance decay law in geography, but different diffusion processes may be modeled by different mathematical functions under differ…
FAF: A Feature-Adaptive Framework for Few-Shot Time Series Forecasting
Pengpeng Ouyang, Dong Chen, Tong Yang +3
Multi-task and few-shot time series forecasting tasks are commonly encountered in scenarios such as the launch of new products in different cities. However, traditional time series…
Stackelberg Game Approaches for Anti-jamming Defence in Wireless Networks
Luliang Jia, Yuhua Xu, Youming Sun +2
This article investigates the anti-jamming communications problem in wireless networks from a Stackelberg game perspective. By exploring and analyzing the inherent characteristics…
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…
Context-aware Group Buying in Ultra-dense Small Cell Networks: Unity is Strength
Yuli Zhang, Yuhua Xu, Alagan Anpalagan +5
The ultra-dense small cell networks (SCNs) have been regarded as a promising technology to solve the data traffic explosion in future. However, the complicated relationships among…
Knowledge-data fusion dominated vehicle platoon dynamics modeling and analysis: A physics-encoded deep learning approach
Hao Lyu, Yanyong Guo, Pan Liu +3
Recently, artificial intelligence (AI)-enabled nonlinear vehicle platoon dynamics modeling plays a crucial role in predicting and optimizing the interactions between vehicles. Exis…
Improving Brain-to-Image Reconstruction via Fine-Grained Text Bridging
Runze Xia, Shuo Feng, Renzhi Wang +3
Brain-to-Image reconstruction aims to recover visual stimuli perceived by humans from brain activity. However, the reconstructed visual stimuli often missing details and semantic i…
DC-WAM: Dynamic-Centric Visual Supervision and Reasoning for World-Action Models
Haoyuan Ji, Lingxiang Fan, Shang Su +4
The paper introduces DC-WAM, a framework that shifts visual supervision in robot world-action models toward dynamic, interaction-relevant features using flow matching and attention…
Distributed Cooperative Driving in Multi-Intersection Road Networks
Huaxin Pei, Yi Zhang, Qinghua Tao +2
Cooperative driving at isolated intersections attracted great interest and had been well discussed in recent years. However, cooperative driving in multi-intersection road networks…
IntersectioNDE: Learning Complex Urban Traffic Dynamics based on Interaction Decoupling Strategy
Enli Lin, Ziyuan Yang, Qiujing Lu +2
Realistic traffic simulation is critical for ensuring the safety and reliability of autonomous vehicles (AVs), especially in complex and diverse urban traffic environments. However…
Adaptive Safety Evaluation for Connected and Automated Vehicles with Sparse Control Variates
Jingxuan Yang, Haowei Sun, Honglin He +3
Safety performance evaluation is critical for developing and deploying connected and automated vehicles (CAVs). One prevailing way is to design testing scenarios using prior knowle…
Comparing Fabrication Workflows in CAD to Support Design Reasoning
Shuo Feng, Xuening Wang, Yifan +7
When novices fabricate, they start by choosing a workflow (e.g., laser cutting, 3D printing, etc.) and corresponding software from a narrow set they know. As they advance their des…
Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network
Shuo Feng, Runlin Zhou, Yuyang Li +1
Industrial surface defect detection often suffers from limited defect samples, severe long-tailed distributions, and difficulties in accurately localizing subtle defects under comp…
Latent Two-Sample Testing for Fair Autonomous Vehicle Road Evaluation
Qiujing Lu, Xuanhan Wang, Guanghong Jia +5
With the rapid advancement of autonomous vehicle (AV) systems, fast and reliable iteration through road testing has become increasingly critical. However, changes in testing enviro…
A Grouping Based Cooperative Driving Strategy for CAVs Merging Problems
Huile Xu, Shuo Feng, Yi Zhang +1
In general, there are two kinds of cooperative driving strategies, planning based strategy and ad hoc negotiation based strategy, for connected and automated vehicles (CAVs) mergin…
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…
A Mechanical System Inspired Microscopic Traffic Model: Modeling, Analysis, and Validation
Mohammad R. Hajidavalloo, Zhaojian Li, Dong Chen +3
In this paper, we develop a mechanical system inspired microscopic traffic model to characterize the longitudinal interaction dynamics among a chain of vehicles. In particular, we…
Efficient Safety Verification of Autonomous Vehicles with Neural Network Operator
Lingxiang Fan, Linxuan He, Haoyuan Ji +1
When autonomous vehicles encounter untrained scenarios, ensuring safety hinges on effective safety verification to prevent accidents stemming from unexpected model decisions. Reach…
Evaluation of automated driving system safety metrics with logged vehicle trajectory data
Xintao Yan, Shuo Feng, David J. LeBlanc +2
Real-time safety metrics are important for the automated driving system (ADS) to assess the risk of driving situations and to assist the decision-making. Although a number of real-…
Longitudinal Safety Analysis For Heterogeneous Platoon Of Automated And Human Vehicles
Zi Yang, Xinpeng Wang, Xin Pei +4
With the recent advancement in environmental sensing, vehicle control and vehicle-infrastructure cooperation technologies, more and more autonomous driving companies start to put t…
Game-theoretic Learning Anti-jamming Approaches in Wireless Networks
Luliang Jia, Nan Qi, Feihuang Chu +4
In this article, the anti-jamming communication problem is investigated from a game-theoretic learning perspective. By exploring and analyzing intelligent anti-jamming communicatio…
"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…
Topology-Driven Anti-Entanglement Control for Soft Robots
Haoyang Le, Shengxuan Wang, Mohan Chen +1
In the field of precision manufacturing in complex constrained environments, the role of soft robots is increasingly prominent, and the realization of anti-winding control based on…
Adaptive Testing for Connected and Automated Vehicles with Sparse Control Variates in Overtaking Scenarios
Jingxuan Yang, Honglin He, Yi Zhang +2
Testing and evaluation is a critical step in the development and deployment of connected and automated vehicles (CAVs). Due to the black-box property and various types of CAVs, how…
Intelligent Resilience Testing for Decision-Making Agents with Dual-Mode Surrogate Adaptation
Jingxuan Yang, Weichao Xu, Yuchen Shi +3
Testing and evaluating decision-making agents remains challenging due to unknown system architectures, limited access to internal states, and the vastness of high-dimensional scena…
Controllable risk scenario generation from human crash data for autonomous vehicle testing
Qiujing Lu, Xuanhan Wang, Runze Yuan +3
Ensuring the safety of autonomous vehicles (AV) requires rigorous testing under both everyday driving and rare, safety-critical conditions. A key challenge lies in simulating envir…
Accurately Predicting Probabilities of Safety-Critical Rare Events for Intelligent Systems
Ruoxuan Bai, Jingxuan Yang, Weiduo Gong +3
Intelligent systems are increasingly integral to our daily lives, yet rare safety-critical events present significant latent threats to their practical deployment. Addressing this…
A Bi-Level Cooperative Driving Strategy Allowing Lane Changes
Huile Xu, Yi Zhang, Christos G. Cassandras +2
This paper studies the cooperative driving of connected and automated vehicles (CAVs) at conflict areas (e.g., non-signalized intersections and ramping regions). Due to safety conc…
Distilling Neuron Spike with High Temperature in Reinforcement Learning Agents
Ling Zhang, Jian Cao, Yuan Zhang +2
Spiking neural network (SNN), compared with depth neural network (DNN), has faster processing speed, lower energy consumption and more biological interpretability, which is expecte…
VPN: Visual Prompt Navigation
Shuo Feng, Zihan Wang, Yuchen Li +6
While natural language is commonly used to guide embodied agents, the inherent ambiguity and verbosity of language often hinder the effectiveness of language-guided navigation in c…
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,…
Difference-in-Differences for Health Policy and Practice: A Review of Modern Methods
Shuo Feng, Ishani Ganguli, Youjin Lee +3
Difference-in-differences (DiD) is the most popular observational causal inference method in health policy, employed to evaluate the real-world impact of policies and programs. To…
Few-Shot Scenario Testing for Autonomous Vehicles Based on Neighborhood Coverage and Similarity
Shu Li, Jingxuan Yang, Honglin He +3
Testing and evaluating the safety performance of autonomous vehicles (AVs) is essential before the large-scale deployment. Practically, the number of testing scenarios permissible…
CACL: Community-Aware Heterogeneous Graph Contrastive Learning for Social Media Bot Detection
Sirry Chen, Shuo Feng, Songsong Liang +3
Social media bot detection is increasingly crucial with the rise of social media platforms. Existing methods predominantly construct social networks as graph and utilize graph neur…
Conditional Analysis for Key-Value Data with Local Differential Privacy
Lin Sun, Jun Zhao, Xiaojun Ye +3
Local differential privacy (LDP) has been deemed as the de facto measure for privacy-preserving distributed data collection and analysis. Recently, researchers have extended LDP to…
TeraSim-World: Worldwide Safety-Critical Data Synthesis for End-to-End Autonomous Driving
Jiawei Wang, Haowei Sun, Xintao Yan +3
Safe and scalable deployment of end-to-end (E2E) autonomous driving requires extensive and diverse data, particularly safety-critical events. Existing data are mostly generated fro…
Behavioral Safety Assessment towards Large-scale Deployment of Autonomous Vehicles
Henry X. Liu, Xintao Yan, Haowei Sun +7
Autonomous vehicles (AVs) have significantly advanced in real-world deployment in recent years, yet safety continues to be a critical barrier to widespread adoption. Traditional fu…
Challenger: Affordable Adversarial Driving Video Generation
Zhiyuan Xu, Bohan Li, Huan-ang Gao +7
Generating photorealistic driving videos has seen significant progress recently, but current methods largely focus on ordinary, non-adversarial scenarios. Meanwhile, efforts to gen…
Pride and Prejudice: Toward an Information-Theoretic Framework for Mutually Communicative Driver Behavior Modeling
Tingjun Li, Nan Xu, Shuo Feng +3
Mixed autonomy driving becomes unsafe and inefficient when autonomous vehicles (AVs) and human-driven vehicles (HVs) misread each other's intentions. We study this problem as impli…
An adaptive multi-fidelity sampling framework for safety analysis of connected and automated vehicles
Xianliang Gong, Shuo Feng, Yulin Pan
Testing and evaluation are expensive but critical steps in the development of connected and automated vehicles (CAVs). In this paper, we develop an adaptive sampling framework to e…
Adaptive Testing Environment Generation for Connected and Automated Vehicles with Dense Reinforcement Learning
Jingxuan Yang, Ruoxuan Bai, Haoyuan Ji +3
The assessment of safety performance plays a pivotal role in the development and deployment of connected and automated vehicles (CAVs). A common approach involves designing testing…
Ancient Chinese Word Segmentation and Part-of-Speech Tagging Using Distant Supervision
Shuo Feng, Piji Li
Ancient Chinese word segmentation (WSG) and part-of-speech tagging (POS) are important to study ancient Chinese, but the amount of ancient Chinese WSG and POS tagging data is still…
Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments
Deliang Jin, Gang Chen, Shuo Feng +2
Deep neural networks (DNNs) have achieved remarkable success across diverse domains, but their performance can be severely degraded by noisy or corrupted training data. Conventiona…
OriStitch: A Machine Embroidery Workflow to Turn Existing Fabrics into Self-Folding 3D Textiles
Zekun Chang, Yixuan Gao, Yuta Noma +11
OriStitch is a computational fabrication workflow to turn existing flat fabrics into self-folding 3D structures. Users turn fabrics into self-folding sheets by machine embroidering…
Co-Design with Myself: A Brain-Computer Interface Design Tool that Predicts Live Emotion to Enhance Metacognitive Monitoring of Designers
Qi Yang, Shuo Feng, Tianlin Zhao +1
Intuition, metacognition, and subjective uncertainty interact in complex ways to shape the creative design process. Design intuition, a designer's innate ability to generate creati…
Cognitive Internet of Things: A New Paradigm beyond Connection
Qihui Wu, Guoru Ding, Yuhua Xu +4
Current research on Internet of Things (IoT) mainly focuses on how to enable general objects to see, hear, and smell the physical world for themselves, and make them connected to s…
Optimal Cooperative Driving at Signal-Free Intersections with Polynomial-Time Complexity
Huaxin Pei, Yuxiao Zhang, Yi Zhang +1
Cooperative driving at signal-free intersections, which aims to improve driving safety and efficiency for connected and automated vehicles, has attracted increasing interest in rec…
Self-Evolving Learning for Embodied AI with Criticality Model
Linxuan He, Yuying Tian, Lingxiang Fan +5
The paper introduces a self‑evolving learning approach for embodied AI that uses a state‑wise criticality model to predict failure and prioritize failure‑prone samples during finet…
Few-Shot Testing of Autonomous Vehicles with Scenario Similarity Learning
Shu Li, Honglin He, Jingxuan Yang +3
Testing and evaluation are critical to the development and deployment of autonomous vehicles (AVs). Given the rarity of safety-critical events such as crashes, millions of tests ar…
Multimodal Large Language Model Driven Scenario Testing for Autonomous Vehicles
Qiujing Lu, Xuanhan Wang, Yiwei Jiang +3
The generation of corner cases has become increasingly crucial for efficiently testing autonomous vehicles prior to road deployment. However, existing methods struggle to accommoda…
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…
Realistic Corner Case Generation for Autonomous Vehicles with Multimodal Large Language Model
Qiujing Lu, Meng Ma, Ximiao Dai +2
To guarantee the safety and reliability of autonomous vehicle (AV) systems, corner cases play a crucial role in exploring the system's behavior under rare and challenging condition…
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…