108 citations · 110 across the 6 of their papers we have counts for
7 papers
EvoAD: Self-Evolving Autonomous Driving via Latent World-Model Guided Post-hoc Reflection
Junjie Yang, Qiming Zhang, Yuyan Li +12
End-to-end autonomous driving systems have achieved rapid progress by learning unified policies that map sensor observations directly to driving trajectories. However, once deploye…
Synergistic Perception and Generative Recomposition: A Multi-Agent Orchestration for Expert-Level Building Inspection
Hui Zhong, Yichun Gao, Luyan Liu +4
Building facade defect inspection is fundamental to structural health monitoring and sustainable urban maintenance, yet it remains a formidable challenge due to extreme geometric v…
Enhancing Urban Sensing Utility with Sensor-enabled Vehicles and Easily Accessible Data
Hui Zhong, Qing-Long Lu, Qiming Zhang +2
Urban sensing is essential for the development of smart cities, enabling monitoring, computing, and decision-making for urban management.Thanks to the advent of vehicle technologie…
A Physics-informed End-to-End Occupancy Framework for Motion Planning of Autonomous Vehicles
Shuqi Shen, Junjie Yang, Hongliang Lu +3
Accurate and interpretable motion planning is essential for autonomous vehicles (AVs) navigating complex and uncertain environments. While recent end-to-end occupancy prediction me…
Deployment-friendly Lane-changing Intention Prediction Powered by Brain-inspired Spiking Neural Networks
Shuqi Shen, Junjie Yang, Hui Zhong +3
Accurate and real-time prediction of surrounding vehicles' lane-changing intentions is a critical challenge in deploying safe and efficient autonomous driving systems in open-world…
Diffusion Models for Intelligent Transportation Systems: A Survey
Mingxing Peng, Kehua Chen, Xusen Guo +4
Intelligent Transportation Systems (ITS) are vital in modern traffic management and optimization, significantly enhancing traffic efficiency and safety. Recently, diffusion models…
Towards Explainable Traffic Flow Prediction with Large Language Models
Xusen Guo, Qiming Zhang, Junyue Jiang +4
Traffic forecasting is crucial for intelligent transportation systems. It has experienced significant advancements thanks to the power of deep learning in capturing latent patterns…