activity
20242026
collaborators

6 papers

cs.RO2026

Robust Energy-Aware Routing for Air-Ground Cooperative Multi-UAV Delivery in Wind-Uncertain Environments

Tianshun Li, Hongliang Lu, Yanggang Sheng +3

Ensuring energy feasibility under wind uncertainty is critical for the safety and reliability of UAV delivery missions. In realistic truck-drone logistics systems, UAVs must delive…

cs.AI2026

Language-Grounded Multi-Agent Planning for Personalized and Fair Participatory Urban Sensing

Xusen Guo, Mingxing Peng, Hongliang Lu +3

Participatory urban sensing leverages human mobility for large-scale urban data collection, yet existing methods typically rely on centralized optimization and assume homogeneous p…

cs.ET2025

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…

cs.RO2025

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…

eess.SP2024

High-resolution urban air pollution and thermal comfort mapping: an application of drive mobile sensing platform for smart city services

Hui Zhong, Hongliang Lu, Ting Gan +2

Air pollutant exposure exhibits significant spatial and temporal variability, with localized hotspots, particularly in traffic microenvironments, posing health risks to commuters.…

cs.AI2024

Automating Traffic Model Enhancement with AI Research Agent

Xusen Guo, Xinxi Yang, Mingxing Peng +3

Developing efficient traffic models is crucial for optimizing modern transportation systems. However, current modeling approaches remain labor-intensive and prone to human errors d…