1 citations · 1 across the 2 of their papers we have counts for
6 papers
Heterogeneous Vertiport Selection Optimization for On-Demand Air Taxi Services: A Deep Reinforcement Learning Approach
Aoyu Pang, Maonan Wang, Zifan Sha +4
Urban Air Mobility (UAM) has emerged as a transformative solution to alleviate urban congestion by utilizing low-altitude airspace, thereby reducing pressure on ground transportati…
TranSimHub:A Unified Air-Ground Simulation Platform for Multi-Modal Perception and Decision-Making
Maonan Wang, Yirong Chen, Yuxin Cai +12
Air-ground collaborative intelligence is becoming a key approach for next-generation urban intelligent transportation management, where aerial and ground systems work together on p…
Real-Time Communication-Aware Ride-Sharing Route Planning for Urban Air Mobility: A Multi-Source Hybrid Attention Reinforcement Learning Approach
Yuejiao Xie, Maonan Wang, Di Zhou +2
Urban Air Mobility (UAM) systems are rapidly emerging as promising solutions to alleviate urban congestion, with path planning becoming a key focus area. Unlike ground transportati…
VLMLight: Safety-Critical Traffic Signal Control via Vision-Language Meta-Control and Dual-Branch Reasoning Architecture
Maonan Wang, Yirong Chen, Aoyu Pang +4
Traffic signal control (TSC) is a core challenge in urban mobility, where real-time decisions must balance efficiency and safety. Existing methods - ranging from rule-based heurist…
A Large Language Model-Enhanced Q-learning for Capacitated Vehicle Routing Problem with Time Windows
Linjiang Cao, Maonan Wang, Xi Xiong
The Capacitated Vehicle Routing Problem with Time Windows (CVRPTW) is a classic NP-hard combinatorial optimization problem widely applied in logistics distribution and transportati…
CL-CoTNav: Closed-Loop Hierarchical Chain-of-Thought for Zero-Shot Object-Goal Navigation with Vision-Language Models
Yuxin Cai, Xiangkun He, Maonan Wang +3
Visual Object Goal Navigation (ObjectNav) requires a robot to locate a target object in an unseen environment using egocentric observations. However, decision-making policies often…