6 citations · 15 across the 11 of their papers we have counts for
11 papers
GPS-Enhanced Tourist Mobility Modeling with Seasonal Spatial Priors and LLM-Based Activity Chain Generation
Yifan Liu, Yanling Sang, Xishun Liao +6
Tourist mobility poses a distinct challenge for urban transportation planning. Unlike resident commuting, tourist travel is largely non-routine, attraction driven, and highly sensi…
Beyond 9-to-5: A Generative Model for Augmenting Mobility Data of Underrepresented Shift Workers
Haoxuan Ma, Xishun Liao, Yifan Liu +2
This paper addresses a critical gap in urban mobility modeling by focusing on shift workers, a population segment comprising 15-20% of the workforce in industrialized societies yet…
Next-Generation Travel Demand Modeling with a Generative Framework for Household Activity Coordination
Xishun Liao, Haoxuan Ma, Yifan Liu +4
Travel demand models are critical tools for planning, policy, and mobility system design. Traditional activity-based models (ABMs), although grounded in behavioral theories, often…
MobiVerse: Scaling Urban Mobility Simulation with Hybrid Lightweight Domain-Specific Generator and Large Language Models
Yifan Liu, Xishun Liao, Haoxuan Ma +3
Understanding and modeling human mobility patterns is crucial for effective transportation planning and urban development. Despite significant advances in mobility research, there…
Learning Universal Human Mobility Patterns with a Foundation Model for Cross-domain Data Fusion
Haoxuan Ma, Xishun Liao, Yifan Liu +4
Human mobility modeling is critical for urban planning and transportation management, yet existing approaches often lack the integration capabilities needed to handle diverse data…
Reconstructing Human Mobility Pattern: A Semi-Supervised Approach for Cross-Dataset Transfer Learning
Xishun Liao, Yifan Liu, Chenchen Kuai +5
Understanding human mobility patterns is crucial for urban planning, transportation management, and public health. This study tackles two primary challenges in the field: the relia…
NUMOSIM: A Synthetic Mobility Dataset with Anomaly Detection Benchmarks
Chris Stanford, Suman Adari, Xishun Liao +10
Collecting real-world mobility data is challenging. It is often fraught with privacy concerns, logistical difficulties, and inherent biases. Moreover, accurately annotating anomali…
Human Mobility Modeling with Household Coordination Activities under Limited Information via Retrieval-Augmented LLMs
Yifan Liu, Xishun Liao, Haoxuan Ma +3
Understanding human mobility patterns has long been a challenging task in transportation modeling. Due to the difficulties in obtaining high-quality training datasets across divers…
An Attention-Based Multi-Context Convolutional Encoder-Decoder Neural Network for Work Zone Traffic Impact Prediction
Qinhua Jiang, Xishun Liao, Yaofa Gong +1
Work zone is one of the major causes of non-recurrent traffic congestion and road incidents. Despite the significance of its impact, studies on predicting the traffic impact of wor…
Deep Activity Model: A Generative Approach for Human Mobility Pattern Synthesis
Xishun Liao, Qinhua Jiang, Brian Yueshuai He +3
Human mobility plays a crucial role in transportation, urban planning, and public health, but current approaches face important limitations. Existing deep learning models tend to o…
Semantic Trajectory Data Mining with LLM-Informed POI Classification
Yifan Liu, Chenchen Kuai, Haoxuan Ma +3
Human travel trajectory mining is crucial for transportation systems, enhancing route optimization, traffic management, and the study of human travel patterns. Previous rule-based…