3 citations · 6 across the 8 of their papers we have counts for
9 papers
Design and Validation of a Grid-based Home Detection via Stay-Time (GHOST) Software for Mobile Location Data
Alessandra Recalde, Mustafa Sameen, Xiaojian Zhang +1
Accurately detecting home locations from GPS data generated by mobile devices is a foundational step in human mobility research, with significant implications for transportation pl…
Evacuation destination choices during Hurricane Ian: A direct demand modeling approach
Alessandra Recalde, Luyu Liu, Xiaojian Zhang +3
Hurricanes are causing unprecedented damage to the natural environment, infrastructure, and communities. Understanding evacuation behavior is essential for improving emergency prep…
PEMAND: Persona-Enriched Multi-Agent Negotiation for Household Decision-Making
Yuran Sun, Mustafa Sameen, Yaotian Zhang +5
Modeling household-level decisions is central to many real-world applications, including trip planning, residential mobility and migration, disaster management, etc. Existing studi…
Wildfire Evacuation Analysis Using Facebook Data: Evidence from Palisades and Eaton Fires
Shangkun Jiang, Ruggiero Lovreglio, Thomas J. Cova +3
The growing frequency and intensity of wildfires pose serious threats to communities in wildland-urban interface regions. Understanding evacuation behavior is critical for effectiv…
Synthesizing Attitudes, Predicting Actions (SAPA): Behavioral Theory-Guided LLMs for Ridesourcing Mode Choice Modeling
Mustafa Sameen, Xiaojian Zhang, Xilei Zhao
Accurate modeling of ridesourcing mode choices is essential for designing and implementing effective traffic management policies for reducing congestion, improving mobility, and al…
Hurricane Evacuation Analysis with Large-scale Mobile Device Location Data during Hurricane Ian
Luyu Liu, Xiaojian Zhang, Shangkun Jiang +1
Hurricane Ian is the deadliest and costliest hurricane in Florida's history, with 2.5 million people ordered to evacuate. As we witness increasingly severe hurricanes in the contex…
Post-hurricane building damage assessment using street-view imagery and structured data: A multi-modal deep learning approach
Zhuoqun Xue, Xiaojian Zhang, David O. Prevatt +3
Accurately assessing building damage is critical for disaster response and recovery. However, many existing models for detecting building damage have poor prediction accuracy due t…
Social Vulnerabilities and Wildfire Evacuations: A Case Study of the 2019 Kincade Fire
Yuran Sun, Ana Forrister, Erica D. Kuligowski +3
Vulnerable populations are disproportionately impacted by natural hazards like wildfires. It is crucial to develop equitable and effective evacuation strategies to meet their uniqu…
Causality-informed Rapid Post-hurricane Building Damage Detection in Large Scale from InSAR Imagery
Chenguang Wang, Yepeng Liu, Xiaojian Zhang +6
Timely and accurate assessment of hurricane-induced building damage is crucial for effective post-hurricane response and recovery efforts. Recently, remote sensing technologies pro…