Xilei Zhao
Xilei Zhao
Assistant Professor, Civil and Coastal Engineering, University of Florida
Verified email at - Homepage
Cited by
Cited by
Prediction and behavioral analysis of travel mode choice: A comparison of machine learning and logit models
X Zhao, X Yan, A Yu, P Van Hentenryck
Travel Behaviour and Society 20, 22-35, 2020
Integrating ridesourcing services with public transit: An evaluation of traveler responses combining revealed and stated preference data
X Yan, J Levine, X Zhao
Transportation Research Part C: Emerging Technologies 105, 683-696, 2019
COPEWELL: A Conceptual Framework and System Dynamics Model for Predicting Community Functioning and Resilience After Disasters
JM Links, BS Schwartz, S Lin, N Kanarek, J Mitrani-Reiser, TK Sell, ...
Disaster Medicine and Public Health Preparedness, 2017
Modelling and interpreting pre-evacuation decision-making using machine learning
X Zhao, R Lovreglio, D Nilsson
Automation in Construction 113, 103140, 2020
Identifying key factors associated with ridesplitting adoption rate and modeling their nonlinear relationships
Y Xu, X Yan, X Liu, X Zhao
Transportation Research Part A: Policy and Practice 144, 170-188, 2021
Using machine learning for direct demand modeling of ridesourcing services in Chicago
X Yan, X Liu, X Zhao
Journal of Transport Geography 83, 102661, 2020
A spatiotemporal analysis of e-scooters’ relationships with transit and station-based bikeshare
X Yan, W Yang, X Zhang, Y Xu, I Bejleri, X Zhao
Transportation research part D: transport and environment 101, 103088, 2021
A segment-level model of shared, electric scooter origins and destinations
LA Merlin, X Yan, Y Xu, X Zhao
Transportation Research Part D: Transport and Environment 92, 102709, 2021
Mobility-on-demand versus fixed-route transit systems: An evaluation of traveler preferences in low-income communities
X Yan, X Zhao, Y Han, P Van Hentenryck, T Dillahunt
Transportation Research Part A: Policy and Practice 148, 481-495, 2021
Modeling evacuation decisions in the 2019 Kincade fire in California
ED Kuligowski, X Zhao, R Lovreglio, N Xu, K Yang, A Westbury, D Nilsson, ...
Safety science 146, 105541, 2022
Assessing food system vulnerabilities: a fault tree modeling approach
GM Chodur, X Zhao, E Biehl, J Mitrani-Reiser, R Neff
BMC public health 18, 1-11, 2018
Identifying latent shared mobility preference segments in low-income communities: Ride-hailing, fixed-route bus, and mobility-on-demand transit
X Wang, X Yan, X Zhao, Z Cao
Travel Behaviour and Society 26, 134-142, 2022
Estimating wildfire evacuation decision and departure timing using large-scale GPS data
X Zhao, Y Xu, R Lovreglio, E Kuligowski, D Nilsson, TJ Cova, A Wu, X Yan
Transportation research part D: transport and environment 107, 103277, 2022
Using Artificial Intelligence for Safe and Effective Wildfire Evacuations
X Zhao, R Lovreglio, E Kuligowski, D Nilsson
Fire Technology, 2020
Modeling heterogeneity in mode-switching behavior under a mobility-on-demand transit system: An interpretable machine learning approach
X Zhao, X Yan, P Van Hentenryck
arXiv preprint arXiv:1902.02904, 2019
Machine learning approach for spatial modeling of ridesourcing demand
X Zhang, X Zhao
Journal of Transport Geography 100, 103310, 2022
Form-finding analysis for a new type of cable–strut tensile structures generated by semi-regular tensegrity
J Lu, X Dong, X Zhao, X Wu, G Shu
Advances in Structural Engineering 20 (5), 772-783, 2017
Micromobility trip origin and destination inference using general bikeshare feed specification data
Y Xu, X Yan, VP Sisiopiku, LA Merlin, F Xing, X Zhao
Transportation Research Record 2676 (11), 223-238, 2022
Predicting and assessing wildfire evacuation decision-making using machine learning: findings from the 2019 Kincade Fire
N Xu, R Lovreglio, ED Kuligowski, TJ Cova, D Nilsson, X Zhao
Fire Technology 59 (2), 793-825, 2023
Form finding analysis of cable-strut tensile dome based on tensegrity torus
J Lu, X Wu, X Zhao, G Shu
Engineering Mechanics 32 (6), 66-71, 2015
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