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 | 100 | 2021 |
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 | 71 | 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 | 61 | 2021 |
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 | 40 | 2022 |
Two‐dimensional simulation of turning behavior in potential conflict area of mixed‐flow intersections Z Ma, J Xie, X Qi, Y Xu, J Sun Computer‐Aided Civil and Infrastructure Engineering 32 (5), 412-428, 2017 | 35 | 2017 |
Accelerated testing for automated vehicles safety evaluation in cut-in scenarios based on importance sampling, genetic algorithm and simulation applications Y Xu, Y Zou, J Sun Journal of intelligent and connected vehicles 1 (1), 28-38, 2018 | 30 | 2018 |
Vehicle turning behavior modeling at conflicting areas of mixed-flow intersections based on deep learning J Sun, X Qi, Y Xu, Y Tian IEEE transactions on intelligent transportation systems 21 (9), 3674-3685, 2019 | 27 | 2019 |
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 | 20* | 2022 |
Simulation of turning vehicles’ behaviors at mixed-flow intersections based on potential field theory Y Xu, Z Ma, J Sun Transportmetrica B: Transport Dynamics 7 (1), 498-518, 2019 | 19 | 2019 |
Wildfire evacuation decision modeling using GPS data A Wu, X Yan, E Kuligowski, R Lovreglio, D Nilsson, TJ Cova, Y Xu, X Zhao International Journal of Disaster Risk Reduction 83, 103373, 2022 | 18 | 2022 |
Real-time forecasting of dockless scooter-sharing demand: A spatio-temporal multi-graph transformer approach Y Xu, X Zhao, X Zhang, M Paliwal IEEE Transactions on Intelligent Transportation Systems 24 (8), 8507-8518, 2023 | 12* | 2023 |
Analyzing spatial heterogeneity of ridesourcing usage determinants using explainable machine learning X Zhang, Z Zhou, Y Xu, X Zhao Journal of Transport Geography 114, 103782, 2024 | 6* | 2024 |
Autonomous vehicles’ car-following drivability evaluation based on driving behavior spectrum reference model X Qi, Y Ni, Y Xu, Y Tian, J Wang, J Sun Transportation research record 2675 (7), 129-141, 2021 | 5 | 2021 |
Situational-aware multi-graph convolutional recurrent network (sa-mgcrn) for travel demand forecasting during wildfires X Zhang, X Zhao, Y Xu, R Lovreglio, D Nilsson arXiv preprint arXiv:2304.06233, 2023 | 3 | 2023 |
Micromobility as a Solution to Reduce Urban Traffic Congestion X Zhao, VP Sisiopiku, RL Steiner, Y Xu, Y Liu, D Yan, J Khalil, W Yang, ... Southeastern Transportation Research, Innovation, Development and Education …, 2022 | 3 | 2022 |
ICN: Interactive convolutional network for forecasting travel demand of shared micromobility Y Xu, Q Ke, X Zhang, X Zhao GeoInformatica, 1-26, 2024 | 1 | 2024 |
A highway vehicle routing dataset during the 2019 Kincade Fire evacuation Y Xu, X Zhao, R Lovreglio, E Kuligowski, D Nilsson, TJ Cova, X Yan Scientific data 9 (1), 608, 2022 | 1 | 2022 |
Real-Time Urban Traffic Monitoring Using Transit Buses as Probes S Jiang, Y Sun, W Wong, Y Xu, X Zhao Transportation Research Record, 03611981241260708, 2024 | | 2024 |
Vehicle Cooperation Around Lane-Changing D Chen, Y Xu, J Sun Transportation Research Board 98th Annual MeetingTransportation Research Board, 2019 | | 2019 |