Li, X. W. D. J., Ye, X., & Sun, Q. (2024). Leveraging Connected Vehicle Data for Near-Crash Detection and Analysis in Urban Environments. In arXiv preprint arXiv:2409.11341.
@unpublished{li2024leveraging,
title = {Leveraging Connected Vehicle Data for Near-Crash Detection and Analysis in Urban Environments},
author = {Li, Xinyu Wu Dayong(Jason) and Ye, Xinyue and Sun, Quan},
journal = {arXiv preprint arXiv:2409.11341},
year = {2024},
file = {Leveraging Connected Vehicle Data for Near-Crash and Analysis in Urban Environments.pdf}
}
Refereed journal articles
Ye, Xinyue and Du, Jiaxin and Li, Xinyu* and Shaw, Shih-Lung and Fu, Yanjie and Dong, Xishuang and Zhang, Zhe and Wu, Ling. (2025). Human-centered GeoAI foundation models: where GeoAI meets human dynamics. Urban Informatics, 4(1), 2.
@article{ye2025human,
title = {Human-centered GeoAI foundation models: where GeoAI meets human dynamics},
author = {{Ye, Xinyue and Du, Jiaxin and Li, Xinyu* and Shaw, Shih-Lung and Fu, Yanjie and Dong, Xishuang and Zhang, Zhe and Wu, Ling}},
journal = {Urban Informatics},
volume = {4},
number = {1},
pages = {2},
year = {2025},
publisher = {Springer},
doi = {https://doi.org/10.1007/s44212-025-00067-x},
file = {Human-centered GeoAI foundation models where GeoAI meets human dynamics.pdf}
}
Li, Xinyu and Xu, Yang* and Zhang, Xiaohu and Shi, Wenzhong and Yue, Yang and Li, Qingquan. (2023). Improving short-term bike sharing demand forecast through an irregular convolutional neural network. Transportation Research Part C: Emerging Technologies, 147, 103984.
@article{li2023improving,
title = {Improving short-term bike sharing demand forecast through an irregular convolutional neural network},
author = {{Li, Xinyu and Xu, Yang* and Zhang, Xiaohu and Shi, Wenzhong and Yue, Yang and Li, Qingquan}},
journal = {Transportation research part C: emerging technologies},
volume = {147},
pages = {103984},
year = {2023},
publisher = {Elsevier},
doi = {https://doi.org/10.1016/j.trc.2022.103984},
file = {Improving short-term bike sharing demand forecast through an irregular convolutional neural network.pdf}
}
Xu, Yang* and Zou, Dan and Park, Sangwon and Li, Qiuping and Zhou, Suhong and Li, Xinyu. (2022). Understanding the movement predictability of international travelers using a nationwide mobile phone dataset collected in South Korea. Computers, Environment and Urban Systems, 92, 101753.
@article{xu2022understanding,
title = {Understanding the movement predictability of international travelers using a nationwide mobile phone dataset collected in South Korea},
author = {{Xu, Yang* and Zou, Dan and Park, Sangwon and Li, Qiuping and Zhou, Suhong and Li, Xinyu}},
journal = {Computers, Environment and Urban Systems},
volume = {92},
pages = {101753},
year = {2022},
publisher = {Elsevier},
doi = {https://10.1109/TITS.2021.3097240},
file = {Understanding the movement predictability of international travelers using a nationwide mobile phone dataset collected in South Korea.pdf}
}
Li, Xinyu and Xu, Yang* and Chen, Qi and Wang, Lei and Zhang, Xiaohu and Shi, Wenzhong. (2021). Short-term forecast of bicycle usage in bike sharing systems: a spatial-temporal memory network. IEEE Transactions on Intelligent Transportation Systems, 23(8), 10923–10934.
@article{li2021short,
title = {Short-term forecast of bicycle usage in bike sharing systems: a spatial-temporal memory network},
author = {{Li, Xinyu and Xu, Yang* and Chen, Qi and Wang, Lei and Zhang, Xiaohu and Shi, Wenzhong}},
journal = {IEEE Transactions on Intelligent Transportation Systems},
volume = {23},
number = {8},
pages = {10923--10934},
year = {2021},
publisher = {IEEE},
doi = {https://10.1109/TITS.2021.3097240},
file = {Short-Term_Forecast_of_Bicycle_Usage_in_Bike_Sharing_Systems_A_Spatial-Temporal_Memory_Network.pdf}
}
Xu, Yang* and Li, Xinyu and Shaw, Shih-Lung and Lu, Feng and Yin, Ling and Chen, Bi Yu. (2020). Effects of data preprocessing methods on addressing location uncertainty in mobile signaling data. Annals of the American Association of Geographers, 111(2), 515–539.
@article{xu2020effects,
title = {Effects of data preprocessing methods on addressing location uncertainty in mobile signaling data},
author = {{Xu, Yang* and Li, Xinyu and Shaw, Shih-Lung and Lu, Feng and Yin, Ling and Chen, Bi Yu}},
journal = {Annals of the American Association of Geographers},
volume = {111},
number = {2},
pages = {515--539},
year = {2020},
publisher = {Taylor \& Francis},
doi = {https://doi.org/10.1080/24694452.2020.1773232},
file = {Effects of Data Preprocessing Methods on Addressing Location Uncertainty in Mobile Signaling Data}
}
Refereed conference proceedings
Quan Sun, Xinyu Li*, Dayong Wu, Tianchen Huang, Xinyue Ye and Wei Li. (2024). Assessing Volume Delay Function Accuracy Through Multi-Source Traffic Data: Insights from Connected Vehicle Data and Traffic Simulation Data. Accepted by the TRB Annual Meeting 2025.
@inproceedings{Li2025TRB,
author = {{Quan Sun, Xinyu Li*, Dayong Wu, Tianchen Huang, Xinyue Ye and Wei Li}},
title = {Assessing Volume Delay Function Accuracy Through Multi-Source Traffic Data: Insights from Connected Vehicle Data and Traffic Simulation Data},
note = {Accepted by the TRB Annual Meeting 2025},
year = {2024}
}
Xinyu Li, Y. X., & Zhang, R. (2023). CPGIS 2023 Programme. Accessed: 2024-09-03.
@inproceedings{CPGIS2023,
author = {Xinyu Li, Yang Xu and Zhang, Ruojing},
title = {CPGIS 2023 Programme},
year = {2023},
note = {Accessed: 2024-09-03},
file = {CPGIS_2023_programme.pdf}
}
This study proposes a deep learning model to predict short-term bike sharing usage through feature fusion in spatial and topological domains across two station-based bike-sharing systems in Chicago and New York. Based on the prediction results, the proposed model performs better than the baseline models. The results imply that the prediction model leveraging bike-sharing usage’s spatial and topological features outperforms the model only using spatial features.
Xinyu Li, Y. X. (2021). Short-Term Forecast of Bicycle Usage in Bike Sharing Systems: A Spatial-Temporal Memory Network. Proceedings of The 4th International Symposium on Multimodal Transportation. Webinar.
@inproceedings{Li2021Multimodal,
author = {Xinyu Li, Yang Xu},
title = {Short-Term Forecast of Bicycle Usage in Bike Sharing Systems: A Spatial-Temporal Memory Network},
booktitle = {Proceedings of The 4th International Symposium on Multimodal Transportation},
year = {2021},
note = {Webinar}
}
Xinyu Li, Y. X. (2021). Short-Term Forecast of Bicycle Usage in Bike Sharing Systems: A Spatial-Temporal Memory Network. Proceedings of The 2021 City+ Milan Conference. Webinar, Theme: Smart City Beyond.
@inproceedings{Li2021CityPlus,
author = {Xinyu Li, Yang Xu},
title = {Short-Term Forecast of Bicycle Usage in Bike Sharing Systems: A Spatial-Temporal Memory Network},
booktitle = {Proceedings of The 2021 City+ Milan Conference},
year = {2021},
address = {Milan, Italy},
note = {Webinar, Theme: Smart City Beyond}
}