Contact: Rm 1011, No. 2 SEU Road Nanjing, China Email: qixiu[dot]cheng[at]seu[dot]edu[dot]cn qixiu[dot]kevin[dot]cheng[at]gmail[dot]com
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Research Interests
Traffic Flow Theory
Transportation Network Optimization
AI Algorithms in Transportation
Selected Journal Publications
Wang, Z., Lin, Y., Liu, Z., Dong, Y., Zheng, Y., Liu, P., & Cheng, Q. (2026). Traffic dynamics modeling with an extended S3 car following model. Transportation Research Part C, 183, 105494. [URL]
Zhou, Y., Cheng, Q., Zhang, C., Luo, M., & Liu, Z. (2026). Stochastic Fundamental Diagram Modeling Using Asymmetric Vine and Nested Archimedean Copulas. Transportation Research Part B, 203, 103350. [URL]
Wang, Z., Liu, Z., Lin, Y., Zhang, Y., & Cheng, Q. (2026). Day-to-day traffic flow dynamics with mixed autonomy considering link-level penetration rate evolution of autonomous vehicles. Proceedings of the IEEE, 114(4), 658-677. [URL]
Hong, K., Wu, Y., Xin, Y., Cheng, Q., Huang, K., & Liu, Z. (2026). Corner Case Detection in Autonomous Driving with Deep Learning. IEEE Transactions on Vehicular Technology, 75(6), 9296-9310. [URL]
Wang, Z., Cheng, Q., Gu, Z., Liu, C., Cun, D., Shi, X., Wu, X., Zhou, Z., He, X., Vlacic, L., & Liu, Z. (2025). Analyzing mega-mobility systems in smart cities: A macro-micro integration with feedback paradigm empowered by artificial intelligence. Research, 9, 0982. [URL]
Shao, F., Shao, H., Wu, X., Cheng, Q., & Lam, W.H.K. (2025). A Physics-Informed Machine Learning Framework for Speed-Flow Prediction: Integrating an S-Shaped Traffic Stream Model with Deep Learning Models. Transportation Research Part C, 180, 105362. [URL]
Cheng, Q., Hong, K., Huang, K., & Liu, Z. (2025). Evaluating effectiveness and identifying appropriate methods for anomaly detection in intelligent transportation systems. IEEE Transactions on Intelligent Transportation Systems, 26(8), 11442-11453. [URL]
Cheng, Q., Zhang, Y., Gu, Z., Wang, Z., Liu, H., Lin, Y., & Liu, Z. (2025). A hybrid physics-based and data-driven approach for car-following behavior modeling and analysis. Transportation Research Part C, 177, 105207. [URL]
Cheng, Q., Song, Q., Wang, Z., Lin, Y., & Liu, Z. (2025). Capturing traffic flow state variation process: An analytical modeling approach. Transportation Research Part E, 198, 104119. [URL]
Cheng, Q., Dai, G., Ru, B., Liu, Z., Ma, W., Liu, H., & Gu, Z. (2025). Traffic flow outlier detection for smart mobility using Gaussian process regression assisted stochastic differential equations. Transportation Research Part E, 193, 103840. [URL]
Wang, Z., Cheng, Q., Liu, P., Yu, W., Wang, J., & Liu, Z. (2025). Energy and environmental implications of automated vehicles under mixed autonomy traffic environment. IEEE Transactions on Intelligent Vehicles, 10(2), 1226-1240. [URL]
Yang, X., Liu, Z., Cheng, Q., & Liu, P. (2024). Geometry-aware car-following model construction: Theoretical modeling and empirical analysis on horizontal curves. Transportation Research Part C, 166, 104772. [URL]
Cheng, Q., Liu, Z., Lu, J., List, G., Liu, P., & Zhou, X. (2024). Using frequency domain analysis to elucidate travel time reliability along congested freeway corridors. Transportation Research Part B, 184, 102961. [URL]
Wang, Z., Liu, Z., Cheng, Q., & Gu, Z. (2024). Integrated self-consistent macro-micro traffic flow modelling and calibration framework based on trajectory data. Transportation Research Part C, 158, 104439. [URL]
Cheng, Q., Lin, Y., Zhou, X., & Liu, Z. (2024). Analytical formulation for explaining the variation of traffic states: A fundamental diagram modeling perspective with stochastic parameters. European Journal of Operational Research, 312(1), 182-197. [URL]
Huo, J., Liu, Z., Chen, J., Cheng, Q., & Meng, Q. (2023). Bayesian optimization for congestion pricing problems: A general framework and its instability. Transportation Research Part B, 169, 1-28. [URL]
Cheng, Q., Liu, Z., Guo, J., Wu, X., Pendyala, R., Belezamo, B., & Zhou, X. (2022). Estimating key traffic state parameters through parsimonious spatial queue models. Transportation Research Part C, 137, 103596. [URL]
Liu, Z., Wang, Y., Cheng, Q., & Yang, H. (2022). Analysis of the information entropy on traffic flows. IEEE Transactions on Intelligent Transportation Systems, 23(10), 18012-18023. [URL]
Cheng, Q., Liu, Z., Lin, Y., & Zhou, X. (2021). An s-shaped three-parameter (S3) traffic stream model with consistent car following relationship. Transportation Research Part B, 153, 246-271. [URL]
Liu, Z., Wang, Z, Cheng, Q., Yin, R., & Wang, M. (2021). Estimation of urban network capacity with second-best constraints for multimodal transport systems. Transportation Research Part B, 152, 276-294. [URL]
An, Q., Fu, X., Huang, D., Cheng, Q., & Liu, Z. (2020). Analysis of adding-runs strategy for peak-hour regular bus services. Transportation Research Part E, 143, 102100. [URL]
Cheng, Q., Wang, S., Liu, Z., & Yuan, Y. (2019). Surrogate-based simulation optimization approach for day-to-day dynamics model calibration with real data. Transportation Research Part C, 105, 422-438. [URL]
Liu, Z., Liu, Y., Meng, Q., & Cheng, Q. (2019). A tailored machine learning approach for urban transport network flow estimation. Transportation Research Part C, 108, 130-150. [URL]
Liu, Z., Wang, S., Zhou, B., & Cheng, Q. (2017). Robust optimization of distance-based tolls in a network considering stochastic day to day dynamics. Transportation Research Part C, 79, 58-72. [URL]