Publications

This page lists the books and peer-reviewed journal publications included in my official Southeast University profile. For the latest citation data and complete publication records, please visit my Google Scholar and ResearchGate profiles.

Author notation: ^* corresponding author; ^# equal contribution.

Books

• Liu, Z., Gu, Z., & Liu, P. (2025). 交通大数据——理论与方法（第三版）. Zhejiang University Press.
• Liu, Z., Gu, Z., & Liu, P. (2024). Transportation Big Data: Theory and Methods. Elsevier. ISBN 978-0-443-33891-5.

2026

• Huang, D.^*, Liu, Z., Li, T., & Gu, Z. Data-driven departure time and traffic assignment model for intercity multimodal transport system. Computers & Industrial Engineering, 214, 111834.
• Gu, Z., Xu, M., Sun, Q., Jiang, A., Zhao, Y., Yu, A., & Liu, Z.^* A data-empowered online simulation framework with parallel computing capabilities for macroscopic heterogeneous highway traffic flows. Transportation Research Part C: Emerging Technologies, 193, 105919.
• Liu, C., Huang, K.^*, Zhou, H., Gu, Z., Liu, Q., & Liu, Z. HMP-RL: Hierarchical multi-Policy reinforcement learning for truck platooning. Transportation Research Part C: Emerging Technologies, 185, 105579.
• Li, Y., Gu, Z.^*, Zheng, N., Ma, W., & Liu, Z. Two-region mixed autonomy network with park-and-ride: Macroscopic modeling, microscopic validation, and multi-scenario analysis. Transportation Research Part A: Policy and Practice, 211, 105084.
• Gu, Z., Kuang, Y., Vu, H. L., Saberi, M., Liu, Y., & Liu, Z.^* Large-scale transportation governance: A tensorization-parallelization co-empowered framework. The Innovation, 7(4), 101246.
• Huo, J., Liu, Z.^*, Gu, Z.^*, & Chen, C. A hybrid ranking and selection procedure to solve simulation-based discrete network design problems. Transportation Research Part C: Emerging Technologies, 183, 105438.
• Gu, Z., Ru, B., Li, Y., Ma, W., Vu, H. L., Cheng, Q., & Kuang, Y.^* Simulation-based optimization for transportation system analysis: State-of-the-art research and future endeavors. Multimodal Transportation, 5(1), 100253.

2025

• Wang, Z., Cheng, Q., Gu, Z.^*, Liu, C., Cun, D., Shi, X., Wu, X., Zhou, Z., He, X., Vlacic, L., & Liu, Z.^* Analyzing mega-mobility systems in smart cities: A macro–micro integration with feedback paradigm empowered by artificial intelligence. Research, 8, 0982.
• Huo, J.^#, Gu, Z.^#, Liu, Z.^*, Wang, S., & Laporte, G. A heteroscedastic robust Bayesian optimization method for solving simulation-based transportation problems. Transportation Science, 59(6), 1353–1374.
• Zhou, Z.^#, Gu, Z.^#, Liu, P., Yu, W., & Liu, Z.^* Leveraging semi-supervised learning and meta-learning for re-identification in few-shot spatiotemporal anomaly detection. IEEE Transactions on Neural Networks and Learning Systems, 36(11), 19560–19573.
• Liu, Z., Zhou, Z., Gu, Z., Liu, S.^*, Liu, P., Zhang, Y., He, Y., & Zhang, K. TRIP: Transport reasoning with intelligence progression—A foundation framework. Transportation Research Part C: Emerging Technologies, 179, 105260.
• Gu, Z.^#, Hong, Q.^#, Zhou, Z., Geng, X., Liu, Z.^*, & Jia, M. Topological information utilization in label enhancement and label distribution learning based on optimal transport theory. IEEE Transactions on Knowledge and Data Engineering, 37(9), 5666–5678.
• Zhang, K., Sun, L., Kong, D.^*, Xu, Y., Gu, Z.^*, Zhao, Z., & Wang, M. A dynamic continuous flow intersection collaborative control framework based on virtual channelization in an intelligent connected environment. Transportation Research Part C: Emerging Technologies, 175, 105123.
• Shi, Y., Wu, T., Guo, T., Huo, J., Gu, Z.^*, Dai, Y., & Liu, Z.^* Traffic simulation optimization considering driving styles. Communications in Transportation Research, 5, 100181.
• Shi, Y., Liu, C.^*, Sun, Q., Liu, C., Liu, H., Gu, Z., Liu, S., Feng, S., & Wang, R. Real-time bottleneck identification and graded variable speed limit control framework for mixed traffic flow on highways based on deep reinforcement learning. Journal of Transportation Engineering, Part A: Systems, 151(5), 04025017.
• Liu, Z., Jiang, A., Wang, Z., Zhou, Z., Fang, L., Cheng, Q.^*, & Gu, Z.^* An integrated framework for multiple traffic anomalies detection on highways using vehicle trajectories. Computer-Aided Civil and Infrastructure Engineering, 40, 5114–5135.
• Liao, Q., Li, G., Yu, J., Gu, Z., & Ma, W.^* Online prediction-assisted safe reinforcement learning for electric vehicle charging station recommendation in dynamically coupled transportation-power systems. Transportation Research Part C: Emerging Technologies, 176, 105155.
• Cheng, Q., Zhang, Y., Gu, Z.^*, Wang, Z., Liu, H., Lin, Y., & Liu, Z.^* A hybrid physics-based and data-driven approach for car-following behavior modeling and analysis. Transportation Research Part C: Emerging Technologies, 177, 105207.
• Cheng, Q., Dai, G., Ru, B., Liu, Z., Ma, W., Liu, H., & Gu, Z.^* Traffic flow outlier detection for smart mobility using Gaussian process regression assisted stochastic differential equations. Transportation Research Part E: Logistics and Transportation Review, 193, 103840.
• Tang, T., Liu, R.^*, Marsden, G., Gu, Z., & Fu, X. The battle for kerbside space: An evaluation of the competition between car-hailing and bus services. Transportation Research Part A: Policy and Practice, 192, 104392.
• Zhou, Z.^#, Gu, Z.^#, Jiang, A., Liu, Z.^*, Zhao, Y., & Liu, H. Prototype augmentation-based spatiotemporal anomaly detection in smart mobility systems. Transportation Research Part E: Logistics and Transportation Review, 193, 103815.

2024

• Gu, Z., Wang, Y., Ma, W., & Liu, Z.^* A joint travel mode and departure time choice model in dynamic multimodal transportation networks based on deep reinforcement learning. Multimodal Transportation, 3(3), 100137.
• Shi, Y., Gu, Z., Jiang, A., Zhou, D., & Liu, Z.^* HPTSim: A highway parallel traffic simulation framework for mixed concurrency scenarios. IEEE Intelligent Transportation Systems Magazine, 2–20.
• Zhou, Z.^#, Gu, Z.^#, Qu, X., Liu, P., Liu, Z.^*, & Yu, W. Urban mobility foundation model: A literature review and hierarchical perspective. Transportation Research Part E: Logistics and Transportation Review, 192, 103795.
• Yang, Y.^#, Zhang, Y.^#, Gu, Z.^*, Liu, Z., Xi, H., Liu, S., Feng, S., & Liu, Q. Fusing physics-based and data-driven models for car-following modeling: A particle filter approach. Journal of Transportation Engineering, Part A: Systems, 150(12), 04024080.
• Xi, H., Li, M., Hensher, D. A., Xie, C.^*, Gu, Z., & Zheng, Y. Strategizing sustainability and profitability in electric Mobility-as-a-Service (E-MaaS) ecosystems with carbon incentives: A multi-leader multi-follower game. Transportation Research Part C: Emerging Technologies, 166, 104758.
• Gu, Z., Li, Y., Saberi, M., & Liu, Z.^* Simulation-based robust and adaptive optimization method for heteroscedastic transportation problems. Transportation Science, 58(4), 860–875.
• Shi, Y., Liu, J., Liu, C., & Gu, Z.^* DeepAD: An integrated decision-making framework for intelligent autonomous driving. Transportation Research Part A: Policy and Practice, 183, 104069.
• Tang, T., Gu, Z.^*, Yang, Y., Sun, H., Chen, S., & Chen, Y. A data-driven framework for natural feature profile of public transport ridership: Insights from Suzhou and Lianyungang, China. Transportation Research Part A: Policy and Practice, 183, 104049.
• Wang, Z., Liu, Z., Cheng, Q.^*, & Gu, Z.^* Integrated self-consistent macro-micro traffic flow modeling and calibration framework based on trajectory data. Transportation Research Part C: Emerging Technologies, 158, 104439.

2023

• Alhariqi, A., Gu, Z., & Saberi, M.^* Impact of vehicle arrangement in mixed autonomy traffic on emissions. Transportation Research Part D: Transport and Environment, 125, 103964.
• Gu, Z., Li, Y., Saberi, M., Rashidi, T. H., & Liu, Z.^* Macroscopic parking dynamics and equitable pricing: Integrating trip-based modeling with simulation-based robust optimization. Transportation Research Part B: Methodological, 173, 354–381.
• Gu, Z., Yang, X., Zhang, Q., Yu, W., & Liu, Z.^* TERL: Two-stage ensemble reinforcement learning paradigm for large-scale decentralized decision making in transportation simulation. IEEE Transactions on Knowledge and Data Engineering, 35(12), 13043–13054.
• Chen, Y., Gu, Z., Zheng, N., & Vu, H. L.^* Optimal coordinated congestion pricing for multiple regions: A surrogate-based approach. Transportation, 51, 2139–2171.
• Shafiei, S.^*, Gu, Z., Grzybowska, H., & Cai, C. Impact of self-parking autonomous vehicles on urban traffic congestion. Transportation, 50(1), 183–203.
• Shi, Y., Gu, Z.^*, Yang, X., Li, Y., & Chu, Z. An adaptive route guidance model considering the effect of traffic signals based on deep reinforcement learning. IEEE Intelligent Transportation Systems Magazine, 2–15.
• Wang, Z., Shi, Y., Tong, W., Gu, Z., & Cheng, Q.^* Car-following models for human-driven vehicles and autonomous vehicles: A systematic review. Journal of Transportation Engineering, Part A: Systems, 149(8), 04023075.

Earlier Publications

2022

• Gu, Z., Wang, Z., Liu, Z., & Saberi, M.^* Network traffic instability with automated driving and cooperative merging. Transportation Research Part C: Emerging Technologies, 138, 103626.
• Chen, Y.^*, Zhang, Y., & Gu, Z. Differential congestion pricing strategies for heterogeneous users in the mixed traffic condition. Journal of Advanced Transportation, 1829104.
• Zhang, J., Wu, W., Cheng, Q.^*, Tong, W.^*, Khadka, A., Fu, X., & Gu, Z. Extracting the complete travel trajectory of subway passengers based on mobile phone data. Journal of Advanced Transportation, 8151520.
• Mansourianfar, M. H., Gu, Z., & Saberi, M.^* Distance-based time-dependent optimal ratio control scheme (TORCS) in congested mixed autonomy networks. Transportation Research Part C: Emerging Technologies, 141, 103760.
• Alhariqi, A., Gu, Z., & Saberi, M.^* Calibration of the intelligent driver model (IDM) with adaptive parameters for mixed autonomy traffic using experimental trajectory data. Transportmetrica B: Transport Dynamics, 10(1), 421–440.

2021

• Najmi, A., Bostanara, M., Gu, Z., & Rashidi, T. H.^* On-street parking management and pricing policies: An evaluation from a system enhancement perspective. Transportation Research Part A: Policy and Practice, 146, 128–151.
• Gu, Z., Safarighouzhdi, F., Saberi, M., & Rashidi, T. H.^* A macro-micro approach to modeling parking. Transportation Research Part B: Methodological, 147, 220–244.
• Gu, Z., & Saberi, M.^* Simulation-based optimization of toll pricing in large-scale urban networks using the network fundamental diagram: A cross-comparison of methods. Transportation Research Part C: Emerging Technologies, 122, 102894.
• Mansourianfar, M. H., Gu, Z., Waller, S. T., & Saberi, M.^* Joint routing and pricing control in congested mixed autonomy networks. Transportation Research Part C: Emerging Technologies, 131, 103338.
• Ashfaq, M., Gu, Z., Waller, S. T., & Saberi, M.^* Comparing dynamic user equilibrium and noniterative stochastic route choice in a simulation-based dynamic traffic assignment model: Practical considerations for large-scale networks. Journal of Advanced Transportation, 6667335.

2020

• Gu, Z., Najmi, A., Saberi, M., Liu, W., & Rashidi, T. H.^* Macroscopic parking dynamics modeling and optimal real-time pricing considering cruising-for-parking. Transportation Research Part C: Emerging Technologies, 118, 102714.
• Saberi, M.^*, Hamedmoghadam, H., Ashfaq, M., Hosseini, S. A., Gu, Z., Shafiei, S., Nair, D. J., Dixit, V., Gardner, L., Waller, S. T., & González, M. C. A simple contagion process describes spreading of traffic jams in urban networks. Nature Communications, 11, 1616.

2019

• Gu, Z., & Saberi, M.^* A bi-partitioning approach to congestion pattern recognition in a congested monocentric city. Transportation Research Part C: Emerging Technologies, 109, 305–320.
• Gu, Z., Waller, S. T., & Saberi, M.^* Surrogate-based toll optimization in a large-scale heterogeneously congested network. Computer-Aided Civil and Infrastructure Engineering, 34(8), 638–653.

2018

• Gu, Z., Saberi, M., Sarvi, M., & Liu, Z.^* A big data approach for clustering and calibration of link fundamental diagrams for large-scale network simulation applications. Transportation Research Part C: Emerging Technologies, 94, 151–171.
• Gu, Z., Shafiei, S., Liu, Z., & Saberi, M.^* Optimal distance- and time-dependent area-based pricing with the network fundamental diagram. Transportation Research Part C: Emerging Technologies, 95, 1–28.
• Shafiei, S., Gu, Z., & Saberi, M.^* Calibration and validation of a simulation-based dynamic traffic assignment model for a large-scale congested network. Simulation Modelling Practice and Theory, 86, 169–186.

2017

• Lu, L., Gu, Z., Huang, D., Liu, Z.^*, & Chen, J. An evaluation framework for the public information guidance system. KSCE Journal of Civil Engineering, 21(5), 1919–1928.

2016

• Gu, Z., Liu, Z.^*, Shiwakoti, N., & Yang, M. Video-based analysis of school students’ emergency evacuation behavior in earthquakes. International Journal of Disaster Risk Reduction, 18, 1–11.