Publications

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Selective Journal and Book Chapter Publications (*: corresponding author)

1. Zhenfang Zeng, Wei Yue, and Lei Zhu. "Finite-time fuzzy cooperative control for multi-AUV systems under cyber-attacks with hybrid unknown nonlinearities." Ocean Engineering 304 (2024): 117875.

2. Lei Lin, Weizi Li, and Lei Zhu*. "Data-Driven Graph Filter-Based Graph Convolutional Neural Network Approach for Network-Level Multi-Step Traffic Prediction." Sustainability 14, no. 24 (2022): 16701.

3. Lei Zhu, Jinghui Wang*, Yuqiu Yuan, and Wei Wu. 2022. “Mode Split Equilibrium Microsimulation Approach for Early-Stage On-Demand Shared Automated Mobility,” Sensors 22, no. 20: 8020. 2022 https://doi.org/10.3390/s22208020

4. Lei Zhu, Brennan Borlaug, Lei Lin, Jacob Holden, and Jeffrey Gonder, “Light-Duty Vehicle Trip Classification using One-Class Novelty Detection and Exhaustive Feature Extraction,” in IEEE Transactions on Industry Applications, vol. 58, no. 3, pp. 3936-3945, May-June 2022, doi: 10.1109/TIA.2022.3149848.

5. Shreya Lohar, Lei Zhu*, Stanley Young, Peter Graf, and Michael Blanton. 2021. "Sensing Technology Survey for Obstacle Detection in Vegetation" Future Transportation 1, no. 3: 672-685. https://doi.org/10.3390/futuretransp1030036

6. Joseph Severino, Yi Hou, Ambarish Nag, Jacob Holden, Lei Zhu, Juliette Ugirurmurera, Stanley Young, Wesley Jones, and Jibonananda Sanyal, “Real-Time Highly Resolved Spatial-Temporal Vehicle Energy Consumption Estimation Using Machine Learning and Probe Data,” Transportation Research Record, (September 2021). https://doi.org/10.1177/03611981211039163. 

7. Lei Zhu, Zhouqiao Zhao, Guoyuan Wu, "Shared Automated Mobility with Demand-Side Cooperation: A Proof-of-Concept Microsimulation Study" Sustainability 13, no. 5: 2483. 2021, https://doi.org/10.3390/su13052483

8. Hamid Mirzahossein, Iman Gholampour, Maryam Sedghi, and Lei Zhu, “How Realistic is Static Traffic Assignment? Analyzing Automatic Number-Plate Recognition Data and Image Processing of Real-Time Traffic Maps for Investigation,” Transportation Research Interdisciplinary Perspectives, Volume 9, 2021, https://doi.org/10.1016/j.trip.2021.100320.

9. J. Sam Lott, Stanley Young, and Lei Zhu, "Safe Operations at Roadway Junctions-Design Principles from Automated Guideway Transit." SAE International Journal of Advances and Current Practices in Mobility, 4, no. 2021-01-1004 (2021): 260-269. https://doi.org/10.4271/2021-01-1004.

10. H M Abdul Aziza, Venu Garikapati, Tony K. Rodriguez, Lei Zhu, Bingrong Sun, Stanley Young, and Yuche Chen, “An Optimization-based Planning Tool for On-Demand Mobility Service Operations,” International Journal of Sustainable Transportation, DOI: 10.1080/15568318.2020.1847368, 2020

11. Zijia Zhong, Lei Zhu*, and Stanley Young, “Approximation Framework of Embodied Energy of Safety: Insights and Analysis,” Energies 13, no. 16: 4230., 2020, https://doi.org/10.3390/en13164230 

12. Yantao Huang, Kara Kockelman, Venu Garikapati, Lei Zhu, and Stanley Young, “Use of Shared Automated Vehicles for First-Mile Last-Mile Service: Micro-Simulation of Rail-Transit Connections in Austin, Texas,” Transportation Research Record, Nov. 2020, doi:10.1177/0361198120962491.

13. L. Zhu, J. Wang, V. Garikapati, and S. Young. “Decision Support Tool for Planning Neighborhood-Scale Deployment of Low-Speed Shared Automated Shuttles.” Transportation Research Record, (July 2020). doi:10.1177/0361198120925273.

14. A. Mohamed, L. Zhu, A. Meintz, and E. Wood, “Planning Optimization for Inductively Charged On-demand Automated Electric Shuttles Project at Greenville, South Carolina,” in IEEE Transactions on Industry Applications, vol. 56, no. 2, pp. 1010-1020, March-April 2020. 

15. Y. Li, L. Zhu, J. Sun, and Y. Tian, “Generating a Spatiotemporal Dynamic Map for Traffic Analysis Using Macroscopic Fundamental Diagram,” Journal of Advanced Transportation, vol. 2019, Article ID 9540386, 15 pages, 2019. https://doi.org/10.1155/2019/9540386.

16. A. Mohamed, A. Meintz, and L. Zhu, “System Design and Optimization of In-route Wireless Charging Infrastructure for Shared Automated Electric Vehicles,” IEEE Access, vol. 7, pp. 79968-79979, 2019. doi: 10.1109/ACCESS.2019.2920232

17. L. Zhu, J. Gonder, E. Bjärkvik, B. Lindenberg, M. Pourabdollah and K. Burgdorf, “An Autonomous Vehicle Fuel Economy Benefits Evaluation Framework Using Real-World Travel and Traffic Data,” IEEE Intelligent Transportation Systems Magazine, vol. 11, no. 3, pp. 29-41, Fall 2019. 

18. L. Lin, J. C. Handley, Y. Gu, L. Zhu, X. Wen, A. W. Sadek, “Quantifying Uncertainty in Short-term Traffic Prediction and its Application to Optimal Staffing Plan Development”, Transportation Research Part C: Emerging Technologies. Volume 92, Pages 323-348, 2018

19. L. Zhu and J. Gonder, “A Driving Cycle Detection Approach Using Map Service API,” Transportation Research Part C: Emerging Technologies. Volume 92, Pages 349-363, 2018

20. J. Holden, H. Van Til, E. Wood, L. Zhu, J. Gonder, and M. Shirk, “Trip Energy Estimation Methodology and Model Based on Real-World Driving Data for Green Routing Applications,” Transportation Research Record: Journal of the Transportation Research Board, 0361-1981, 2018. doi: 10.1177/0361198118798286.

21. L. Zhu, J. Holden, and J. Gonder, “Navigation Application Programming Interface Route Fuel Saving Opportunity Assessment on Large-Scale Real-World Travel Data for Conventional Vehicles and Hybrid Electric Vehicles ,” Transportation Research Record, 2672(25), 139–149.  

22. L. Zhu, J. Holden and J. Gonder, “Trajectory Segmentation Map-Matching Approach for Large-Scale, High-Resolution GPS Data”, Transportation Research Record: Journal of the Transportation Research Board 2017, Vol. 2645: 67-75, 2017. DOI: 10.3141/2645-08

23. L. Zhu, J. Gonder, L. Lin, “Prediction of Individual Social-Demographic Role Based on Travel Behavior Variability Using Long-Term GPS Data”, Journal of Advanced Transportation. Volume 2017 (2017), Article ID 7290248, 13 pages, DOI: https://doi.org/10.1155/2017/7290248, 2017.

24. Y. Chen, L. Zhu, J. Gonder, S. Young, and K. Walkowicz, "Data-driven fuel consumption estimation: A multivariate adaptive regression spline approach", Transportation Research Part C: Emerging Technologies, Volume 83, 2017, pp. 134-145, DOI: https://doi.org/10.1016/j.trc.2017.08.003., 2017.

25. L. Zhu, Y.C. Chiu and Y. Chen, "A Road Network Abstraction Approach for Traffic Analysis: Framework and Numerical Analysis", IET Intelligent Transport Systems, 18 pp. DOI:  10.1049/iet-its.2016.0287, 2017.

26. L. Zhu and Y.C. Chiu, “Transportation Routing Map Abstraction Approach: Algorithm and Numerical Analysis”, Transportation Research Record: Journal of Transportation Research Board, DOI: 10.3141/2528-09.,15-5162, 2015.

27. X. Hu, Y.C. Chiu, Y.L. Ma and L. Zhu, “Studying Driving Risk Factors using Multi-Source Mobile Computing Data”, International Journal of Transportation Science and Technology, 4(3), pp. 295–312, 2015.

28. X. Hu, Y.C. Chiu and L. Zhu, “Behavior Insights for an Incentive-Based Active DemandManagement Platform”, International Journal of Transportation Science and Technology, vol. 4, no.2, p119 – 134, 2015

29. M. Wang, X. Bao, L. Zhu and Y.L. Bao, “A Map-matching Method UsingIntersection-based Parallelogram Criterion”, Advanced Materials Research 403, 2746-2750, DOI: 10.4028/www.scientific.net/AMR.403-408.2746, 2012.

30. L. Zhu, Y.L. Bao, S.G. Wang, Q. Zhou and X. Bao, “Map-Matching compatible with junction adjusting in Vehicle navigation system” Recent Advances in Computer Science and Information Engineering, 451-457, DOI: https://doi.org/10.1007/978-3-642-25778-0_62, 2012.

31. L.B. Bai, L. Zhu and Y.L. Bao, “Traffic Broadcasting Digital Map Service System with Multi-correspondence”, Electronic Technology, Vol 9, p17, 2009. 

32. L. Zhu and Y.L. Bao, “Supplementation of Present Domestic Radio Traffic Information Service System”, Computer System& Applications, Vol 8, p25-28, 2009.