Journal Publications

Published

  1. Yao, Y., Zhou, Y., Xia, J. Wang, X., Li, X., & Ran, B. (2022). Rolling-Horizon-Based Strategy of Fully Cooperative Traffic under Signalized Intersections. Computer‐Aided Civil and Infrastructure Engineering.
  2. Shi, H., Chen, D., Zheng, N., Wang, X., Zhou, Y., & Ran, B. Distributed Connected Automated Vehicles Control Under Real‐Time Aggregated Macroscopic Car Following Behavior Estimation Based on Deep Reinforcement Learning. Available at SSRN 4119544. [full text]
  3. Shi, H., Dong, S., Wu, Y., Li, S., Zhou, Y., & Ran, B. Generative Adversarial Network for Car Following Trajectory Generation and Anomaly Detection. Available at SSRN 4111253.[full text]
  4. Shi, K., Wu, Y., Shi, H., Zhou, Y., & Ran, B. (2022). An integrated car-following and lane changing vehicle trajectory prediction algorithm based on a deep neural network. Physica A: Statistical Mechanics and its Applications, 127303.[full text]
  5. Shi, H., Zhou, Y., Wang, X., Fu, S., Gong, S., & Ran, B. (2022). A deep reinforcement learning‐based distributed connected automated vehicle control under communication failure. Computer‐Aided Civil and Infrastructure Engineering. [full text]
  6. Chen, T., Wang, M., Gong, S., Zhou, Y., & Ran, B. (2021).Connected and automated vehicle distributed control for on-ramp merging scenario: A virtual rotation approach. Transportation Research Part C: Emerging Technologies,133, 103451. [full text]
  7. Shi, H., Zhou, Y., Wu, K., Wang, X., Lin, Y., & Ran, B. (2021).Connected automated vehicle cooperative control with a deep reinforcement learning approach in a mixed traffic environment. Transportation Research Part C: Emerging Technologies, 133, 103421. [full text]
  8. Dong, S., Zhou, Y., Chen, T., Li, S., Gao, Q., & Ran, B. (2021). An integrated Empirical Mode Decomposition and Butterworth filter based vehicle trajectory reconstruction method. Physica A: Statistical Mechanics and its Applications583, 126295.[full text]
  9. Li, S., Shu, K., Zhou, Y., Cao, D., & Ran, B. (2021). Cooperative critical turning point-based decision-making and planning for CAVH intersection management system. IEEE Transactions on Intelligent Transportation Systems. [full text]
  10. Shi, H., Nie, Q., Fu, S., Wang, X., Zhou, Y., & Ran, B. (2021). A distributed deep reinforcement learning–based integrated dynamic bus control system in a connected environment. Computer‐Aided Civil and Infrastructure Engineering. [full text]
  11. Yi, R., Zhou, Y., Wang, X., Liu, Z., Li, X., & Ran, B. (2021). Infrastructure Assisted Constrained Connected Automated Vehicle Trajectory Optimization on Curved Roads: A Spatial Formulation on a Curvilinear Coordinate. arXiv preprint arXiv:2103.00699. [full text]
  12. Li, S., Cheng, Y., Jin, P., Ding, F., Li, Q., & Ran, B. (2020). A Feature-Based Approach to Large-Scale Freeway Congestion Detection Using Full Cellular Activity Data. IEEE Transactions on Intelligent Transportation Systems. [full text]
  13. Li, S., Li, G., Cheng, Y., & Ran, B. (2020). Urban arterial traffic status detection using cellular data without cellphone GPS information. Transportation research part C: emerging technologies114, 446-462. [full text]
  14. Ding, F., Zhang, Z., Zhou, Y., Chen, X., & Ran, B. (2019). Large-scale full-coverage traffic speed estimation under extreme traffic conditions using a big data and deep learning approach: Case study in China. Journal of Transportation Engineering, Part A: Systems145(5), 05019001. [full text]
  15. Ran, B., Cheng, Y., Leight, S., & Parker, S. (2019). Development of an Integrated Transportation System of Connected Automated Vehicles and Highways. ITE Journal89(11). [full text]

Under Revision

  1. Shi, H., Zhou, Y., Wu, K., Chen, S., & Ran, B. A physics-informed deep reinforcement learning-based integrated two-dimensional car-following control strategy for connected automated vehicles. Knowledge-Based Systems. (Under Revision)

Last updated: July 07, 2022