[1] H. Zhao, H. Wu, N. Lu, et al. Research on a Vehicle Lane-Changing Model in the Tunnel Area by Considering the Influence of Brightness and Noise Under a Vehicle-to-Everything Environment. IEEE Intelligent Transportation Systems Magazine, 2022.（SCI）
[2] Peng G, Luo C , Zhao H,et al. A novel lattice model integrating the cooperative deviation of density and optimal flux under V2X environment[J]. Chinese Physics B, 2022.（SCI）
[3] Zhao HZ, Yue H, et al.Low Delay and Seamless Connectivity‑based Message Propagation Mechanism for VANET of VCPS[J]. Wireless Personal Communications. 2021, 118(4):3385-3402.（SCI）
[4] Zhao H, Yue H,et al. An optimisation method for a co-operative driving system at road junctions[J]. Proceedings of the Institution of Civil Engineers-Transport. 2021, 174(6): 354-366.（SCI）
[5] ZHAO, Hongzhuan, et al. The delayed-time effect of traffic flux on traffic stability for two-lane freeway. Physica A: Statistical Mechanics and its Applications, 2020, 540: 123066.（SCI）
[6] Peng G, Kuang H, Zhao H, et al. Nonlinear analysis of a new lattice hydrodynamic model with the consideration of honk effect on flux for two-lane highway[J]. Physica A: Statistical Mechanics and its Applications, 2019, 515: 93-101.（SCI）
[7] Peng G, Zhao H, Li X. The impact of self-stabilization on traffic stability considering the current lattice’s historic flux for two-lane freeway[J]. Physica A: Statistical Mechanics and its Applications, 2019, 515: 31-37.（SCI）
[8] ZHAO, Hongzhuan, et al. Stability analysis of an improved car-following model accounting for the driver’s characteristics and automation. Physica A: Statistical Mechanics and its Applications, 2019, 526: 120990. (SCI)
[9] Peng G, Yang S, Zhao H, et al. The flux difference memory integral effect on two-lane stability in the lattice hydrodynamic model[J]. International Journal of Modern Physics C, 2018, 29(09): 1850083.（SCI）
[10] Peng G, Yang S, Zhao H. The difference of drivers' anticipation behaviors in a new macro model of traffic flow and numerical simulation[J]. Physics Letters A, 2018, 382(36): 2595-2597.（SCI）
[11] Peng G, Yang S, Zhao H. A delayed-feedback control method for the lattice hydrodynamic model caused by the historic density difference effect[J]. Physica A: Statistical Mechanics and its Applications, 2018, 509: 855-860.（SCI）
[12] Peng GH, Yang SH, Zhao HZ. New Feedback Control Model in the Lattice Hydrodynamic Model Considering the Historic Optimal Velocity Difference Effect[J]. COMMUNICATIONS IN THEORETICAL PHYSICS. 2018, 70(6):803-807.（SCI）
[13] Zhao H, Zhang G, Li W, et al. Lattice hydrodynamic modeling of traffic flow with consideration of historical current integration effect[J]. Physica A: Statistical Mechanics and its Applications, 2018, 503, 1204-1211.（SCI）
[14] Sun D, Zhao H, et al. ST TD outlier detection[J]. IET Intelligent Transport Systems, 2017, 11(4): 203-211.（SCI）
[15] Zhao, Hongzhuan, Sun, Dihua, et al.Using CSTPNs to model traffic control CPS[J]. IET Software, 2017, 11(3): 116-125.（SCI）
[16] Sun, Dihua,Zhao, Hongzhuan, et al. A novel membership cloud model‐based trust evaluation model for vehicular ad hoc network of T‐CPS[J]. Security and Communication Networks, 2017, 9(18): 5710-5723.（SCI）
[17] Zhao, Hongzhuan, Sun, Dihua, et al. A novel CPS-based vehicle safety state evaluation scheme [J].PI CIVIL ENG-TRANSP. 2016,169(1): 12-23.（SCI）
[18] Zhao, Hongzhuan, Sun, Dihua, et al. A Multi-Classification Method of Improved SVM-based Information Fusion for Traffic Parameters Forecasting[J]. PROMET-Traffic &Transportation, 2016, 28(2): 117-124.（SCI）
[19] ZHAO, Hongzhuan, et al. CPS-Based Reliability Enhancement Mechanism for Vehicular Emergency Warning System. International Journal of Intelligent Transportation Systems Research, 2019, 17.3: 232-241. (EI)
[20] Zhao H, Sun D, Yue H, et al. Dynamic Trust Model for Vehicular Cyber-Physical Systems[J]. International Journal of Network Security, 2018, 20(1): 157-167. (EI)
[21] 赵红专，孙棣华等. 一种离散与连续混成的时空事件驱动的CPS体系架构[J].哈尔滨工业大学学报, 2016, 48(9):171-175.（EI）