[1] 王艳丽,李林波,吴兵,马万经.专业课程网络教学效果调研与比较分析——以交通管理与控制课程为例[J].大学教育,2022(10):35-37.

[2] 王艳丽,金宇宁.基于层次分析与云模型的TOD站点衔接设计评价[J].深圳大学学报(理工版),2022,39(02):193-200.

[3] 李自圆,孙昊,李林波.基于手机信令数据的长三角全域城际出行网络分析[J].清华大学学报(自然科学版),2022,62(07):1203-1211.

[4] 王艳丽,李林波,吴兵,马万经.专业课程网络教学效果调研与比较分析——以交通管理与控制课程为例[J].大学教育,2022(10):35-37.

[5] Zhang Y, Zou Y, Wang Y, et al. Understanding the merging behavior patterns and evolutionary mechanism at freeway on-Ramps[J]. Journal of Intelligent Transportation Systems, 2022: 1-14.

[6] Li Y, Li L, Ni D, et al. Automatic Lane-Changing Trajectory Planning: From Self-Optimum to Local-Optimum[J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(11): 21004-21014.

[7] Zhang H, Zou Y, Yang X, et al. A temporal fusion transformer for short-term freeway traffic speed multistep prediction[J]. Neurocomputing, 2022, 500: 329-340.

[8] Ding L, Zhu T, Wang Y, et al. Finite mixture of the hidden Markov model for driving style analysis[J]. Journal of advanced transportation, 2022, 2022.

[9] Lu Y, Cheng K, Zhang Y, et al. Analysis of lane-changing conflict between cars and trucks at freeway merging sections using UAV video data[J]. Journal of Transportation Safety & Security, 2022: 1-19.

[10] Yang X, Zou Y, Chen L. Operation analysis of freeway mixed traffic flow based on catch-up coordination platoon[J]. Accident Analysis & Prevention, 2022, 175: 106780.

[11] Zhang Y, Zou Y, Tang J, et al. Long-term prediction for high-resolution lane-changing data using temporal convolution network[J]. Transportmetrica B: transport dynamics, 2022, 10(1): 849-863.

[12] Wang Y, Jin Y, Mishra S, et al. Integrated travel demand and accessibility model to examine the impact of new infrastructures using travel behavior responses[J]. Journal of Transportation Engineering, Part A: Systems, 2022, 148(1): 05021009.

[13] Wang W, Wang Y, Liu Y, et al. Headway distribution considering vehicle type combinations[J]. Journal of transportation engineering, Part A: Systems, 2022, 148(3): 04021119.