程延秋 讲师

• 学院： 运输工程学院
• 性别： 男
• 出生年月： 1990-05-12
• 职称： 讲师
• 学位： 博士
• 学历： 博士研究生
• 毕业院校： 长安大学
• 联系电话：
• 电子邮箱： yqcheng@chd.edu.cn
• 通讯地址： 陕西省西安市碑林区南二环中段长安大学
• 邮编： 710064
• 传真：
• 办公地址： 长安大学交通科技大厦901
• 教育经历：

  （1）2016-09 至 2022-06, 长安大学, 交通运输规划与管理, 博士

  （2）2018-09 至 2020-07, Missouri University of Science and Technology, Civil, Architectural
  and Environmental Engineering，访问学者

  （3）2013-09 至 2016-06, 长安大学, 交通工程, 硕士
  （4）2008-09 至 2012-06, 长安大学, 交通工程, 学士

程延秋，讲师，硕士生导师，博士毕业于长安大学交通运输规划与管理，2018年至2020年访学于Missouri University of Science and Technology。主要研究方向：1）智能网联车辆行为决策分析。2）城市轨道交通规划与运营管理。已发表SCI学术论文十余篇，其中以第一作者/通讯作者身份发表论文8篇。担任《城市规划原理》、《铁路运输经济学》等课程主讲教师。指导本科生参与并获得“2024年全国大学生交通运输科技大赛省级二等奖”。担任Journal of Intelligent Transportation Systems，Transportmetrica A，Transportation Research Record等多个国内外期刊审稿人。2025年计划招硕士研究生1名，欢迎热爱科学研究、踏实勤奋的同学报考和邮件咨询，也欢迎对交通科学感兴趣的计算机科学、应用数学背景的同学报考和咨询。

（1）城市轨道交通规划与运营管理

（2）智能网联车辆行为决策

城市规划原理（本科生课程）

铁路运输经济学（留学生课程）

（1）中央高校基金，基础研究培育项目，300102344101，典型场景下智能网联车辆混合交通流通行能力分析研究，2024.7-2026.7，5万元，在研，主持。

（2）国家自然科学基金委员会, 青年科学基金项目, 71801019, 基于准移动闭塞的多类干扰影响下高速铁路列车运行调整理论与方法研究, 2019-01-01 至 2021-12-31, 20万元, 结题, 参与。

（3）西安市轨道交通集团有限公司, 服务, 220234220523, 2021年西安市居民出行调查项目, 2022-09 至2024-09, 746万元, 在研, 参与.

（4）西安市自然资源和规划局, 厅局级项目, 211834210473, 关中城市群核心区城市轨道交通线网规划,2020-12 至 2023-12, 326万元, 在研, 参与。

期刊论文:

[1]. Xuewen Xie, Yonggang Wang, Yanlin Jiang, Yanqiu Cheng*, Hui Peng. Metro short-term section passenger flow inherent patterns extraction and prediction: A novel denoising-based method. Physica A: Statistical Mechanics and its Applications. 2025. (DOI:10.1016/j.physa.2024.130233)

[2]. Tian Tian, Yanqiu Cheng*, Yichen Liang, Chen Ma, Kuanmin Chen, Xianbiao  Hu. Hub Nodes Identification in Urban Rail Transit Network Evolution using Ridership Weighted Network. Transportation Research Record: Journal of the Transportation Research Board. 2024. (DOI:10.1177/03611981231217500)

[3]. Chen Ma , Yanqiu Cheng*, Shuang Zhang, Kuanmin Chen, Jie Wei, Xianbiao  Hu. Catchment-Area Delineation Approach Considering Travel Purposes for Station-Level Ridership Prediction Task. Transportation Research Record: Journal of the Transportation Research Board. 2023. (DOI: 10.1177/03611981231189738)

[4]. Shuang Zhang, Yanqiu Cheng*, Kuanmin Chen, Chen Ma, Jie Wei, Xianbiao Hu. A General Metro Timetable Rescheduling Approach for the Minimization of the Capacity Loss after Random Line Disruption. Transportmetrica A: Transport Science, 2023. (DOI: 10.1080/23249935.2023.2204965)

[5].  Shuang Zhang, Chaoqun Ma, Chen Ma, Quan Chen, Sijia Sun, Yanqiu Cheng. Last Train Rapid Synchronizing Approach for Maximum OD Accessibility with Passengers’ Effective Travel Route. Journal of Transportation Engineering Part A-Systems.2023. (DOI:10.1061/JTEPBS.0000777)

[6]. Yanqiu Cheng, Xianbiao Hu*, Kuanmin Chen, Xinlian Yu. Online Longitudinal Trajectory Planning for Connected and Autonomous Vehicles in Mixed Traffic Flow with Deep Reinforcement Learning Approach.Journal of Intelligent Transportation Systems. 2022. (DOI: 10.1080/15472450.2022.2046472)

[7]. Yanqiu Cheng, Qing Tang, Xianbiao Hu*, Hongsheng Qi, Hong Yang. Monte Carlo Tree Search-Based Mixed Traffic Flow Control Algorithm for Arterial Intersection.Transportation Research Record: Journal of the Transportation Research Board. 2020. (DOI:10.1177/0361198120919746)

[8]. Yanqiu Cheng, Xianbiao Hu*, Kuanmin Chen. Enhancing Mixed Traffic Flow Safety via Connected and Autonomous Vehicle Trajectory Planning with a Reinforcement Learning Approach. Journal of Advanced Transportation. 2021. (DOI:10.1155/2021/6117890)

[9]. Jie Wei, Yanqiu Cheng*, Kuanmin Chen, Meng Wang, Chen Ma and Xianbiao Hu. Nonlinear Model-based Subway Station-Level Peak Hour Ridership Estimation Approach in the Context of Peak Deviation. Transportation Research Record: Journal of the Transportation Research Board. 2022. (DOI: 10.1177/03611981221075624)

[10]. Qing Tang, Yanqiu Cheng, Xianbiao Hu*, Ruwen Qin. Evaluation Methodology of Leader-Follower Autonomous Vehicle System for Work Zone Maintenance. Transportation Research Record: Journal of the Transportation Research Board. 2020. (DOI:10.1177/0361198120985233)

[11]. Jie Wei*, Yanqiu Cheng, Lijie Yu, Shuang Zhang, and Kuanmin Chen. Improved approach for forecasting the extra-peak hourly subway ridership at the station level based on LASSO. Journal of Transportation Engineering Part A-Systems.2021. (DOI:10.1061/JTEPBS.0000579)

会议论文:

[1]. Chen Ma, Baixi Shi, Yanqiu Cheng*, Lexing Zhang, Kuanmin Chen. From Lockdown to Recovery: Modeling the Long-term Effects of COVID-19 on Xi'an's Metro Ridership.104th Annual Meeting of Transportation Research Board, 2025, At Washington DC.

[2]. Shuang Zhang, Yaoxin Wu, Laurens Bliek, Yanqiu Cheng*, Yingqian Zhang. An effective Prediction- based Timetable Rescheduling Framework for Mitigating Metro Line Capacity Loss Post-Disruption.104th Annual Meeting of Transportation Research Board, 2025, At Washington DC.

[3]. Wenxuan Wang,Bo Yan,Ying Yan,Yanqiu Cheng*. DEVELOPMENT AND PERFORMANCE OF A DECELERATION-BASED SURROGATE SAFETY MEASURE FOR REAR-END COLLISION RISK.103th Annual Meeting of Transportation Research Board, 2024, At Washington DC.

[4]. Chen Ma , Yanqiu Cheng*, Shuang Zhang, Kuanmin Chen, Jie Wei, Xianbiao  Hu. Catchment areas delineation approach considering travel purposes for station-level ridership prediction task. 102th Annual Meeting of Transportation Research Board, 2023, At Washington DC.

[5]. Shuang Zhang, Yanqiu Cheng*, Chen Ma, Kuanmin Chen, and Xianbiao Hu. General Metro Timetable Rescheduling Method for Reducing Capacity Loss in the Context of Random Line Disruption Based on Emergency Operation Rules. 102th Annual Meeting of Transportation Research Board, 2023, At Washington DC.

[6]. Jie Wei, Yanqiu Cheng*, Kuanmin Chen, Meng Wang, Chen Ma and Xianbiao Hu. Nonlinear Model-based Subway Station-Level Peak Hour Ridership Prediction Approach in the Context of Peak Deviation. 101th Annual Meeting of Transportation Research Board, 2022, At Washington DC.

[7]. Yanqiu Cheng, Xianbiao Hu*. Deep Reinforcement Learning-based Online Longitudinal Trajectory Planning for Connected and Autonomous Vehicles in Mixed Traffic Flow. 25th IEEE International Conference on Intelligent Transportation Systems, 2022, At Macau, China.

[8]. Yanqiu Cheng, Xianbiao Hu*, Qing Tang, Hongsheng Qi. A Model-Free Approach for Connected and Autonomous Vehicles Trajectory Scheduling: Monte Carlo Tree Search-Based Mixed Traffic Flow Control Algorithm. 99th Annual Meeting of Transportation Research Board, 2020, At Washington DC.

[9]. Qing Tang, Yanqiu Cheng, Xianbiao Hu*, Chenxi Chen. Field Testing and Evaluation of Leader-Follower Autonomous Truck Mounted Attenuator Vehicle System for Work Zone Maintenance. 99th Annual Meeting of Transportation Research Board, 2020, At Washington DC.

[10]. Qing Tang, Yanqiu Cheng, Xianbiao Hu*. Quantification of Traffic Impact by Leader-Follower Autonomous Truck Mounted Attenuator Vehicle System for Work Zone Maintenance. 99th Annual Meeting of Transportation Research Board, 2020, At Washington DC.

（1）2023-01 至 今, 在站, 长安大学汽车学院博士后流动站