毛其超

毛其超，男，1995 年 7 月生，博士，讲师。2026 年毕业于同济大学计算机科学与技术学院，获工学博士学位。主要从事无人驾驶车群、多车辆协同感知、车路云感通算一体化等前沿方向研究。博士期间作为核心成员参与多项国家自然科学基金等项目。近五年在IEEE Transactions on Mobile Computing (TMC)、IEEE Transactions on Intelligent Transportation Systems (TITS)、IEEE Transactions on Vehicular Technology (TVT)、IEEE Transactions on Network Science and Engineering (TNSE)和IEEE Internet of Things Journal (IOTJ)等国内外高水平期刊及CVPR和ICML等会议发表学术论文30余篇，出版专著1部，授权国家发明专利10余项。长期担任多个国际权威期刊与会议审稿人。

一、论文与专著

专著：

1. Cheng, Jiujun., Zhou, MengChu, Yuan, Guiyuan., Mao, Qichao. Autonomous Vehicle Group: Formation, Evolution, and Cooperation in Internet of Vehicles[M]//Franzè G, Fortino G, Lucia W, Zhou M, eds. Constrained Control and Machine Learning: Emerging Methodologies and Applications. Cham: Springer, 2026.

期刊/会议论文：

1. Mao Qichao, Cheng Jiujun*, Zhou MengChu*, Gao Shangce, Li Chuanhuang* et al. Contributed Perception-based Dynamic Evolution Method for Autonomous Vehicle Groups [J]. IEEE Transactions on Mobile Computing (TMC), 2025, 24(12): 13441-13458. (中科院一区, TOP, CCF-A 期刊, IF: 9.2, 第一作者)

2. Mao Qichao, Qiao Sibo, Yao Jiamin, Cui Zhe, Lyu Zhihan*, et al. TinyML-Driven Distributed Collaborative Computing for Autonomous Vehicle Groups in Open Scenes [J]. IEEE Transactions on Intelligent Transportation Systems (TITS), 2025.(中科院一区, TOP, CCF-B, IF: 8.4, 第一作者)

3. Mao Qichao, Cheng Jiujun*, Zhou MengChu*, Li Chuanhuang*, et al. Edge Computing-based Contributed Perception and Autonomous Vehicle Groups in Open Scenes[J] IEEE Transactions on Intelligent Transportation Systems (TITS), 2025, 26(11): 19697-19708. (中科院一区,TOP, CCF-B, IF: 8.4, 第一作者)

4. Mao Qichao, Cheng Jiujun*, Zhou MengChu*, Han Shoufei, et al. An Edge Computing-based Autonomous Vehicle Group Cooperation Model in a Highway Scene[J]. IEEE Transactions on Vehicular Technology (TVT), 2024, 73(7): 9682-9695. (中科院二区, TOP, IF: 7.1, 第一作者)

5. Mao Qichao, Sun Hongmei, Jia Ruisheng*, et al. Finding every car: a traffic surveillance multi-scale vehicle object detection method[J]. Applied Intelligence, 2020, 50: 3125-3136 (中科院三区, IF: 3.5, 第一作者).

6. Cheng, Jiujun., Zhong Haowen, Mao, Qichao*. 3D MeanFlow: One-Step Point Cloud Completion and Generation via Average-Velocity Transport[C]//Proceedings of the 42nd International Conference on Machine Learning (ICML), 2026. (CCF-A类会议, 通讯作者)

7. Zhang Qiuyang, Cheng Jiujun*, Mao Qichao*, et al. SpikeTrack: A Spike-driven Framework for Efficient Visual Tracking//[C]. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2026 (CCF-A类会议, 通讯作者).

8. Wu Yulu, Cheng Jiujun*, Wang Haowen*, Mao Qichao*, et al. AOMGen: Photoreal, Physics-Consistent Demonstration Generation for Articulated Object Manipulation//[C]. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Findings (CVPR Findings), 2026 (CCF-A类会议 Findings, 通讯作者).

9. Yao Jiamin,Mao Qichao*, Qiao Sibo, et al. 6G-Enabled Autonomous Vehicle Clusters in Expressways: A Collaborative Perception Approach[J]. IEEE Transactions on Intelligent Transportation Systems (TITS), 2025.(中科院一区, TOP, CCF-B, IF: 8.4, 通讯作者)

10. Yao Jiamin, Mao Qichao*, Xie Yu, et al. Energy-Load Collaborative Optimization Method Based on Fuzzy-SM-GA in Consumer Electronics[J]. IEEE Transactions on Consumer Electronics (TCE), 2025.(中科院一区, IF: 10.9, 通讯作者)

11. Yao Jiamin, Xie Yu, Mao Qichao*, et al. Cost-Aware SFC Collaborative Scaling Based on Multi-Agent RL With Stackelberg Game[J]. IEEE Internet of Things Journal (IOTJ), vol. 12, no. 8, pp. 10253-10265, 2025. (中科院一区, TOP, IF: 8.9, 通讯作者)

12. Xiang Zebin, Cheng Jiujun, Mao Qichao*, et al. Privacy-preserving autonomous vehicle group formation in a collusive attack scenario[J]. IEEE Internet of Things Journal (IOTJ), vol. 12, no. 13, 2025. (中科院一区, TOP, IF: 8.9, 通讯作者)

13. Xu Ling, Mao Qichao*, et al. Collaborative Optimization Framework for UAV Clusters: Enhancing Energy Efficiency, Reliability, and Stability. [J] IEEE Internet of Things Journal (IOTJ), 2026. (中科院一区, TOP, IF: 8.9, 通讯作者)

14. Yang Lu, Cheng Jiujun, Mao Qichao*, et al. A Unified Software-Defined Autonomous Vehicle Network and Urban Congestion Prediction Method[J]. IEEE Transactions on Network Science and Engineering (TNSE), 2025.(中科院二区, IF: 7.9, 通讯作者)

二、专利

1. 程久军, 毛其超, 原桂远. 无人驾驶邻近车辆轨迹预测方法: CN202110331661.2 [P]. 2022-03-11.

2. 程久军, 毛其超. 基于边缘计算的无人驾驶车群形成方法及自协模型构建方法: CN202110274590.7 [P]. 2021-06-29.

3. 程久军, 毛其超. 一种基于风险评估效用的安全性无人驾驶车群构建方法: CN202110365927.5 [P]. 2022-08-09.

4. 程久军, 毛其超，原桂远. 无人驾驶车辆运动行为决策方法: CN202110550801.5 [P]. 2022-03-11.

5. 程久军, 毛其超. 高速公路场景中开放式无人驾驶车群动态演化探测方法: CN202110195974.X [P]. 2021-04-23.

6. 程久军, 魏超，毛其超. 封闭场景下无人驾驶车群自协模型构建方法: CN202110975463.X [P]. 2021-08-31.

7. 程久军, 原桂远, 毛其超. 高速公路场景开放式无人驾驶车群模型及车群形成方法: CN202011367229.0 [P]. 2022-03-22.

8. 程久军, 毛其超，吴禹路. 开放式场景下基于感知贡献的无人驾驶车群动态演化模型: CN202511400655.2 [P]. 2025.

9. 程久军, 毛其超，吴禹路. 基于感知贡献的开放式无人驾驶车群动态演化方法: CN202511083109.0 [P]. 2025.

10. 程久军, 毛其超. 基于感知贡献的开放式无人驾驶车群构建方法: CN202410701763.2 [P]. 2026-02-17.

11. 程久军, 侯梦男，毛其超. 基于轨迹预测的无人驾驶车群形成方法: CN202410062779.3 [P]. 2025.

12. 程久军, 原桂远，毛其超，杨露. 城市场景中无人驾驶网络性能影响因素预测模型: CN202211505688.X [P]. 2025.

三、项目

1. 国家自然科学基金面上项目，基于视觉解析的开放式无人驾驶车群内生性自协机理研究，2023-2026，在研。（参与）

2. 国家自然科学基金面上项目，面向开放式无人驾驶车群的正则性自协机理研究，2019-2022，已结题。（参与）