近年来主要研究领域包括：无人驾驶车群、车路云协同、多车协同感知、空地一体关键技术等，共发表学术论文30余篇。部分著作、论文与专利列表如下：

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（*表示通讯作者）：

[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, IF: 9.2,)

[2]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)

[3]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).

[4]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 RecognitionFindings(CVPRFindings), 2026(CCF-A类会议Findings).

[5]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)

[6]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)

[7]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)

[8]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).

[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)

[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)

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

[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)

[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)

[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)

已授权专利：

[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.