彭磊 男 博导 中国科学院深圳先进技术研究院
电子邮件: lei.peng@siat.ac.cn
通信地址: 深圳大学城学苑大道1068
邮政编码: 518055
研究领域
多模态融合感知;多模态时空数据融合处理;人工智能交通系统; 复杂智能系统
招生信息
硕士:2人/年
博士:1人/年
招生方向
招生专业
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学术型:
控制科学与工程(0811):081104-模式识别与智能系统
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专业型:
电子信息(0854):085404-计算机技术
:085410-人工智能
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教育背景
学历
学位
工学博士
工作经历
工作简历
社会兼职
2023-11-30-今,自动化学会综合智能交通专业委员会, 委员
2023-06-30-今,深圳市深圳通有限公司科技专家,
2023-01-16-今,招商局集团科技专家,
2021-04-30-今,深圳智慧城市科技发展集团特聘顾问,
2019-12-31-今,广东省科技专家,
2012-12-31-今,深圳市科技专家,
专利与奖励
专利成果
出版信息
论文
2024:
M.A Ghaffar,Peng L*,M.U Aslam,Mu. Adeel, Sa. Dassari, I.M Mvitu, R.B Mvitu, (2024). Research on Vehicle-UAV Integrated Routing Optimization Problem to Deliver Medical Supplies. Electronics.
Zhang,K.,Cui,Y.,Liu,Q.,Shu,H.,Peng,L*. (2024). Spread of Parking Difficulty in Urban Environments: A Parking Network Perspective. IET Intelligent Transport Systems.
Shao Y., Chen Z, Zhen Y., Peng L *(2024), LSM TR-tree: An Efficient Spatial-Temporal Index for Real-Time IoV Data Storage. In 2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC)
Sun C., Yang X., Zhen Y., Bai Y., Peng L* (2024), Research on Multimodal Fusion Indoor Positioning under High-throughput Passenger Flow : A Case Study of Metro Station. In 2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC)
Yin J., Jiang Z, Liang Q. , Peng L, Zhu F., Liu J, Li H (2024), Heterogeneous Information Fusion-based Distributional Reinforcement Learning for Autonomous Driving. In 2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC)
Liu Z., Chen Z., Yang X, Peng L* (2024). Consistency Check for Multimodal Transportation Data: A Case Study of Vision and LiDARA. In 2024 9th International Conference on Information Management and Technology (ICIMTech 2024)
Liang, Q., Jiang, Z., Yin, J., Peng, L., Liu, J., & Li, H. (2024, June). Efficient Collaborative Multi-Agent Driving via Cross-Attention and Concise Communication. In 2024 IEEE Intelligent Vehicles Symposium (IV)
2023:
Ku, Y., Guo, C., Zhang, K., Cui, Y., Shu, H., Yang, Y., & Peng, L. (2023). Toward Directed Spatiotemporal Graph: A New Idea for Heterogeneous Traffic Prediction. IEEE Intelligent Transportation Systems Magazine.
Cui, Y., Shi, W., Yang, H., Shao, C., Peng, L., & Li, H. (2023). Probabilistic Model-Based Reinforcement Learning Unmanned Surface Vehicles Using Local Update Sparse Spectrum Approximation. IEEE Transactions on Industrial Informatics.
Wang, J., Xia, L., Peng, L., Li, H., & Cui, Y. (2023). Efficient Uncertainty Propagation in Model-Based Reinforcement Learning Unmanned Surface Vehicle Using Unscented Kalman Filter. Drones, 7(4), 228.
Cui, Y., Xu, K., Zheng, C., Liu, J., Peng, L., & Li, H. (2023). Flexible unmanned surface vehicles control using probabilistic model-based reinforcement learning with hierarchical Gaussian distribution. Ocean Engineering, 285, 115467.
Wang, Y., Ku, Y., Liu, Q., Yang Y. & Peng, L (2023). Large-scale Parking Data Prediction: From A Graph Coarsening Perspective, In 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)
Ku, Y., Wang, Y., Liu, Q., Yang Y. & Peng, L (2023). TEDGCN: Asymmetric Spatiotemporal GNN for Heterogeneous Traffic Prediction, In 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)
Sun, Y., Zhang, K.S., Liu, Q., Yang, Y.& Peng, L. (2023). Efficient Large-Scale Parking Data Prediction based on Parking Zone Division, In 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)
2022:
Cui, Y., Peng, L., & Li, H. (2022). Filtered probabilistic model predictive control-based reinforcement learning for unmanned surface vehicles. IEEE Transactions on Industrial Informatics, 18(10), 6950-6961.
Zheng, C., Li, W., Li, W., Xu, K., Peng, L., & Cha, S. W. (2022). A deep reinforcement learning-based energy management strategy for fuel cell hybrid buses. International Journal of Precision Engineering and Manufacturing-Green Technology, 9(3), 885-897.
Luo, Q., Zhou, Y., Hou, W., & Peng, L. (2022). A hierarchical blockchain architecture based V2G market trading system. Applied Energy, 307, 118167.
Liu, Q., Shu, H., Peng, L., Lv, L., Zhang, O., & Yuan, G. (2022, October). Research and Practice on the Construction of Connected Vehicle in the Greater Bay Area under the Smart City. In 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC) (pp. 1882-1885). IEEE.
Wang, J., Xu, K., Shao, C., Peng, L., & Cui, Y. (2022, October). Data-Driven Probabilistic Model of Magneto-Rheological Damper for Intelligent Vehicles using Gaussian Processes. In 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC) (pp. 1094-1099). IEEE.
Zhao, Z., Yang, B., Shu, H., Liu, Q., Zhang, K., & Peng, L. (2022, October). Sensing Intrusion Detection for Automatic Driving System based on Scene Semantic Centroid. In 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC) (pp. 1075-1081). IEEE.
Zhou, R., He, H., Shu, H., Liu, Q., Zhang, K., & Peng, L. (2022, October). Exploration of Adaptive Energy Optimization for 5G Roadside Unit. In 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC) (pp. 761-766). IEEE.
2021:
Yu, J., Zhang, K., & Peng, L. (2021, October). Integrated Prediction of Regional Traffic Situation Based on Multi-Task Spatial-Temporal Network. In IECON 2021–47th Annual Conference of the IEEE Industrial Electronics Society (pp. 1-6). IEEE.
2020:
Sun, T., Jia, C., Liang, J., Li, K., Peng, L., Wang, Z., & Huang, H. (2020). Improved modulated model‐predictive control for PMSM drives with reduced computational burden. IET Power Electronics, 13(14), 3163-3170.
Zou, W., Sun, Y., Zhou, Y., Lu, Q., Nie, Y., Sun, T., & Peng, L. (2020). Limited sensing and deep data mining: A new exploration of developing city-wide parking guidance systems. IEEE Intelligent Transportation Systems Magazine, 14(1), 198-215.
Sun, T., Wang, J., Jia, C., & Peng, L. (2020). Integration of FOC with DFVC for interior permanent magnet synchronous machine drives. IEEE Access, 8, 97935-97945.
Zhang, J., Zhu, M., & Peng, L. (2020, September). Customized Parking Data Generation based on Multi-conditional GAN. In 2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)(pp. 1-6). IEEE.
2019:
Chen, H., Chen, G., Lu, Q., & Peng, L. (2019, October). MMSE-based optimized transfer strategy for transfer prediction of parking data. In 2019 IEEE Intelligent Transportation Systems Conference (ITSC) (pp. 407-412). IEEE.
Lu, Q., Tang, Z., Nie, Y., & Peng, L. (2019, October). ParkingRank-D: A Spatial-temporal Ranking Model of Urban Parking Lots in City-wide Parking Guidance System. In 2019 IEEE Intelligent Transportation Systems Conference (ITSC)(pp. 388-393). IEEE.
2018:
Peng, L., & Li, H. (2016, November). Searching parking spaces in urban environments based on non-stationary Poisson process analysis. In 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC)(pp. 1951-1956). IEEE.
Dong, S., Chen, M., Peng, L., & Li, H. (2018, February). Parking rank: A novel method of parking lots sorting and recommendation based on public information. In 2018 IEEE International Conference on Industrial Technology (ICIT)(pp. 1381-1386). IEEE.
Sun, Y., Peng, L., Li, H., & Sun, M. (2018, November). Exploration on spatiotemporal data repairing of parking lots based on recurrent GANs. In 2018 21st International Conference on Intelligent Transportation Systems (ITSC)(pp. 467-472). IEEE.
Fang, X., Xiang, R., Peng, L., Li, H., & Sun, Y. (2018, October). SAW: a hybrid prediction model for parking occupancy under the environment of lacking real-time data. In IECON 2018-44th Annual Conference of the IEEE Industrial Electronics Society (pp. 3134-3137). IEEE.
Sun, M., Li, Z., Peng, L., Li, H., & Fang, X. (2018, November). FLOPS: an efficient and high-precision prediction on available parking spaces in a long time-span. In 2018 21st International Conference on Intelligent Transportation Systems (ITSC) (pp. 2937-2942). IEEE.
更详细的论文信息请浏览:https://orcid.org/0000-0002-0124-140X
科研活动
近五年科研项目
面向复杂公共交通场景的数字人民币支付关键技术研究与应用示范, 深圳市科技重大专项, 2024-04--2026-03
面向智能网联运营管理的车路云一体化数据底座关键技术与应用示范, 深圳市科技重大专项, 2024-04--2027-03
面向6G的无线通信系统 仿真试验平台, 广东省科技重大专项, 2024-04--2027-03
5G城域物联专网总体技术框架研究与计算机辅助建设, 国家重点研发计划, 2020-10--2023-10
城市级交通流数据生成及应用关键技术研究, 深圳市基础研究重点项目, 2019-04--2022-03
知识与数据协同驱动的集装箱码头关键设备故障预测关键技术研究, 工业委托开发, 2023-04--2023-12
车联网智慧出行创新企业联合实验室, 工业委托开发 , 2019-01--2022-02
基于车联网技术的城市级智慧停车应用示范, 广东省科技重大专项, 2016-01--2020-06
室外大范围复杂动态场景安保机器人长期导航与场景理解, 国自然联合重点基金, 2020-01--2023-12
具有电堆寿命增强作用的氢燃料电池汽车电堆管理与整车能量管理关键技术研究, 深圳市基础研究重点项目, 2021-08--2024-08
合作情况
依托新一代信息基础设施,面向智慧城市、智能交通、智慧港口等重要应用场景,聚焦多模态实时时空大数据融合关键技术,积极与行业龙头企业,学界头部团队开展产学研合作,承担国家、省、市多个层面的科技重大项目。
项目合作单位
香港科技大学(广州)
深圳智慧城市科技发展集团有限公司
深圳市深圳通有限公司
深圳市城市交通规划设计研究中心股份有限公司
深圳市地铁集团有限公司
深圳巴士集团股份有限公司
招商局港口集团股份有限公司
鹏城实验室
南方科技大学
深圳航盛电子股份有限公司
指导学生
1)已指导的学生参与了具有技术探索和应用价值的各类型科研项目,包括国家重点研发计划、国家自然科学基金、广东省科技重大专项、深圳市科技重大专项、深圳市自然科学基金以及工业委托项目等,学习掌握行业最新的前沿技术。
2)已指导的学生在项目实践中收获了自己的研究成果,以第一作者身份在智能交通领域的主流SCI期刊 IEEE TITS, IEEE MITS, IET ITS, 智能交通领域的国际顶会IEEE ITSC, IEEE IV发表了多篇论文。
3)已指导的学生能够获得来自业界著名企业的工作机会,包括华为、腾讯、阿里、比亚迪、招商银行、工商银行等,以及诸多深圳市属国企,包括深智城、深城交等。
4) 已指导的学生获得了中国科学院大学三好学生,先进院院长奖学金、集成所优秀研究生等荣誉。