彭剑坤 - 东南大学

个人简介

东南大学教授，博士生/硕士生导师，交通学院院长院务助理。2022~2025年连续四年入选斯坦福全球前 2%顶尖科学家，并入选Scholar GPS全球前0.05% 终身顶尖学者。近年来主持国家自然科学基金面上项目2项、青年项目(C类)1项、国家重点研发计划专题1项及省部级课题4项、主持6项产学研合作项目。获省部级和一级学会科技奖励7项，其中教育部科技进步一等奖1项(序2/13)、中国汽车工业技术发明一等奖1项(序4/6)；获中国优秀专利奖1项(序2/4)。以第一/通讯作者身份发表SCI期刊论文50余篇，ESI高被引论文5篇，千分之一热点论文1篇，权威顶刊封面文章1篇，Google学术累计被引近6000余次，授权国家发明专利40余件、计算机软件著作权8项。教育背景 2016 年 6 月毕业于北京理工大学机械与车辆学院机械工程专业，获工学博士学位，师从何洪文教授。工作经历 2025.01-至今东南大学，交通学院，教授，博导/硕导 2019.12-2024.12 东南大学，交通学院，副教授，博导 / 硕导 2016.07-2019.11 北京理工大学，电动车辆国家工程研究中心，博士后

研究领域

端到端自动驾驶、全向线控底盘智能控制、低空电驱动运载器控制、全类型新能源汽车学习型控制。

近期论文

查看导师新发文章（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）

一、自动驾驶感知决策控制 [1] Yu S, Peng J * , Ge Y, et al. A traffic state prediction method based on spatial–temporal data mining of floating car data by using autoformer architecture[J]. Computer‐Aided Civil and Infrastructure Engineering, 2024, 39(18): 2774-2787. (SCI, Q1 , 封面文章 ) [ 2 ] Peng J , Yu S, Ge Y, et al. Personalized Decision-Making Framework for Collaborative Lane Change and Speed Control Based on Deep Reinforcement Learning[J]. IEEE Transactions on Intelligent Transportation Systems, 2 025, 26(9): 13629-13644. ( SCI, Q1) [ 3 ] Peng J , Zhang S, Zhou Y, et al. An integrated model for autonomous speed and lane change decision-making based on deep reinforcement learning[J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(11): 21848-21860. (SCI, Q1) [ 4 ] Peng J , Liu X, Wu C, et al. Deep reinforcement learning-tuning hierarchical vehicle trajectory tracking framework based on improved kinematic model predictive control[J]. Engineering Applications of Artificial Intelligence, 2025, 162: 112551. (SCI, Q1) [ 5 ] Peng J , Shi Y, He H, et al. Multi-level Attention Driven Decision-Making Framework for Unsignalized Intersections Based on Dual-Buffer Soft Actor-Critic [J]. IEEE Internet of Things Journal, 2025. (SCI, Q1) [6] Guo X, Peng J* , Pi D, et al. Enhanced consensus control architecture for autonomous platoon utilizing multi‐agent reinforcement learning[J]. Computer‐Aided Civil and Infrastructure Engineering, 2025. (SCI, Q1) [ 7 ] Wu D, Peng J * , Yu S, et a l. UKD-TEAD: An Unsupervised Knowledge Distillation Framework for Detecting Anomalies in Traffic Equipment With Various Aspect Ratios[J]. IEEE Internet of Things Journal, 2025. (SCI, Q1) [ 8 ] Yang J , Peng J * , Zhang Q, et al. Monocular vision approach for Soft Actor-Critic based car-following strategy in adaptive cruise control [J]. Experts Systems with Applications, 2025. (SCI, Q1) [ 9 ] Han Y , Li Y, Yu S, Peng J * , et al. Modeling lane changes using parallel learning [J]. Transportation Research Part C: Emerging Technologies, 2024, 167: 104841. (SCI, Q1) 二、新能源汽车节能优化控制 [1] Peng J , He H, Xiong R. Rule based energy management strategy for a series–parallel plug-in hybrid electric bus optimized by dynamic programming[J]. Applied Energy, 2017, 185: 1633-1643. (SCI, Q1, 1% 高被引和 1‰ 热点论文 ) [2] Wu J, He H, Peng J * , et al. Continuous reinforcement learning of energy management with deep Q network for a power split hybrid electric bus[J]. Applied energy, 2018, 222: 799-811. (SCI, Q1, 1% 高被引论文 ) [3] Wu Y, Tan H, Peng J * , et al. Deep reinforcement learning of energy management with continuous control strategy and traffic information for a series-parallel plug-in hybrid electric bus[J]. Applied Energy, 2019, 247: 454-466. (SCI, Q1, 1% 高被引论文 ) [ 4 ] Peng J , Zhou J, Chen J, et al. Multiple electric components health-aware eco-driving strategy for fuel cell hybrid electric vehicle based on soft actor-critic algorithm[J]. IEEE Transactions on Transportation Electrification, 2023, 10(3): 6242-6257. (SCI, Q1) [ 5 ] Peng J , Chen W, Fan Y, et al. Ecological Driving Framework of Hybrid Electric Vehicle Based on Heterogeneous Multi-Agent Deep Reinforcement Learning[J]. IEEE Transactions on Transportation Electrification, 2023, 10(1): 392-406. (SCI, Q1) [ 6 ] Peng J , Fan Y, Yin G, et al. Collaborative optimization of energy management strategy and adaptive cruise control based on deep reinforcement learning[J]. IEEE Transactions on Transportation Electrification, 2022, 9(1): 34-4 4. (SCI, Q1) [7] Peng J , Zhang H, Ma C, et al. Powertrain Parameters’ Optimization for a Series–Parallel Plug-In Hybrid Electric Bus by Using a Combinatorial Optimization Algorithm[J]. IEEE Journal of Emerging and Selected Topics in Power Electronics, 2021, 11(1): 32-43. (SCI, Q1) [ 8 ] Wu C, Peng J * , Zhou J, et al. Thermal Management Methodology Based on a hybrid Deep Deterministic Policy Gradient with Memory Function for Battery Electric Vehicles in Hot Weather Conditions[J]. IEEE Transactions on Transportation Electrification, 2025. (SCI, Q1) [9 ] Wu J, Peng J * , Li M, et al. Enhancing fuel cell electric vehicle efficiency with TIP-EMS: A trainable integrated predictive energy management approach[J]. Energy Conversion and Management, 2024, 310: 118499. (SCI, Q1) [1 0 ] Peng J , Luo J, He H, et al. An improved state of charge estimation method based on cubature Kalman filter for lithium-ion batteries[J]. Applied Energy, 2019, 253: 113520. (SCI, Q1)

学术兼职

担任国际期刊《 Sustainable Horizons 》特刊主编、中国车辆控制与智能化大会( CVCI 2022) 组织委员会副主席，国际应用能源会议( ICAE 2016)“ 电动车辆 ” 分会主席，汽车前沿技术青年学者论坛( Auto E 2017)“ 车辆动力学 ” 分会主席。是国家新能源汽车技术创新中心特聘专家、中国汽车研发软件产业创新联盟技术专家委员会委员、中国公路学会自动驾驶工作委员会委员、智能汽车与智慧城市协同发展联盟委员，是国家自然科学基金通讯评审专家以及江苏省、山西省、山东省等多省科技咨询专家。在境外国际会议宣读论文及海报展示 10 余次，担任 10 余个汽车、能源及交通领域知名 SCI 期刊审稿人，近年来审稿 100 余篇。