徐少兵 - 清华大学 - 车辆与运载学院

个人简介

教育背景 2011/08-2016/07 清华大学，汽车系工学博士 2014/10-2015/04 密歇根大学安娜堡分校，机械工程系联合培养 2007/08-2011/07 中国农业大学，车辆工程系工学学士工作履历 2022-至今清华大学，车辆与运载学院助理教授 2019/01-2022/02 密歇根大学安娜堡分校，机械工程系助理研究员 2016/10-2018/12 密歇根大学安娜堡分校，机械工程系博士后荣誉与奖励 2021 国家自然科学基金委优秀青年项目 2018 最佳论文奖，第14届先进汽车控制国际会议（AVEC）(1/2) 2016 优秀博士论文奖，清华大学 2016 北京市优秀博士毕业生 2011 第4届全国大学生机械创新设计大赛一等奖(1/5) 2008 第19届北京市高等数学竞赛一等奖 2014, 2010, 2009 国家奖学金

研究领域

智能车辆自主与协同智能、决策规划与运动控制、增强现实聚焦智能系统的学习、控制和设计，开发智能、可扩展、可部署的算法与工具。主要以智能汽车和特种车辆为应用对象，希望解决智能系统开发和应用中面临的共性难题。

近期论文

查看导师最新文章（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）

S. Xu*, R. Zidek, Z. Cao, P. Lu, X. Wang, B. Li, and H. Peng, “System and Experiments of Motion Planning and Control for Autonomous Vehicles,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, pp. 1-15, 2021. (IF: 13.45) S. Xu, H. Peng, and Y. Tang, “Preview Path Tracking Control with Delay Compensation for Autonomous Vehicles,” IEEE Transactions on Intelligent Transportation Systems, vol. 22, no. 5, pp. 2979-2989, 2021. (IF: 6.49) S. Xu, H. Peng, Z. Song, K. Chen, and Y. Tang, “Design and Test of Speed Tracking Control for the Self-Driving Lincoln MKZ Platform,” IEEE Transactions on Intelligent Vehicles, vol. 5, no. 2, pp. 324-334, 2019. (IF: 6.72) S. Xu and H. Peng, “Design, Analysis, and Experiments of Preview Path Tracking Control for Autonomous Vehicles,” IEEE Transactions on Intelligent Transportation Systems, vol. 21, no. 1, pp. 48-58, 2019. (IF: 6.49, ESI Highly Cited Paper) S. Xu, S. Li, B. Cheng, and K. Li, “Instantaneous Feedback Control for a Fuel-Prioritized Vehicle Cruising System on Highways with a Varying Slope,” IEEE Transactions on Intelligent Transportation Systems, vol. 18, no. 5, pp.1210-1220, 2017. (IF: 6.49) S. Xu, S. Li, H Peng, and B. Cheng, “Fuel-Saving Cruising Strategies for Parallel HEV,” IEEE Transactions on Vehicular Technology, vol. 65, no. 6, pp. 4676-4686, 2016. (IF: 5.978) S. Xu, S. Li, X. Zhang, B. Cheng, and H. Peng, “Fuel-Optimal Cruising Strategy for Road Vehicles with Step-gear Mechanical Transmission,” IEEE Transactions on Intelligent Transportation Systems, vol. 16, no. 6, pp. 3496-3507, 2015. (IF: 6.49) S. Xu, S. Li, K. Deng, S. Li, and B. Cheng, “A Unified Pseudospectral Computational Framework for Optimal Control of Road Vehicles,” IEEE/ASME Transactions on Mechatronics, vol. 20, no. 4, pp. 1499-1510, 2015. (IF: 5.303) S. Li, Q. Guo, S. Xu*, J. Duan, S. Li, C. Li, and K. Su, “Performance Enhanced Predictive Control for Adaptive Cruise Control System Considering Road Elevation Information,” IEEE Transactions on Intelligent Vehicles, vol. 2, no. 3, pp.150-160, 2017. S. Li#, S. Xu#, X. Huang, B. Cheng, and H. Peng, “Eco-Departure of Connected Vehicles with V2X Communication at Signalized Intersections,” IEEE Transactions on Vehicular Technology, vol. 64, no. 12, pp. 5439-5449, 2015. (# co-first author, IF: 5.978) P. Lu, S. Xu, and H. Peng, “Graph-Embedded Lane Detection,” IEEE Transactions on Image Processing, vol. 30, pp. 2977-2988, 2021. (IF: 10.86) Z. Cao, S. Xu, H. Peng, D. Yang, and R. Zidek, “Confidence-Aware Reinforcement Learning for Self-driving Cars,” IEEE Transactions on Intelligent Transportation Systems, pp. 1-11, 2020. (IF: 6.49) S. Xu and H. Peng, “Safeguard Protected Preview Lane Keeping Control for Automated Vehicles,” 14th International Symposium on Advanced Vehicle Control, AVEC'18, July 16-20, 2018, pp. 1-7. (Best Paper Award) S. Xu, H. Peng, Z. Song, K. Chen, and Y. Tang, “Accurate and Smooth Speed Control for an Autonomous Vehicle,” IEEE Intelligent Vehicles Symposium (IV'18), Suzhou, China, 2018, pp. 1976-1982. S. Xu, K. Deng, S. Li, S. Li, and B. Cheng, “Legendre Pseudo-spectral Computation of Optimal Speed Profiles for Vehicle Eco-Driving System,” Dearborn, Michigan, USA, June 8-11, 2014, pp. 1103-1108.

学术兼职

2022，专刊编辑，Recent Advances in Automated Driving Technologies, IEEE Vehicular Technology Magazine (IF=7.9) 2022，编委(Associate Editor)，2022 Modeling, Estimation and Control Conference (Jersey City, US) 2022，编委，Highlights of Vehicles 2021，专刊编辑，Recent Advances in Motion Control, Estimation and Diagnosis for Automated Vehicles, IEEE Vehicular Technology Magazine (IF=7.9)