智能电动汽车的感知、决策与控制关键基础问题及对策研究

李克强

doi:10.3981/j.issn.1000-7857.2017.14.011

PDF(895 KB)

科技导报 ›› 2017, Vol. 35 ›› Issue (14) : 85-88. DOI: 10.3981/j.issn.1000-7857.2017.14.011

研究论文

智能电动汽车的感知、决策与控制关键基础问题及对策研究

李克强

作者信息 -

清华大学汽车安全与节能国家重点实验室, 北京 100084

作者简介:

李克强,教授,研究方向为汽车智能化和电动化技术,电子信箱:likq@tsinghua.edu.cn

Key topics and measures for perception, decision-making and control of intelligent electric vehicles

LI Keqiang

Author information -

State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China

摘要

电动化与智能化的融合是新一代汽车技术发展的前沿，因其所具有的环保、安全特性而在国际上引起极大关注。本文梳理总结了智能电动汽车的感知、决策与控制等方面的发展趋势和现有问题，指出智能电动汽车属于多学科交叉领域，集成难度高；其动力来源与传统汽车不同，这也带来了电池安全性、能量回收、动力学模型等基础问题。最后给出适合中国国情且清晰可行的研究对策，指出了该研究可带来的预期经济与社会效益。

Abstract

Intelligent electric vehicles have attracted a great attention in the international community. This paper reviews its trends and existing problems, focusing on the perception, the decision-making and the control. Feasible researches best suited for our country are pinpointed, together with the expected economic and social benefits.

导出引用

李克强. 智能电动汽车的感知、决策与控制关键基础问题及对策研究[J]. 科技导报, 2017, 35(14): 85-88 https://doi.org/10.3981/j.issn.1000-7857.2017.14.011

LI Keqiang. Key topics and measures for perception, decision-making and control of intelligent electric vehicles[J]. Science & Technology Review, 2017, 35(14): 85-88 https://doi.org/10.3981/j.issn.1000-7857.2017.14.011

参考文献

[1] Li K, Chen T, Luo Y, et al. Intelligent environment-friendly vehicles:Concept and case studies[J]. IEEE Transactions on Intelligent Transpor tation Systems, 2012, 13(1):318-328.
[2] Tawari A, Martin S, Trivedi M. Continuous head movement estimator for driver assistance:Issues, algorithms, and on-road evaluations[J]. IEEE Transactions on Intelligent Transportation Systems, 2014, 15(2):818-830.
[3] Kanghyun N, Hiroshi F, Yoichi H. Estimation of sideslip and roll an gles of electric vehicles using lateral tire force sensors through RLS and Kalman filter approaches[J]. IEEE Transactions on Industrial Elec tronics, 2013, 60(3):988-1000.
[4] Held D, Levinson J, Thrun S, et al. Robust real-time tracking combin ing 3D shape, color, and motion[J]. The International Journal of Robot ics Research, 2016, 35(1/3):30-49.
[5] Natour G, Ait-Aider O, Rouveure R, et al. Toward 3D reconstruction of outdoor scenes using an MMW radar and a monocular vision sensor[J]. Sensors, 2015, 15(10):25937-25967.
[6] Bayram S, Papapanagiotou I. A survey on communication technologies and requirements for internet of electric vehicles[J]. EURASIP Journal on Wireless Communications and Networking, 2014(1):1-18.
[7] Kitayama H, Munetoh S, Ohnishi K, et al. Advanced security and priva cy in connected vehicles[J]. IBM Journal of Research and Develop ment, 2014, 58(1):1-7.
[8] Zeadally S, Hunt R, Chen Y, et al. Vehicular ad hoc networks (VANETS):Status, results, and challenges[J]. Telecommunication Sys tems, 2012, 50(4):217-241.
[9] Okuda H, Ikami N, Suzuki T, et al. Modeling and analysis of driving be havior based on a probability weighted ARX model[J]. IEEE Transac tions on Intelligent Transportation Systems, 2013, 14(1):98-112.
[10] Teichman A, Lussier J T, Thrun S. Learning to segment and track in RGBD[J]. IEEE Transactions on Automation Science and Engineering, 2013, 10(4):841-852.
[11] Hoult W, Cole D. A neuromuscular model featuring co-activation for use in driver simulation[J]. Vehicle System Dynamics, 2008, 46(1):175-189.
[12] Beal C, Gerdes J. Model predictive control for vehicle stabilization at the limits of handling[J]. IEEE Transactions on Control Systems Tech nology, 2013, 21(4):1258-1269.
[13] Anderson S. Constraint-based navigation for safe, shared control of ground vehicles[D]. Cambridge, USA:Massachusetts Institute of Tech nology, 2013.
[14] Nam K, Fujimoto H, Hori Y. Lateral stability control of In-Wheel-Mo tor-Driven electric vehicles based on sideslip angle estimation using lateral tire force sensors[J]. IEEE Transaction on Vehicular Technolo gy, 2012, 61(5):1972-1985.
[15] Cairano S, Tseng H, et al. Vehicle yaw stability control by coordinated active front steering and differential braking in the tire sideslip angles domain[J]. IEEE Transactions on Control Systems Technology, 2013, 21(4):1236-1248.
[16] Wang R, Wang J. Fault-tolerant control for electric ground vehicles with independently-actuated in-wheel motors[J]. Journal of Dynamic Systems Measurement and Control, 2012, 134(2):194-203.
[17] 郭景华, 罗禹贡, 李克强. 智能电动车辆纵横向协调与重构控制[J]. 控制理论与应用, 2014, 31(9):1238-1244. Guo Jinghua, Luo Yugong, Li Keqiang. Cooperative and reconfigu rable lateral and longitudinal control of intelligent electric vehicles[J]. Control Theory and Applications, 2014, 31(9):1238-1244.
[18] Gu Q, Cheng X. Study on optimal slip ration identification and trac tion control for electric vehicle[C]//International Conference on Mecha tronic Science, Electric Engineering and Computer, Jilin, China:IEEE, 2011:738-742.
[19] Hedrick J, Tomizuka M, Varaiya P. Control issues in automated high way systems[J]. IEEE Control Systems, 1994, 14(6):21-32.
[20] Desjardins C, Chaibdraa B. Cooperative adaptive cruise control:A re inforcement learning approach[J]. IEEE Transactions on Intelligent Transportation Systems, 2011, 12(4):1248-1260.
[21] Taefi T, Kreutzfeldt J, Held T, et al. Strategies to increase the profit ability of electric vehicles in urban freight transport[M]. Berlin, Germa ny:Springer, 2015, 367-388.
[22] Dunbar W, Caveney D. Distributed receding horizon control of vehicle platoons:Stability and string stability[J]. IEEE Transactions on Auto matic Control, 2012, 57(3):620-633.