Optimal control methods in intelligent vehicles

被引：0
|
作者：
Chen H. [1 ,2 ]
Guo L. [1 ,2 ]
Qu T. [1 ]
Gao B. [1 ]
Wang F. [1 ]
机构：
[1] State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun
[2] Department of Control Science and Engineering, Jilin University, Changchun
来源：
Chen, Hong (chenh@jlu.edu.cn) | 1600年 / Taylor and Francis Ltd.卷 / 04期
基金：
中国国家自然科学基金;
关键词：
Control technology; eco-driving; intelligent vehicles; MPC-based driver modelling;
D O I：
10.1080/23307706.2016.1254072
中图分类号：
学科分类号：
摘要：
In recent years, intelligent vehicles (IVs) have become a hot spot in automotive industry. Key technologies of IVs range over the field of sensing, decision-making and control. Among them, control technology provides an enabling support for improving autonomous driving safety, reducing energy consumption and carbon emission. This paper focuses on some aspects of applying advanced control methodologies in IVs through several selected examples including eco-driving and MPC-based driver modelling. © 2016, © 2016 Northeastern University, China.
引用
收藏
页码：32 / 56
页数：24
相关论文
共 50 条
  • [1] Optimal Control of Overtaking Maneuver for Intelligent Vehicles
    Nemeth, Balazs
    Gaspar, Peter
    Hegedus, Tamas
    JOURNAL OF ADVANCED TRANSPORTATION, 2018,
  • [2] Optimal Predictive Control for Intelligent Usage of Hybrid Vehicles
    Sansa, Mariano
    Azami, Hamza Idrissi Hassani
    ADVANCED MICROSYSTEMS FOR AUTOMOTIVE APPLICATIONS 2016: SMART SYSTEMS FOR THE AUTOMOBILE OF THE FUTURE, 2016, : 183 - 200
  • [3] Intelligent Constrained Optimal Control of Aerospace Vehicles with Model Uncertainties
    Ding, Jie
    Balakrishnan, S. N.
    JOURNAL OF GUIDANCE CONTROL AND DYNAMICS, 2012, 35 (05) : 1582 - 1592
  • [4] Development of an intelligent cruise control using optimal control methods
    Dellnitz, Michael
    Eckstein, Julian
    Flasskamp, Kathrin
    Friedel, Patrick
    Horenkamp, Christian
    Koehler, Ulrich
    Ober-Bloebaum, Sina
    Peitz, Sebastian
    Tiemeyer, Sebastian
    2ND INTERNATIONAL CONFERENCE ON SYSTEM-INTEGRATED INTELLIGENCE: CHALLENGES FOR PRODUCT AND PRODUCTION ENGINEERING, 2014, 15 : 285 - 294
  • [5] Intelligent Charging Control of Power Aggregator for Electric Vehicles Using Optimal Control
    Alkawaz, Ali Najem
    Kanesan, Jeevan
    Mohd Khairuddin, Anis Salwa
    Chow, Chee Onn
    Singh, Mandeep
    ADVANCES IN ELECTRICAL AND COMPUTER ENGINEERING, 2021, 21 (04) : 21 - 30
  • [6] Lane-change Control for Intelligent Vehicles Based on Optimal Preview
    Qiu S.
    Qian L.
    Lu J.
    Zhongguo Jixie Gongcheng/China Mechanical Engineering, 2019, 30 (23): : 2778 - 2783
  • [7] Methods for the Solution of Hybrid Optimal Control Problems and their Application to the Optimal Operation of Hybrid Vehicles
    Schori, Markus
    Boehme, Thomas J.
    Becker, Uwe
    Schultalbers, Matthias
    AT-AUTOMATISIERUNGSTECHNIK, 2013, 61 (12) : 831 - 839
  • [8] Review on Machine Learning Methods for Motion Planning and Control Policy of Intelligent Vehicles
    Gong J.
    Gong C.
    Lin Y.
    Li Z.
    Chao L.
    Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology, 2022, 42 (07): : 665 - 674
  • [9] Optimal Resonant Beam Charging for Electronic Vehicles in Internet of Intelligent Vehicles
    Zhang, Qingqing
    Liu, Mingqing
    Lin, Xing
    Liu, Qingwen
    Wu, Jun
    Xia, Pengfei
    IEEE INTERNET OF THINGS JOURNAL, 2019, 6 (01): : 6 - 14
  • [10] Intelligent control strategies of hybrid vehicles
    Brunner, H
    Winger, A
    INNOVATIVE POWER TRAIN SYSTEMS, 1998, 1418 : 155 - 177
12345