Multi-objective adaptive cruise control (ACC) algorithm for cooperative ACC platooning

ZHANG Jun-hui; LI Qing; CHEN Da-peng

doi:10.13374/j.issn2095-9389.2019.05.21.002

Volume 42 Issue 4

Apr. 2020

Turn off MathJax

Article Contents

Article Navigation > Chinese Journal of Engineering > 2020 > 42(4): 423-433

ZHANG Jun-hui, LI Qing, CHEN Da-peng. Multi-objective adaptive cruise control (ACC) algorithm for cooperative ACC platooning[J]. Chinese Journal of Engineering, 2020, 42(4): 423-433. doi: 10.13374/j.issn2095-9389.2019.05.21.002

Citation:

ZHANG Jun-hui, LI Qing, CHEN Da-peng. Multi-objective adaptive cruise control (ACC) algorithm for cooperative ACC platooning[J]. Chinese Journal of Engineering, 2020, 42(4): 423-433. doi: 10.13374/j.issn2095-9389.2019.05.21.002

Citation:

PDF( 3082 KB)

Multi-objective adaptive cruise control (ACC) algorithm for cooperative ACC platooning

doi: 10.13374/j.issn2095-9389.2019.05.21.002

ZHANG Jun-hui^{1, 2, 3},
LI Qing^{1, 2, 3},
CHEN Da-peng^{1, 2, 3
,
,}

1.
Institute of Microelectronics of Chinese Academy of Sciences, Beijing 100029, China
2.
Jiangsu R&D Center for Internet of Things, Wuxi 214135, China
3.
Wuxi Internet of Things Innovation Center Co., Ltd., Wuxi 214135, China

More Information

Corresponding author: E-mail: dpchen@ime.ac.cn
Received Date: 2019-05-21
Publish Date: 2020-04-01

Abstract

Abstract

With the rapid progress of the automated highway system, the issue of platoon stability, which might significantly affect highway traffic characteristics, such as traffic efficiency, traffic capacity, and traffic safety, has attracted considerable attention. A string of vehicles equipped with adaptive cruise control (ACC) and moving longitudinally in an automated manner is regarded as an autonomous vehicle platooning system. During car following, the quality of the ride could be poor and rear-end collisions could occur, particularly if the spacing and velocity errors are amplified to some extent as they propagate upstream. Research on platoon stability has been the focus of significant interest. However, a method to coordinate multiple sub-objectives dynamically during autonomous vehicle platooning against multiple traffic scenarios has not yet been developed. In this study, a multi-objective ACC algorithm for cooperative adaptive cruise control (CACC) platooning based on vehicle-to-vehicle (V2V) real-time communication technology, which enabled the interconnection of vehicles within a limited range to share vehicle position and motion state information, was thus proposed. The quantization of homogeneous and heterogeneous platoon stability was analyzed on the basis of the Lyapunov stability theory. Furthermore, on the basis of the model predictive control framework, the coordination among various conflicting sub-objectives, such as driver-desired car-following response, rear-end safety, platoon stability, and platoon overall quality, was comprehensively considered. Then, by utilizing a quadratic cost function with linear multi-constraints, the design of the multi-objective CACC was transformed into the convex quadratic programming problem with multiple constraints. The comparative simulations show that the I/O constraints and slack relaxation of platoon control are strict, indicating that platoon stability is easily affected by certain factors, such as time gap, platoon size, sub-objective weight coefficient, transient traffic scenarios, and heterogeneous features. Thus, rear-end safety and platoon stability should be prioritized to guarantee the overall quality of the platoon.
- automated highway system,
- platoon stability,
- cooperative adaptive cruise control,
- model predictive control

FullText(HTML)

References(17)

References

[1]	Xiao L Y, Gao F. Practical string stability of platoon of adaptive cruise control vehicles. IEEE Trans Intell Transp Syst, 2011, 12(4): 1184 doi: 10.1109/TITS.2011.2143407
[2]	Kayacan E. Multiobjective H∞ control for string stability of cooperative adaptive cruise control systems. IEEE Trans Intell Transp Syst, 2017, 2(1): 52
[3]	Filho C M, Terra M H, Wolf D F. Safe optimization of highway traffic with robust model predictive control-based cooperative adaptive cruise control. IEEE Trans Intell Transp Syst, 2017, 18(11): 3193 doi: 10.1109/TITS.2017.2679098
[4]	Fernandes P, Nunes U. Multiplatooning leaders positioning and cooperative behavior algorithms of communicant automated vehicles for high traffic capacity. IEEE Trans Intell Transp Syst, 2015, 16(3): 1172 doi: 10.1109/TITS.2014.2352858
[5]	Swaroop D, Rajagopal K R. A review of constant time headway policy for automatic vehicle following // 2001 IEEE Intelligent Transportation Systems Conference Proceedings. Oakland, 2001: 65
[6]	吳光強, 張亮修, 劉兆勇, 等. 汽車自適應巡航控制系統研究現狀與發展趨勢. 同濟大學學報: 自然科學版, 2017, 45(4):544 Wu G Q, Zhang L X, Liu Z Y, et al. Research status and development trend of vehicle adaptive cruise control systems. J Tongji Univ Nat Sci, 2017, 45(4): 544
[7]	章軍輝, 李慶, 陳大鵬. 仿駕駛員多目標決策自適應巡航魯棒控制. 控制理論與應用, 2018, 35(6):769 doi: 10.7641/CTA.2017.70585 Zhang J H, Li Q, Chen D P. Drivers imitated multi-objective adaptive cruise control algorithm. Control Theory Appl, 2018, 35(6): 769 doi: 10.7641/CTA.2017.70585
[8]	趙津, 大屋勝敬, 王婷, 等. 自適應巡航系統對高速公路交通安全及流量的影響. 中國機械工程, 2007, 18(12):1496 doi: 10.3321/j.issn:1004-132X.2007.12.026 Zhao J, Masahiro O, Wang T, et al. Impacts of the ACC system on highway traffic safety and capacity. China Mech Eng, 2007, 18(12): 1496 doi: 10.3321/j.issn:1004-132X.2007.12.026
[9]	Bifulco G N, Pariota L, Simonelli F, et al. Development and testing of a fully adaptive cruise control system. Transp Res Part C Emerg Technol, 2013, 29: 156 doi: 10.1016/j.trc.2011.07.001
[10]	Zhang J H, Li Q, Chen D P. Integrated adaptive cruise control with weight coefficient self-tuning strategy. Appl Sci, 2018, 8(6): 978 doi: 10.3390/app8060978
[11]	Milanes V, Shladover S E, Spring J, et al. Cooperative adaptive cruise control in real traffic situations. IEEE Trans Intell Transp Syst, 2014, 15(1): 296 doi: 10.1109/TITS.2013.2278494
[12]	章軍輝, 李慶, 陳大鵬. 車輛多模式多目標自適應巡航控制. 電子科技大學學報, 2018, 47(3):368 doi: 10.3969/j.issn.1001-0548.2018.03.008 Zhang J H, Li Q, Chen D P. Multi-objective adaptive cruise control with multi-mode strategy. J Univ Electron Sci Technol China, 2018, 47(3): 368 doi: 10.3969/j.issn.1001-0548.2018.03.008
[13]	Li S B, Li K Q, Rajamani R, et al. Model predictive multi-objective vehicular adaptive cruise control. IEEE Trans Control Syst Technol, 2011, 19(3): 556 doi: 10.1109/TCST.2010.2049203
[14]	Bageshwar V L, Garrard W L, Rajamani R. Model predictive control of transitional maneuvers for adaptive cruise control vehicles. IEEE Trans Veh Technol, 2004, 53(5): 1573 doi: 10.1109/TVT.2004.833625
[15]	Zhang J, Ioannou P A. Longitudinal control of heavy trucks in mixed traffic: Environmental and fuel economy considerations. IEEE Trans Intell Transp Syst, 2006, 7(1): 92 doi: 10.1109/TITS.2006.869597
[16]	Boer E, Nicholas W, Michael M, et al. Driver-model based assessment of behavioral adaptation. Trans Soc Autom Eng Japan, 2006, 37(4): 21
[17]	Zhang J H, Li Q, Chen D P. Vehicle-to-vehicle based multi-objective coordinated adaptive cruise control considering platoon stability. Adv Mech Eng, 2018, 10(10): 1