Please wait a minute...
J4  2011, Vol. 45 Issue (12): 2073-2078    DOI: 10.3785/j.issn.1008-973X.2011.12.001
自动化技术     
考虑驾驶员行驶特性的双模式自适应
巡航控制设计
罗莉华, 龚李龙, 李平, 王慧
浙江大学 工业控制技术国家重点实验室 浙江 杭州 310027
Two-mode adaptive cruise control design with
humans’ driving habits consideration
LUO Li-hua, GONG Li-long, LI Ping, WANG Hui
1. The State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou 310027, China
 全文: PDF  HTML
摘要:

为了设计一个能够模拟驾驶员行驶行为的汽车自适应巡航控制(ACC)系统,通过分析驾驶员的日常行驶特性,在模型预测控制的框架基础上提出一个双模式的自适应巡航控制策略:当远离前车时,ACC系统采取快速接近模式,在满足安全舒适的前提下以尽量短的时间减小两车间距;一旦车间距调整至期望值附近时,ACC系统切换到平稳跟车模式,使车辆安全、平稳、舒适地对前车进行跟车;为使2种模式切换时能平滑过渡,利用模糊理论设计了2个模式的切换规则来模拟驾驶员的决策过程.通过仿真试验,证实了该双模式ACC控制策略在满足行驶过程中的安全性以及舒适性的同时,有效地反映了驾驶员的日常行驶习惯,更易于被驾驶员接受,有利于提高ACC系统的使用率.

Abstract:

In order to design an adaptive cruise control (ACC) system which emulates humans’ driving behavior, a two-mode ACC algorithm in model predictive control (MPC) framework was proposed according to the analysis of humans’ driving habits. In this algorithm, fast approaching mode, which is activated when the interdistance is much larger than the desired value, is designed to approach the preceding vehicle quickly when safety and comfort are guaranteed; once the inter-distance is regulated to round the desired value, the ACC vehicle switches to the steady following mode to adapt the spacing and speed safely, reposefully and comfortably. The switching strategy between the two control modes is designed based on fuzzy logic, to imitate humans’ deciding which mode is activated, and smooth the switching responses. The simulation shows that the proposed ACC algorithm not only provides safe and comfortable driving, but also performs natural behaviors to human drivers, and therefore it will be more acceptable to human drivers and lead to the increased usage rate of ACC systems.

出版日期: 2011-12-01
:  TP 273  
基金资助:

国家自然科学基金资助项目(50908204).

通讯作者: 王慧,女,教授.     E-mail: hwang@iipc.zju.edu.cn
作者简介: 罗莉华(1985—),女,博士生,研究方向为智能交通和汽车自适应巡航控制.E-mail: lihualuo.zju06@gmail.com
服务  
把本文推荐给朋友
加入引用管理器
E-mail Alert
作者相关文章  

引用本文:

罗莉华, 龚李龙, 李平, 王慧. 考虑驾驶员行驶特性的双模式自适应
巡航控制设计[J]. J4, 2011, 45(12): 2073-2078.

LUO Li-hua, GONG Li-long, LI Ping, WANG Hui. Two-mode adaptive cruise control design with
humans’ driving habits consideration. J4, 2011, 45(12): 2073-2078.

链接本文:

https://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2011.12.001        https://www.zjujournals.com/eng/CN/Y2011/V45/I12/2073

[1] RAZA H, IOANNOU P. Vehicle following control design for automated highway systems [J]. IEEE Control Systems Magazine, 1996, 16(6): 43-60.
[2] VAHIDI A, ESKANDRIAN A. Research advances in intelligent collision avoidance and adaptive cruise control [J]. IEEE Transactions on Intelligent Transportation Systems, 2003, 4(3): 143-153.
[3] RAJAMANI R. Vehicle dynamics and control [M]. New York: Springer, 2006: 153-181.
[4] ZHANG Jianlong, IOANNOU P. Longitudinal control of heavy trucks in mixed traffic: environmental and fuel economy considerations [J]. IEEE Transactions on Intelligent Transportation Systems, 2006, 7(1): 92-104.
[5] NARANJO J E, GONZALEZ C, GARCIA R, et al. Adaptive fuzzy control for intervehicle gap keeping [J]. IEEE Transactions on Intelligent Transportation Systems, 2003, 4(3): 132-142.
[6] LUO Lihua, LIU Hong, LI Ping, et al. Model predictive control for adaptive cruise control with multiobjectives: comfort, fueleconomy, safety and carfollowing [J]. Journal of Zhejiang UniversityScience A, 2010, 11(3): 191-201.
[7] MOON S, YI K. Human driving databased design of a vehicle adaptive cruise control algorithm [J]. Vehicle System Dynamics, 2008, 46(8): 661-690.
[8] YI K, CHUNG J T. Nonlinear brake control for vehicle CW/CA systems [J]. IEEE Transactions on Mechatronics, 2001, 6(1): 17-25.
[9] LIANG Chiying, PENG Huei. Optimal adaptive cruise control with guaranteed string stability [J]. Vehicle System Dynamics, 1999, 32(4/5): 313-330.
[10] CHEN Xi, LI Zhaohua, YANG Jing, et al. Nested tabu search (TS) and sequential quadratic programming (SQP) method, combined with adaptive model reformulation for heat exchanger network synthesis (HENS) [J]. Industrial & Engineering Chemistry Research, 2008, 47(7): 2320-2330.
[11] ZADEH L A. Fuzzy Sets [J]. Information and Control, 1965, 8(3) : 338-353.

[1] 程森林,李雷,朱保卫,柴毅. WSN定位中的RSSI概率质心计算方法[J]. J4, 2014, 48(1): 100-104.
[2] 方强, 陈利鹏, 费少华, 梁青霄, 李卫平, 赵金锋. 定位器模型参考自适应控制系统设计[J]. J4, 2013, 47(12): 2234-2242.
[3] 罗继亮, 王飞,邵辉,赵良煦. 基于约束转换的Petri网最优监控器设计[J]. J4, 2013, 47(11): 2051-2056.
[4] 任雯, 胥布工. 基于FI-SNAPID算法的经编机多速电子送经系统开发[J]. J4, 2013, 47(10): 1712-1721.
[5] 李奇安, 金鑫. 对角CARIMA模型多变量广义预测近似解耦控制[J]. J4, 2013, 47(10): 1764-1769.
[6] 叶凌云,陈波,张建,宋开臣. 基于最少拍无波纹算法的高精度动态标准源反馈控制[J]. J4, 2013, 47(9): 1554-1558.
[7] 孟德远,陶国良,钱鹏飞,班伟. 气动力伺服系统的自适应鲁棒控制[J]. J4, 2013, 47(9): 1611-1619.
[8] 叶凌箭,马修水. 基于软测量技术的化工过程优化控制策略[J]. J4, 2013, 47(7): 1253-1257.
[9] 黄晓烁,何衍,蒋静坪. 基于互联网无刷直流电机传动系统的控制策略[J]. J4, 2013, 47(5): 831-836.
[10] 贺乃宝, 高倩, 徐启华, 姜长生. 基于自适应观测器的飞行器抗干扰控制[J]. J4, 2013, 47(4): 650-655.
[11] 朱予辰,冯冬芹,褚健. 基于EPA的块数据流通信调度与控制[J]. J4, 2012, 46(11): 2097-2102.
[12] 朱康武, 顾临怡, 马新军, 胥本涛. 水下运载器多变量鲁棒输出反馈控制方法[J]. J4, 2012, 46(8): 1397-1406.
[13] 刘志鹏, 颜文俊. 预粉磨系统的智能建模与复合控制[J]. J4, 2012, 46(8): 1506-1511.
[14] 费少华,方强,孟祥磊,柯映林. 基于压脚位移补偿的机器人制孔锪窝深度控制[J]. J4, 2012, 46(7): 1157-1161.
[15] 于晓明, 蒋静坪. 基于神经网络延时预测的自适应网络控制系统[J]. J4, 2012, 46(2): 194-198.