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基于区间二型模糊集合的人工交通系统可信度评估

李润梅 梁秋鸿

李润梅, 梁秋鸿. 基于区间二型模糊集合的人工交通系统可信度评估. 自动化学报, 2019, 45(10): 1915-1922. doi: 10.16383/j.aas.c180105
引用本文: 李润梅, 梁秋鸿. 基于区间二型模糊集合的人工交通系统可信度评估. 自动化学报, 2019, 45(10): 1915-1922. doi: 10.16383/j.aas.c180105
LI Run-Mei, LIANG Qiu-Hong. Artificial Traffic System Credibility Evaluation With Interval Type-2 Fuzzy Sets. ACTA AUTOMATICA SINICA, 2019, 45(10): 1915-1922. doi: 10.16383/j.aas.c180105
Citation: LI Run-Mei, LIANG Qiu-Hong. Artificial Traffic System Credibility Evaluation With Interval Type-2 Fuzzy Sets. ACTA AUTOMATICA SINICA, 2019, 45(10): 1915-1922. doi: 10.16383/j.aas.c180105

基于区间二型模糊集合的人工交通系统可信度评估

doi: 10.16383/j.aas.c180105
基金项目: 

国家重点研发计划 2018YFB1201500

详细信息
    作者简介:

    梁秋鸿   北京交通大学智能系统与可再生能源中心硕士研究生.主要研究方向为交通流量预测和交通信息处理.E-mail:17120235@bjtu.edu.cn

    通讯作者:

    李润梅  北京交通大学电子信息工程学院副教授.2005年获中国科学院自动化研究所控制理论与控制工程博士学位.主要研究方向为交通信息处理, 无人驾驶车辆的路径规划和控制.本文通信作者.E-mail:rmli@bjtu.edu.cn

Artificial Traffic System Credibility Evaluation With Interval Type-2 Fuzzy Sets

Funds: 

National Key Research and Development Program of China 2018YFB1201500

More Information
    Author Bio:

     Master student at the Center for Intelligent Systems and Renewable Energy, Beijing Jiaotong University. Her research interest covers traffic flow prediction and traffic information processing

    Corresponding author: LI Run-Mei   Associate professor at the School of Electronic and Information Engineering of Beijing Jiaotong University. She received her Ph. D. degree in control theory and control engineering from the Institute of Automation, Chinese Academy of Sciences in 2005. Her research interest covers traffic information processing, path planning and control for unmanned vehicles. Corresponding author of this paper
  • 摘要: 提出了一种基于区间二型模糊集合理论的人工交通系统可信度评估方法.该方法以二型模糊集合算法为核心数据处理方法,构建了人工交通系统的评估体系.利用置信区间方法提取实际交通数据和人工交通数据的统计特征,同时为二型模糊集合提供了输入数据.利用二型模糊集合处理不确定性、随机性和噪声数据的能力,得到刻画实际交通系统和人工交通系统特性的输出数据集.并基于Jaccard算法对两个系统二型模糊集合的输出集进行了相似度运算,以Cronbach系数值为依据,实现了人工交通系统的可信度评估.与传统可信度评估方法相比,该评估方法具有较强的数据处理能力,有效地实现了基于数据驱动方法理念下人工系统与实际系统之间的比较.本文基于面向对象编程语言搭建开发的基于Agent的人工交通系统模型,对其进行了可信度评估验证,评估结果说明了所提出方法的合理性和有效性.
    1)  本文责任编委 莫红
  • 图  1  基于二型模糊集合理论的人工交通系统评估过程

    Fig.  1  Artificial traffic system assessment process based on type-2 fuzzy set theory

    图  2  24小时交通流量的区间化描述

    Fig.  2  The interval description of 24 hours traffic flow

    图  3  典型人工公共交通系统模型

    Fig.  3  Typical artificial transit traffic system model

    图  4  区间算法一型模糊集合并运算

    Fig.  4  An example of the union of type-1 fuzzy sets

    图  5  三个候车站实际候车乘客数据和对应的人工交通系统候车乘客人数数据的二型模糊集合

    Fig.  5  Two-type fuzzy set of three stations actual data and corresponding simulation data

    表  1  三个公交车站上车人数的实际调研数据和人工交通系统运行数据

    Table  1  The actual data and simulation data of people get on the three bus stops

    时段 实际系统第1站 仿真系统第1站 实际系统第2站 仿真系统第2站 仿真系统第3站 实际系统第3站
    3:00 $\sim$ 3:05 9 13 8 15 4 5
    3:06 $\sim$ 3:10 10 15 10 13 0 1
    3:11 $\sim$ 3:15 14 9 5 8 3 3
    3:16 $\sim$ 3:20 0 25 6 9 1 2
    3:21 $\sim$ 3:25 29 20 16 0 6 3
    3:26 $\sim$ 3:30 25 3 11 19 3 5
    3:31 $\sim$ 3:35 15 17 5 6 4 8
    3:36 $\sim$ 3:40 10 0 7 6 3 2
    3:41 $\sim$ 3:45 15 9 8 0 5 1
    3:46 $\sim$ 3:50 19 15 6 11 1 0
    3:51 $\sim$ 3:55 9 21 10 9 4 4
    3:56 $\sim$ 4:00 19 4 16 18 0 2
    下载: 导出CSV

    表  2  三个公交车站上车人数模糊化以后的实际数据和仿真数据

    Table  2  The actual data and simulation data after fuzzified of people get on the three bus stops

    时段 实际系统第1站 仿真系统第1站 实际系统第2站 仿真系统第2站 仿真系统第3站 实际系统第3站
    3:00 $\sim$ 3:05 2      4 3      5 3      5 6      8 3      5 4      6
    3:06 $\sim$ 3:10 2      4 4      6 4      6 6      8 0      1 0      2
    3:11 $\sim$ 3:15 3      5 2      4 1      3 3      5 2      4 2      4
    3:16 $\sim$ 3:20 0      1 7      9 2      4 3      5 0      2 1      3
    3:21 $\sim$ 3:25 6      8 6      8 7      9 0      1 5      7 2      4
    3:26 $\sim$ 3:30 6      8 0      2 4      6 5      7 2      4 4      6
    3:31 $\sim$ 3:35 4      6 5      7 1      3 2      4 3      5 7      9
    3:36 $\sim$ 3:40 2      4 0      1 3      5 2      4 2      4 1      3
    3:41 $\sim$ 3:45 4      6 2      4 3      5 0      1 4      6 0      2
    3:46 $\sim$ 3:50 5      7 4      6 2      4 4      6 0      2 0      1
    3:51 $\sim$ 3:55 2      4 6      8 4      6 4      6 3      5 3      5
    3:56 $\sim$ 4:00 5      7 0      2 7      9 8      9 0      1 1      3
    下载: 导出CSV

    表  3  可信度值与Cronbach系数的关系

    Table  3  The relationship between the value of credibility and Cronbach coefficient

    系统可信程度 Cronbach系数(可信度)
    不可信 $ < 0.3$
    勉强可信 $0.3 \leq\alpha < 0.4$
    可信 $0.4 \leq\alpha < 0.5$
    很可信(最常见) $0.5 \leq\alpha < 0.7$
    很可信(次常见) $0.7 \leq\alpha < 0.9$
    十分可信 $0.9 \leq\alpha$
    下载: 导出CSV
  • [1] 王飞跃, 汤淑明.人工交通系统的基本思想与框架体系.复杂系统与复杂性科学, 2004, 1(2):52-59 doi: 10.3969/j.issn.1672-3813.2004.02.008

    Wang Fei-Yue, Tang Shu-Ming. Concepts and frameworks of artificial transportation systems. Complex Systems and Complexity Science, 2004, 1(2):52-59 doi: 10.3969/j.issn.1672-3813.2004.02.008
    [2] 王飞跃, 史蒂夫·兰森.从人工生命到人工社会-复杂社会系统研究的现状和展望.复杂系统与复杂性科学, 2004, 1(1):34-41 http://d.old.wanfangdata.com.cn/Periodical/fzxtyfzxkx200401007

    Wang Fei-Yue, Lansing J S. From artificial life to artificial societies-new methods for studies of complex social systems. Complex Systems and Complexity Science, 2004, 1(1):34-41 http://d.old.wanfangdata.com.cn/Periodical/fzxtyfzxkx200401007
    [3] Wang F-Y, Tang S M. A framework for artificial transportation systems: from computer simulations to computational experiments. In: Proceedings of the 2005 IEEE Intelligent Transportation Systems. Vienna, Austria: IEEE, 2005. 1130-1134
    [4] Zheng X L, Zhong Y G, Zeng D, Wang F-Y. Social influence and spread dynamics in social networks. Frontiers of Computer Science, 2012, 6(5):611-620 http://d.old.wanfangdata.com.cn/OAPaper/oai_arXiv.org_1311.3475
    [5] 王飞跃.计算实验方法与复杂系统行为分析和决策评估.系统仿真学报, 2004, 16(5):893-897 doi: 10.3969/j.issn.1004-731X.2004.05.009

    Wang Fei-Yue. Computational experiments for behavior analysis and decision evaluation of complex systems. Journal of System Simulation, 2004, 16(5):893-897 doi: 10.3969/j.issn.1004-731X.2004.05.009
    [6] Wang F-Y, Yang L Q, Cheng X, Han S S, Yang J. Network softwarization and parallel networks:beyond software-defined networks. IEEE Network, 2016, 30(4):60-65 doi: 10.1109/MNET.2016.7513865
    [7] Holland J H. Emergence: From Chaos to Order. Boston, MA, USA: Addison-Wesley Longman Publishing Co., Inc., 1998.
    [8] Helmreich S. Silicon Second Nature:Culturing Artificial Life in a Digital World. Berkeley, CA, USA:University of California Press, 2000.
    [9] Herzog T N. Introduction to Credibility Theory (3rd edition). Winsted, CT:ACTEX Publications, 1999.
    [10] Freeman K S, Spyridakis J H. Effect of contact information on the credibility of online health information. IEEE Transactions on Professional Communication, 2009, 52(2):152-166 doi: 10.1109/TPC.2009.2017992
    [11] Pawlikowski K, Jeong H D J, Lee J S R. On credibility of simulation studies of telecommunication networks. IEEE Communications Magazine, 2002, 40(1):132-139 doi: 10.1109/35.978060
    [12] 孙剑, 李克平.微观交通系统仿真模型可信性评价.计算机仿真, 2010, 27(1):276-280 doi: 10.3969/j.issn.1006-9348.2010.01.076

    Sun Jian, Li Ke-Ping. Credibility evaluation for micro traffic simulation model. Computer Simulation, 2010, 27(1):276-280 doi: 10.3969/j.issn.1006-9348.2010.01.076
    [13] 张俊杰, 赵栋.双馈风电机组低电压穿越仿真模型可信度评估.电力与能源, 2017, 38(4):459-462 http://d.old.wanfangdata.com.cn/Periodical/dlyny201704024

    Zhang Jun-Jie, Zhao Dong. Credibility evaluation for Doubly-Fed induction generator low voltage ride-through simulation model. Power and Energy, 2017, 38(4):459-462 http://d.old.wanfangdata.com.cn/Periodical/dlyny201704024
    [14] 陈建球.基于SOA的列控仿真系统设计及可信性研究[博士学位论文], 北京交通大学, 中国, 2017. http://cdmd.cnki.com.cn/Article/CDMD-10004-1017095157.htm

    Chen Jian-Qiu. Research on Design and Credibility of Train Control Simulation System Based on SOA[Ph.D. dissertation], Beijing Jiaotong University, China, 2017. http://cdmd.cnki.com.cn/Article/CDMD-10004-1017095157.htm
    [15] Schaub F, Hipp M, Kargl F, Weber M. On credibility improvements for automotive navigation systems. Personal and Ubiquitous Computing, 2013, 17(5):803-813 doi: 10.1007/s00779-012-0519-0
    [16] 宿相萍, 林琪.卫星网络仿真系统可信度评估方法.中南大学学报(自然科学版), 2011, 42(S1):969-973 http://d.old.wanfangdata.com.cn/Conference/7651779

    Su Xiang-Ping, Lin Qi. Credibility evaluation method for satellite network simulation system. Journal of Central South University (Science and Technology), 2011, 42(S1):969-973 http://d.old.wanfangdata.com.cn/Conference/7651779
    [17] Liu Z B, Liu W Z, Fang L, Tang Y Z. Channel allocation model and credibility evaluation for LBS indoor nodes. Journal of Computer Applications, 2013, 33(3):603-606 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=jsjyy201303001
    [18] 焦鹏, 唐见兵, 查亚兵.仿真可信度评估中相似度方法的改进及其应用.系统仿真学报, 2007, 19(12):2658-2660 doi: 10.3969/j.issn.1004-731X.2007.12.006

    Jiao Peng, Tang Jian-Bing, Zha Ya-Bing. Amelioration and application of similar degree method for simulation credibility evaluation. Journal of System Simulation, 2007, 19(12):2658-2660 doi: 10.3969/j.issn.1004-731X.2007.12.006
    [19] Darty K, Saunier J, Sabouret N. Behavior clustering and explicitation for the study of agents' credibility: application to a virtual driver simulation. In: Proceedings of the 6th International Conference on Agents and Artificial Intelligence. Angers, France: Springer-Verlag, 2014, 8946: 82-99
    [20] Li R M, Liu J Z, Dong H R. On credibility validation of the artificial urban rail transportation system. In: Proceedings of the 2011 IEEE International Conference on Service Operations, Logistics, and Informatics. Beijing, China: IEEE, 2011. 570-573
    [21] Zhao X, Li X, Yue Q B. Application of fuzzy comprehensive evaluation method in the equipment supply support effectiveness evaluation. In: Proceedings of the 2011 International Conference on Applied Informatics and Communication. Applied Informatics and Communication. Berlin, Heidelberg, Germany: Springer, 2011. 700-705
    [22] 吴静, 吴晓燕, 高忠长.复杂仿真系统建模与仿真可信性模糊综合评估.计算机集成制造系统, 2010, 16(2):287-292 http://d.old.wanfangdata.com.cn/Periodical/jsjjczzxt201002009

    Wu Jing, Wu Xiao-Yan, Gao Zhong-Chang. Fuzzy synthesis evaluation of modeling and simulation credibility for complex simulation system. Computer Integrated Manufacturing Systems, 2010, 16(2):287-292 http://d.old.wanfangdata.com.cn/Periodical/jsjjczzxt201002009
    [23] Zadeh L A. The concept of a linguistic variable and its application to approximate reasoning-I. Information Sciences, 1975, 8(3):199-249 doi: 10.1016/0020-0255(75)90036-5
    [24] Mendel J M. Type-2 fuzzy sets and systems:an overview. IEEE Computational Intelligence Magazine, 2007, 2(2):20-29 http://d.old.wanfangdata.com.cn/NSTLHY/NSTL_HYCC0211004221/
    [25] 王飞跃, 莫红.关于二型模糊集合的一些基本问题.自动化学报, 2017, 43(7):1114-1141 http://www.aas.net.cn/CN/abstract/abstract19087.shtml

    Wang Fei-Yue, Mo Hong. Some fundamental issues on type-2 fuzzy sets. Acta Automatica Sinica. 2017, 43(7):1114-1141 http://www.aas.net.cn/CN/abstract/abstract19087.shtml
    [26] 盛骤, 谢式千, 潘承毅.概率论与数理统计.第4版.北京:高等教育出版社, 2008.

    Sheng Zhou, Xie Shi-Qian, Pan Cheng-Yi. Probability Theory and Mathematical Statistics (4th Edition). Beijing:Higher Education Press, 2008.
    [27] Dehay D, Leskow J, Napolitano A. Central limit theorem in the functional approach. IEEE Transactions on Signal Processing, 2013, 61(16):4025-4037 doi: 10.1109/TSP.2013.2266324
    [28] Real R, Vargas J M. The probabilistic basis of Jaccard's index of similarity. Systematic Biology, 1996, 45(3):380-385 doi: 10.1093/sysbio/45.3.380
    [29] Bell J, Dee H M. The subset-matched Jaccard index for evaluation of segmentation for plant images. 2016, arXiv: 1611.06880
    [30] Rinartha K, Suryasa W. Comparative study for better result on query suggestion of article searching with MySQL pattern matching and Jaccard similarity. In: Proceedings of the 5th International Conference on Cyber and IT Service Management. Denpasar, Indonesia: IEEE, 2017. 1-4
    [31] Wu D R, Mendel J M. A comparative study of ranking methods, similarity measures and uncertainty measures for interval type-2 fuzzy sets. Information Sciences, 2009, 179(8):1169-1192 doi: 10.1016/j.ins.2008.12.010
    [32] Cho E. Making reliability reliable:a systematic approach to reliability coefficients. Organizational Research Methods, 2016, 19(4):651-682 http://cn.bing.com/academic/profile?id=7a35960b28a75397dc5b03883d051ac5&encoded=0&v=paper_preview&mkt=zh-cn
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  • 收稿日期:  2018-02-26
  • 录用日期:  2018-08-30
  • 刊出日期:  2019-10-20

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