Volume 14 Issue 3
. 
Turn off MathJax
Article Contents
Article Navigation >  Journal of Traffic and Transportation Engineering  > 2014  >  14(3): 87-94
XIE Hai-hong, DAI Xu-hao, QI Yuan. Improved K-nearest neighbor algorithm for short-term traffic flow forecasting[J]. Journal of Traffic and Transportation Engineering, 2014, 14(3): 87-94.
Citation: XIE Hai-hong, DAI Xu-hao, QI Yuan. Improved K-nearest neighbor algorithm for short-term traffic flow forecasting[J]. Journal of Traffic and Transportation Engineering, 2014, 14(3): 87-94.
shu

Improved K-nearest neighbor algorithm for short-term traffic flow forecasting

  • 1.

    MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing 100044, China

  • 2.

    Center of Cooperative Innovation for Beijing Metropolitan Transportation, Beijing 100044, China

  • 3.

    Hunan Provincial Communications Planning, Survey and Design Institute, Changsha 410008, Hunan, China

More Information
  • Author Bio:

    XIE Hai-hong (1963-), female, associate professor, +86-10-51687138, xiehaihong16@163.com

  • Received Date: 2014-01-13
  • Publish Date: 2014-06-25
    Abstract
  • The original K-nearest neighbor algorithm for short-term traffic flow forecasting was analyzed.Pattern distance search method was used to replace the original Euclidean distance search method, the multiple statistics regression model was introduced, an improved K-nearest neighbor algorithm for short-term traffic flow forecasting was put forward, and an example verification was carried out by using the traffic flow data from a certain section in Beijing.Test result indicates when Kis 23, the error of mean square, mean absolute error and average relative error of forecasting results are 31.43%, 4.17% and 0.27% respectively by using the improved K-nearest neighbor algorithm.By using the original K-nearest neighbor algorithm, the error of mean square, mean absolute error and average relative error of forecasting results are 33.33%, 4.40% and 0.28% respectively.By using the historical average model, the error of mean square, mean absolute error and average relative error of forecasting results are 46.20%, 11.40% and 0.48% respectively.The forecasting accuracy of the improved K-nearest neighbor algorithm is obviously higher than the other two algorithms.The improved K-nearest neighbor algorithm notonly increases searching efficiency, but also accurately reflects the real situation of traffic flow.

     

    • FullText(HTML)
  • loading
    • References(22)
  • [1]
    贺国光, 李宇, 马寿峰. 基于数学模型的短时交通流预测方法探讨[J]. 系统工程理论与实践, 2000, 20 (12): 51-56. https://www.cnki.com.cn/Article/CJFDTOTAL-XTLL200012007.htm

    HE Guo-guang, LI Yu, MA Shou-feng. Discussion on shortterm traffic flow forecasting methods based on mathematical models[J]. Systems Engineering—Theory and Practice, 2000, 20 (12): 51-56. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-XTLL200012007.htm
    [2]
    SMITH B L, DEMETSKY M J. Traffic flow forecasting: comparison of modeling approaches[J]. Journal of Transportation Engineering, 1997, 123 (4): 261-266. doi: 10.1061/(ASCE)0733-947X(1997)123:4(261)
    [3]
    KREER J B. A comparison of predictor algorithms for computerized control[J]. Traffic Engineering, 1975, 45 (4): 51-56.
    [4]
    WILLIAMS B M, HOEL L A. Modeling and forecasting vehicular traffic flow as a seasonal ARIMA process: theoretical basis and empirical results[J]. Journal of Transportation Engineering, 2003, 129 (6): 664-672. doi: 10.1061/(ASCE)0733-947X(2003)129:6(664)
    [5]
    OKUTANI I, STEPHANEDES Y J. Dynamic prediction of traffic volume through Kalman filtering theory[J]. Transportation Research Part B: Methodological, 1984, 18 (1): 1-11. doi: 10.1016/0191-2615(84)90002-X
    [6]
    SIMON D, SIMON D L. Kalman filtering with inequality constraints for turbofan engine health estimation[J]. Control Theory and Applications, 2006, 153 (3): 371-378. doi: 10.1049/ip-cta:20050074
    [7]
    董春娇, 邵春福, 熊志华, 等. 基于Elman神经网络的道路网短时交通流预测方法[J]. 交通运输系统工程与信息, 2010, 10 (1): 145-151. https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT201001022.htm

    DONG Chun-jiao, SHAO Chun-fu, XIONG Zhi-hua, et al. Short-term traffic flow forecasting of road network based on Elman neural net work[J]. Journal of Transportation Systems Engineering and Information Technology, 2010, 10 (1): 145-151. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT201001022.htm
    [8]
    魏文, 余立建, 龚炯. 基于混沌理论和PSO神经网络的短时交通流预测[J]. 物流工程与管理, 2010, 32 (2): 75-77. https://www.cnki.com.cn/Article/CJFDTOTAL-SPCY201002031.htm

    WEI Wen, YU Li-jian, GONG Jiong. Short-time traffic flow prediction based on chaos and particle swarm optimized neural network[J]. Logistics Engineering and Management, 2010, 32 (2): 75-77. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-SPCY201002031.htm
    [9]
    承向军, 刘军, 马敏书. 基于分形理论的短时交通流预测算法[J]. 交通运输系统工程与信息, 2010, 10 (4): 106-110. https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT201004017.htm

    CHENG Xiang-jun, LIU Jun, MA Min-shu. Algorithm of short-term traffic flow forecasting using fractal theory[J]. Journal of Transportation System Engineering and Information Technology, 2010, 10 (4): 106-110. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT201004017.htm
    [10]
    樊娜, 赵祥模, 戴明, 等. 短时交通流预测模型[J]. 交通运输工程学报, 2012, 12 (4): 114-119. http://transport.chd.edu.cn/article/id/201204015

    FAN Na, ZHAO Xiang-mo, DAI Ming, et al. Short-term traffic flow prediction model[J]. Journal of Traffic and Transportation Engineering, 2012, 12 (4): 114-119. (in Chinese). http://transport.chd.edu.cn/article/id/201204015
    [11]
    林德花, 袁振洲. 基于IOWA算子的短时交通流预测方法研究[J]. 科学技术与工程, 2013, 13 (25): 7596-7600. https://www.cnki.com.cn/Article/CJFDTOTAL-KXJS201325063.htm

    LIN De-hua, YUAN Zhen-zhou. Research on short-term traffic flow forecasting method based on IOWA operator[J]. Science Technology and Engineering, 2013, 13 (25): 7596-7600. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-KXJS201325063.htm
    [12]
    ISHAK S, ALECSANDRU C. Optimizing traffic prediction performance of neural networks under various topological input and traffic condition setting[J]. Journal of Transportation Engineering, 2004, 130 (7): 452-465.
    [13]
    SMITH B L, WILLIAMS B M R, OSWALD K. Comparison of parametric and nonparametric models for traffic flow forecasting[J]. Transportation Research Part C: Emerging Technologies, 2002, 10 (4): 303-321.
    [14]
    宫晓燕, 汤淑明. 基于非参数回归的短时交通流预测与事件检测综合算法[J]. 中国公路学报, 2003, 16 (1): 82-86.

    GONG Xiao-yan, TANG Shu-ming. Integrated traffic flow forecasting and traffic incident detection algorithm based on non-parametric regression[J]. China Journal of Highway and Transport, 2003, 16 (1): 82-86. (in Chinese).
    [15]
    周小鹏, 冯奇, 孙立军. 基于最近邻法的短时交通流预测[J]. 同济大学学报: 自然科学版, 2006, 34 (10): 1494-1498. https://www.cnki.com.cn/Article/CJFDTOTAL-TJDZ200611014.htm

    ZHOU Xiao-peng, FENG Qi, SUN Li-jun. Short-term traffic flow forecasting based on nearest neighbor algorithm[J]. Journal of Tongji University: Natural Science, 2006, 34 (10): 1494-1498. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-TJDZ200611014.htm
    [16]
    于滨, 邬珊华, 王明华, 等. K近邻短时交通流预测模型[J]. 交通运输工程学报, 2012, 12 (2): 105-111. http://transport.chd.edu.cn/article/id/201202015

    YU Bin, WU Shan-hua, WANG Ming-hua, et al. K-nearest neighbor model of short-term traffic flow forecast[J]. Journal of Traffic and Transportation Engineering, 2012, 12 (2): 105-111. (in Chinese). http://transport.chd.edu.cn/article/id/201202015
    [17]
    屈莉, 兰时勇, 张建伟. 基于浮动车数据非参数回归短时交通速度预测[J]. 计算机工程与设计, 2013, 34 (9): 3298-3332. https://www.cnki.com.cn/Article/CJFDTOTAL-SJSJ201309059.htm

    QU Li, LAN Shi-yong, ZHANG Jian-wei. Short-term traffic forecasting based on nonparametric regression and floating car data[J]. Computer Engineering and Design, 2013, 34 (9): 3298-3332. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-SJSJ201309059.htm
    [18]
    李振龙, 张利国, 钱海峰. 基于非参数回归的短时交通流预测研究综述[J]. 交通运输工程与信息学报, 2008, 6 (4): 34-39. https://www.cnki.com.cn/Article/CJFDTOTAL-JTGC200804009.htm

    LI Zhen-long, ZHANG Li-guo, QIAN Hai-feng. Review of the short-term traffic flow forecasting based on the non-parametric regression[J]. Journal of Transportation Engineering and Information, 2008, 6 (4): 34-39. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-JTGC200804009.htm
    [19]
    王达, 荣冈. 时间序列的模式距离[J]. 浙江大学学报: 工学版, 2004, 38 (7): 795-798. https://www.cnki.com.cn/Article/CJFDTOTAL-ZDZC200407001.htm

    WANG Da, RONG Gang. Pattern distance of time series[J]. Journal of Zhejiang University: Engineering Science, 2004, 38 (7): 795-798. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-ZDZC200407001.htm
    [20]
    吴耿锋, 周佩玲, 储阅春, 等. 基于相空间重构的预测方法及其在天气预报中的应用[J]. 自然杂志, 1999, 21 (2): 107-110. https://www.cnki.com.cn/Article/CJFDTOTAL-ZRZZ199902011.htm

    WU Geng-feng, ZHOU Pei-ling, CHU Yue-chun, et al. Prediction based on phrase construction and its application in weather forecast[J]. Nature Magazine, 1999, 21 (2): 107-110. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-ZRZZ199902011.htm
    [21]
    朱莉, 吴建华, 胡广书. 基于Cao算法的心率变异信号分析[J]. 航天医学与医学工程, 2009, 22 (2): 132-134. https://www.cnki.com.cn/Article/CJFDTOTAL-HYXB200902013.htm

    ZHU Li, WU Jian-hua, HU Guang-shu. Analysis of heart rate variability signal based on Cao algorithm[J]. Space Medicine and Medical Engineering, 2009, 22 (2): 132-134. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-HYXB200902013.htm
    [22]
    陈德望, 高海军, 陈龙, 等. 城市高速道路微波检测器RTMS的检测精度分析[J]. 公路交通科技, 2002, 19 (5): 122-124. https://www.cnki.com.cn/Article/CJFDTOTAL-GLJK200205034.htm

    CHEN De-wang, GAO Hai-jun, CHEN Long, et al. Accuracy analysis of RTMS on urban freeway[J]. Journal of Highway and Transportation Research and Development, 2002, 19 (5): 122-124. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-GLJK200205034.htm
    • Relative Articles
    • Supplements(0)
    • Cited By
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索
    Get Citation
    PDF
    XML

    Article Metrics

    Article views (714) PDF downloads(871) Cited by()
    Proportional views
    Related

    Copyright《Journal of Traffic and Transportation Engineering》编辑部陕ICP备05001904号-1

    Address ：Editorial Department of Journal of Traffic and Transportation Engineering, Chang 'an University, Middle Section of South Second Ring Road, Xi 'an, Shaanxi（710064） Tel：029-82334388 Email：jygc@chd.edu.cn

    All visit:Today's visit:

    Supported by: Beijing Renhe Information Technology Co. Ltd    

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return