Journal of South China University of Technology (Natural Science Edition) ›› 2015, Vol. 43 ›› Issue (10): 1-7.doi: 10.3969/j.issn.1000-565X.2015.10.001

• Traffic & Transportation Engineering •     Next Articles

A Dynamic Shortest Path Algorithm for Big Data

Xu Jian-min Wang Yu Lin Pei-qun   

  1. School of Civil Engineering and Transportation，South China University of Technology，Guangzhou 510640，Guangdong，China
  • Received:2014-12-02 Revised:2015-06-01 Online:2015-10-25 Published:2015-09-06
  • Contact: 徐建闽( 1960-) ，男，教授，博士生导师，主要从事智能交通系统、交通信息工程及控制研究． E-mail:aujmxu@scut,edu,cn
  • About author:徐建闽( 1960-) ，男，教授，博士生导师，主要从事智能交通系统、交通信息工程及控制研究．
  • Supported by:
    Supported by the National Natural Science Foundation of China( 51108191，61174184) and the Major Science and Technology Foundation of Guangdong Province( 2012A010800007)

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Abstract: Massive heterogeneous data processing has been a great challenge to intelligent traffic applications． In this paper，the dynamic shortest path problem in traffic guidance is dealt with，and a mathematic model of dynamic traffic networks is constructed． Then，a dynamic shortest path algorithm considering the intersection delay is proposed． Furthermore，a distributed and parallel processing model for solving the dynamic shortest path problem is presented based on HaLoop MapＲeduce and by using big data techniques． Finally，the proposed algorithm is tested on the intelligent traffic management and control platform based on continual flow． Experimental results demonstrate that the proposed algorithm and the presented model can effectively find the dynamic shortest path in large scale networks and can meet the real-time requirement．

Key words: big data, dynamic shortest path algorithm, intersection delay, route guidance

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