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ExtTra: Short-Term Traffic Flow Prediction Based on Extremely Randomized Trees

  • Jiaxing Shang
  • Xiaofan Yan
  • Linhui Feng
  • Zheng Dong
  • Haojie Wang
  • Shangbo Zhou
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11304)

Abstract

Short-term traffic flow prediction is an important task for intelligent transportation systems. Conventional time series based approaches such as ARIMA can hardly reflect the inter-dependence of related roads. Other parametric or nonparametric methods do not take full advantage of the spatial temporal features. Moreover, some machine learning models are still not investigated in solving this problem. To fill this gap, in this paper we propose ExtTra: an extremely randomized trees based approach for short-term traffic flow prediction. To the best of our knowledge, our work is the first effort to apply the extremely randomized trees model on the traffic flow prediction problem. Moreover, our approach incorporates new spatial temporal features which were not considered in previous studies. Experimental results show that our approach significantly outperforms the baselines in prediction accuracy.

Keywords

Traffic flow prediction Extremely randomized trees Spatial temporal features Intelligent transportation Machine learning 

Notes

Acknowledgements

This work was supported in part by: National Natural Science Foundation of China (No. 61702059), Frontier and Application Foundation Research Program of Chongqing City (No. cstc2018jcyjAX0340), Chongqing Industrial Generic Technology Innovation Program (No. cstc2017zdcy-zdzxX0010), Guangxi Key Laboratory of Trusted Software (No. kx201702).

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Jiaxing Shang
    • 1
    • 2
    • 3
  • Xiaofan Yan
    • 1
  • Linhui Feng
    • 1
  • Zheng Dong
    • 1
  • Haojie Wang
    • 1
  • Shangbo Zhou
    • 1
    • 2
  1. 1.College of Computer ScienceChongiqng UniversityChongqingChina
  2. 2.Key Laboratory of Dependable Service Computing in Cyber Physical Society, Ministry of Education, Chongqing UniversityChongqingChina
  3. 3.Guangxi Key Laboratory of Trusted SoftwareGuilin University of Electronic TechnologyGuilinChina

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