Short-Term Traffic Flow Prediction Based on Multilinear Analysis and k-Nearest Neighbor Regression

Yuankai Wu, Huachun Tan, Jin Peter, Bin Shen, Bin Ran

Research output: Chapter in Book/Report/Conference proceedingConference contribution

20 Scopus citations

Abstract

Prevailing short-Term traffic flow prediction models concentrate on using black-box type of artificial intelligence (AI) algorithms without explicit knowledge of traffic flow data. In this paper, a novel short-Term traffic flow prediction method Ml-k-NN was developed using multilinear analysis. The model recognizes the lane flow distribution within the traffic flow data and uses the k-nearest neighbor to predict traffic flow. The proposed multilinear analysis technique employs a dynamic tensor form of traffic flow data and uses tensor decomposition to combine several characteristics of traffic flow data. With the tensor decomposition, we can not only find the spatial-Temporal information and lane distribution of traffic flow pattern, but also acquire the short-Term traffic prediction by applying the k-nearest neighbor method on the generated features. Experiments on real traffic data acquired from 10 locations on 4-lane freeway are provided to validate and evaluate the proposed approach. Experimental results show that the proposed method has the promising performance in predicting traffic flow.

Original languageEnglish (US)
Title of host publicationCICTP 2015 - Efficient, Safe, and Green Multimodal Transportation - Proceedings of the 15th COTA International Conference of Transportation Professionals
EditorsXuedong Yan, Yu Zhang, Yafeng Yin
PublisherAmerican Society of Civil Engineers (ASCE)
Pages556-569
Number of pages14
ISBN (Electronic)9780784479292
DOIs
StatePublished - 2015
Event15th COTA International Conference of Transportation Professionals: Efficient, Safe, and Green Multimodal Transportation, CICTP 2015 - Beijing, China
Duration: Jul 24 2015Jul 27 2015

Publication series

NameCICTP 2015 - Efficient, Safe, and Green Multimodal Transportation - Proceedings of the 15th COTA International Conference of Transportation Professionals

Other

Other15th COTA International Conference of Transportation Professionals: Efficient, Safe, and Green Multimodal Transportation, CICTP 2015
Country/TerritoryChina
CityBeijing
Period7/24/157/27/15

All Science Journal Classification (ASJC) codes

  • Transportation

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