Evaluation of Network-Level Traffic State Using 2DLNMF Algorithm

Abstract

Abstract:

Abstract： Network-level traffic state reflects the macroscopical conditions of the road network. The exesting evaluation algorithms have some shortcomings such as their applicable conditions are limited to section and they just depend on a single index. As a result, based on the analysis of the correlation between the measuring index and sections and the local nonnegative matrix factorization(LNMF) algorithm, the algorithm of 2DLNMF was proposed and the features of the traffic data were extracted by choosing appropriate parameters to reduce the numbers of dimensions of the road network data. The simulation results indicate that the evaluation of 2DLNMF is more accurate and its online accuracy is up to 95.69%.

Key words: network-level traffic state, cluster, 2D-local non-negative matrix factorization (2D-LNMF), feature extraction

XU Rong,WU Cong,JIANG ShiZheng,CHEN QiMei. Evaluation of Network-Level Traffic State Using 2DLNMF Algorithm[J]. Journal of Shanghai Jiaotong University, 2015, 49(08): 1131-1136.

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