Road traffic density estimation using microscopic and macroscopic parameters

作者：

Highlights：

• We propose an algorithm for road traffic congestion estimation from video scenes.

• We compare between macroscopic and microscopic parameters in terms of accuracy.

• The method proposed is accurate, and it is computationally inexpensive.

• It does not require segmentation or tracking of vehicles.

• It is robust towards illumination changes.

摘要

•We propose an algorithm for road traffic congestion estimation from video scenes.•We compare between macroscopic and microscopic parameters in terms of accuracy.•The method proposed is accurate, and it is computationally inexpensive.•It does not require segmentation or tracking of vehicles.•It is robust towards illumination changes.

论文关键词：Road traffic density estimation,Microscopic and macroscopic traffic parameters,Motion detection and tracking,KNN,LVQ,SVM

论文评审过程：Received 13 January 2013, Revised 6 July 2013, Accepted 23 September 2013, Available online 30 September 2013.

论文官网地址：https://doi.org/10.1016/j.imavis.2013.09.006