An expert system to discover key congestion points for urban traffic

作者：

Highlights：

• Define key congestion points and convert it to a feature selection problem.

• Propose an expert system to discover key congestion points of urban traffic.

• Revise BSSReduce, which runs 15 times faster than BSSReduce for this data.

• Discover 75 and 300 key congestion points from over 10,000 and 50,000 points.

摘要

•Define key congestion points and convert it to a feature selection problem.•Propose an expert system to discover key congestion points of urban traffic.•Revise BSSReduce, which runs 15 times faster than BSSReduce for this data.•Discover 75 and 300 key congestion points from over 10,000 and 50,000 points.

论文关键词：Key points of congestion,BSSReduce,Digital map,Feature selection,Soft sets,Rough sets

论文评审过程：Received 16 October 2019, Revised 29 December 2019, Accepted 8 May 2020, Available online 4 June 2020, Version of Record 21 June 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.113544