Trip end identification based on spatial-temporal clustering algorithm using smartphone positioning data

作者：

Highlights：

• A spatial-temporal density-based clustering algorithm is proposed for trip end detection.

• Three scenario optimization models are applied to improve the method capability.

• A smartphone application is developed for GNSS data collection.

• The potential of the method is demonstrated by comparing results with travel log.

摘要

•A spatial-temporal density-based clustering algorithm is proposed for trip end detection.•Three scenario optimization models are applied to improve the method capability.•A smartphone application is developed for GNSS data collection.•The potential of the method is demonstrated by comparing results with travel log.

论文关键词：Travel survey,Trip end Identification,Smartphone GNSS data,Spatial-temporal density based clustering

论文评审过程：Received 18 October 2020, Revised 14 June 2021, Accepted 22 February 2022, Available online 24 February 2022, Version of Record 12 March 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.116734