Trip-pair based clustering model for urban mobility of bus passengers in Macao

Document Type

Journal Article

Publication Date

2023

Subject Area

place - asia, place - urban, mode - bus, technology - passenger information, technology - ticketing systems, ridership - behaviour

Keywords

Smartcard data, clustering, urban mobility, regularity, transit bus

Abstract

Public transit is a major mode of urban mobility in Macao, a compact and populous city in China. Public transit ridership is related to round-the-clock shift-based work arrangements in the gaming industry. Smartcards that are used in transit fare collection are a vital data source for understanding the travel patterns and characteristics of transit passengers. However, transactional information from single data sources is fragmented, hindering the extraction of mobility patterns. We proposed a trip-pair-based clustering model that extracts the within-day mobility patterns of bus riders. DBSCAN is employed to filter scattered trips and hierarchical agglomerative clustering to identify clusters. Using a six-month smartcard dataset from Macao, categories of bus passengers were identified. Travel patterns exist with irregular, one-way, and round-trip passengers, and shift workers. The unique shift-based work-life and mixed travel modes in Macao can serve as an example of dense and compact city travel for smart cities.

Rights

Permission to publish the abstract has been given by Taylor&Francis, copyright remains with them.

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