Comparing Sequential with Combined Spatiotemporal Clustering of Passenger Trips in the Public Transit Network Using Smart Card Data

Table 1

Literature review.

Clustering type	Study	Description
Temporal clustering	Agard et al. [4]	Clustering trips based on boarding time transactions.
	Ghaemi et al. [22]	Clustering passengers based on boarding time transactions.
Spatial clustering	Tao et al. [18]	Clustering trips based on locations of boarding and alighting stops.
Spatial-Temporal clustering	Ma et al. [16]	Clustering trips first based on location of boarding stops, then dividing clusters according to the time interval of boarding transactions.
	Nishiuchi et al. [17]	Clustering and investigating relations between the spatial and temporal patterns of trips.
	Kieu et al. [5]	Clustering trips first based on locations of alighting stops, then based on the location of boarding stops, and thirdly based on times of the boarding transactions.
	Sun and Axhausen [19]	Decomposing data to investigate the interactions between the time of day, passenger type, and origin and destination zones.
	Manley et al. [20]	Investigating spatial and temporal regularity over different transit modes.
	Yu and He [21]	Using heat maps to discover spatial and temporal demand of bus trips.
	Briand et al. [23]	Modelling time in a continuous space to investigate passenger exchanges between clusters over time.