Exploring Travel Pattern Variability of Public Transport Users Through Smart Card Data: Role of Gender and Age

A better understanding of travel pattern variability is important for public transport (PT) authorities to improve passenger experience and service provision. Although many studies have examined the travel pattern variability of PT users, these studies are often limited to a short analysis period or to only one dimension of travel behavior. In addition, there is limited knowledge of how the demographic characteristics of PT users are associated with their travel pattern variability. To address these limitations, we develop a novel measure that simultaneously considers multiple dimensions of travel behavior to quantify the intrapersonal variability in weekly PT usage. Moreover, we examine interpersonal variability by identifying clusters of users who share similar weekly profiles. Based on smart card transaction data for 52 weeks and an anonymous cardholder database (including age and gender) from Shizuoka, Japan, we analyze the intrapersonal and interpersonal variability in weekly PT usage as well as the role of gender and age in travel pattern variability. The results indicate that gender and age play an important role in the travel pattern variability of PT users. Female users exhibit higher intrapersonal variability than their male counterparts. Weekly patterns are the most diverse for users aged 70 or over, followed by the users aged 65-69. Regarding interpersonal variability, we identify five clusters of users, each characterized by a distinct weekly profile and associated with certain age and gender.

Automated summary

Understanding the variability of travel patterns is crucial for improving public transport services. In this study, we developed a novel measure that considers multiple dimensions of travel behavior to quantify intrapersonal and interpersonal variability in weekly public transport usage. Analyses based on smart card data and an anonymous cardholder database revealed the influence of gender and age on travel pattern variability.