Revealing sequential activity-travel patterns and spatial structures among older and younger adults from smart card data

Individual routine activities and travel often exhibit spatiotemporal and purposeful sequential patterns. However, limited studies have examined sequential activity-travel patterns that simultaneously incorporate movements and their underlying purposes, as well as spatial structures formed by people’s sequential activities. Understanding these patterns offers a clearer picture of how individuals systematically organize and unfold their routine activities, revealing the connections between different spatial locations by sequences of people’s activities. This study proposes an analytical framework to effectively uncover sequential activity-travel patterns and their spatial structures from the large-scale mobility dataset. Using Beijing as a case study, we first infer older and younger adults’ trip purposes by rule-based and topic-modeling approaches using smart card data. Then, we examine frequent sequential activity-travel patterns based on detected activity and spatial activity sequences using the CM-SPADE algorithm. The study reveals frequent activity sequences, spatial activity sequences, and their corresponding spatial structures across different urban areas, reflecting representative mobility patterns of older and younger adults. The findings indicate that older adults exhibit diverse frequent activity-travel patterns, and complex spatial structures of frequent interactions motivated by daily activities, compared to younger adults. This study also contributes to identifying potential multi-activity attractive centers, key interaction hubs, and their functional spatial structures of interactions motivated by daily activities. By uncovering the mechanisms of urban mobility regularity and the spatiotemporal structure of daily urban life, this research provides valuable insights for efficient and tailored urban transportation planning.