Spatiotemporal Characteristics of Subway Travel by the Elderly Based on Activity Space: A Case Study of Kunming

Abstract

With the aging of society, the travel activities of the elderly, as a vital part of resident travel, have become the focus of transportation management in most cities. The widespread application of big data has enabled travel behavior to be analyzed in more detail, with the results revealing actual travel patterns and helping to gain an in-depth understanding of the daily travel of residents. In studies on travel patterns, several methods can be used to analyze the daily activity patterns of the elderly by combining big data with the theory of activity space. However, studies on the internal disparity in the travel behavior of the elderly remain limited. Hence, we conducted a comparative analysis of the travel behavior of age groups within the elderly from the perspective of activity space based on the smart card data of the Kunming subway system. In the analysis, we first compared the basic travel behavior of the elderly and nonelderly. Based on the findings, we divided the elderly who took the subway into 60-69- and over-70-year-old groups. Second, we compared the travel behavior and activity spaces of these two groups using a statistical and spatial analysis approach. The results showed significant differences between the elderly and nonelderly groups, the 60-69-year-old group, and the over-70-year-old group. (1) We found spatiotemporal differences in travel behavior between the elderly and nonelderly. Compared to the nonelderly group, the elderly group was less mobile. Their single-subway travel duration and frequency were lower, and they traveled more during the early peak hours. Their activity range was relatively concentrated in the city center, and their travel purposes showed a stronger orientation toward leisure and medical needs. (2) With increasing age, the elderly were less mobile, and their dependence on public transport increased. In detail, the over-70-year-old group had a shorter travel duration as well as a smaller activity space, whereas their travel frequency and number of visited stations were higher than those of the primary age group. Compared with the 60-69-year-old group, the daily activity pattern of the elderly over 70 years old could be summarized as being within a smaller activity space and higher in frequency. (3) The distribution of activity spaces of the two elderly groups was similar to each other, both in areas along metro lines 1, 2, and 3, without line 6. It indicated that the daily activities of the elderly mainly occur in central urban areas with high population densities. Regarding differences, the activity spaces of those over 70 years old were more concentrated in the densely inhabited districts along metro line 3, whereas the activity spaces of the 60-69-year-old group spread to low-density areas in the south and east. These findings may imply that factors, such as the built environment, largely restrict the subway travel of older people. In other words, their daily activities rely on facilities and transit more heavily. In conclusion, our results reveal the subway travel behavior and daily activity patterns of different-aged elderly groups, which verify the feasibility of smart card data in activity space analysis. Additionally, our study provides ideas for urban planning and transportation management in the aging era to promote social space equity.

Keywords

• elderly group
• transit use
• activity space theory
• individual trajectory
• kunming