Examining dual exposure to traffic congestion and in-vehicle crowding among senior and regular cardholders using smart card data

In urban travel, traffic congestion often results in prolonged travel times, while in-vehicle crowding causes physical discomfort. Bus passengers uniquely face dual exposure to both congestion (from shared road networks) and crowding (from shared vehicle space), which compounds health risks and undermines sustainable transport goals. Despite this, few studies examine these concurrent exposures or the socio-demographic disparities in who bears this burden, particularly critical for vulnerable populations like senior groups who may face disproportionate impacts. Using Beijing bus smart card data, we measure congestion and crowding levels to identify adverse travel patterns and infer passengers' home locations. We then apply statistical and random forest models to examine how socio-demographic characteristics shape exposure to these adverse conditions across different urban areas. The study reveals the spatial-temporal dynamics of congestion and crowding, the daily rhythms of adverse travel flow across urban spaces, and the socio-demographic characteristic disparities that shape differential exposures among senior and regular cardholders. The findings indicate that congestion concentrates in urban centers and suburban hubs during peak hours, while crowding tends to persist throughout the day on suburban-urban corridors. Urban residents experience more congestion but less crowding than suburban and rural residents. Senior cardholders experience shorter durations but higher rates of adverse conditions than regular cardholders. By revealing dual exposure patterns across space, time, and demographics, this study identifies where and when interventions are needed to reduce congestion for urban commuters and crowding for suburban riders.