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This study used activity-travel diary data to analyze the time-of-day dynamics of interpersonal contacts and examined their complex relationship with other activity-travel time allocation and personal accessibility dynamics. In total, 2,942 activity-travel diaries from 1,471 participants were used to identify five unique patterns of daily human interaction, with latent class analysis. Latent classes for the time-of-day dynamics of time allocation to activities and the time-of-day dynamics of experienced business employment density are also estimated independently and correlated with the five human interaction patterns. The analysis used a form of multinomial regression model (also called a three-step model in latent class analysis) to examine these relationships and to test the association of human interaction patterns and external explanatory variables simultaneously. Strong correlation was found between interpersonal …