Quantitative understanding of human movement behaviors would provide helpful insights into the mechanisms of many socioeconomic phenomena. In this paper, we investigate human mobility patterns through analyzing taxi-trace datasets collected from five metropolitan cities in two countries. We focus on three statistics for each dataset: the displacement of each occupied trip, the duration of each occupied trip, and the time interval between successive occupied trips by the same taxi (interevent time). The results indicate that the displacement distributions of human travel by taxi tend to follow exponential laws in two displacement ranges rather than power laws; the trip duration distributions can be approximated by log-normal distributions; the interevent time distributions can be well characterized by log-normal bodies followed by power law tails. For each considered measure, the rescaled distributions of all cities collapsed into a master curve. These results provide empirical evidence supporting the common regularity of intra-city human mobility. Moreover, we show that airport locations could play a role in explaining the spikes of displacement distributions of taxi trips in certain cities.