Modeling the Distribution of Human Mobility Metrics with Online Car-Hailing Data—An Empirical Study in Xi’an, China

Modeling the distribution of daily and hourly human mobility metrics is beneficial for studying underlying travel patterns. In previous studies, some probability functions were employed in order to establish a base research. However, selection most suitable still challenging task. this paper, we focus on modeling distributions distance, time, speed. The trip data are fitted with several candidate distributions, best one selected based Bayesian information criterion. A case study online car-hailing Xi’an, China, presented demonstrate evaluate model fit. results indicate that distance time tend follow Gamma distribution, speed can be approximated by Burr distribution. These contribute better understanding patterns