Statistical mechanism of passenger mobility behaviors for different transportations

Abstract

<jats:p> Passengers’ boarding time interval is of great significance for analysis of collective mobility behaviors. In this paper, we empirically investigate the boarding time interval of mobility behaviors based on three large-scale reservation records of passengers traveling by three different types of transportation from a travel agency platform, namely airplane, intercity bus and car rental. The statistical results show that similar properties exist in the passengers’ mobility behaviors, for example, there are similar burstiness [Formula: see text] and memory [Formula: see text] for different time interval distribution, which indicates that the passengers’ mobility behaviors are periodical. Furthermore, we present a probability model to regenerate the empirical results by assuming that the passengers’ next boarding time interval will generate between a short time of 1–7 days with probability [Formula: see text] and a random long time with probability [Formula: see text]. The simulation results show that the presented model can reproduce the burstiness and memory effect of the boarding time interval when [Formula: see text] for three empirical datasets, which suggests the periodical behaviors with the probability [Formula: see text]. This work helps in deeply understanding the regularity of human mobility behaviors. </jats:p>

Features of intercity bus passenger group mobility behaviors in the context of smart tourism

“…Sui et al [15] conducted a spatiotemporal analysis of passengers' travel behaviors based on bus smart card data in Brisbane, Australia. According to the booking records on the website, Han et al [16] analyzed the travel inter-event time of passengers who take different transportation, then carried out modeling and simulation.…”