An Urban Mobility Model with Buildings Involved

Abstract

Urban Mobility Models (UMMs) are fundamental tools for estimating the population in urban sites and their spatial movements over time. Most existing UMMs were developed primarily in 2D. However, we argue that people’s movements and living patterns involve 3D space, i.e., buildings, which can heavily affect the accuracy of UMMs. In this article, we for the first time conduct a comprehensive study on the impacts of buildings on human movements and the effect on UMMs. We innovatively capture the impacts by developing a Semi-absorbing Urban Mobility model (SUM) and theoretically prove its properties on its difference from that of previous UMMs. We also show that calibrating our original SUM may need a large number of parameters. As such, we develop two SUM extensions with a substantially reduced number of parameters, making calibration practical. Our evaluation also demonstrates that, as a basis for supporting mobile applications in an intracity and hourly scale, the SUM is far superior to previous UMMs. In a case study, we also show that the performance of the resource allocation scheme in a cellular network substantially improves by using SUM, with a reduction in the packet loss probability of 3.19 times.