Date of Award

5-2023

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Computer Engineering and Sciences

First Advisor

Ivica Kostanic

Second Advisor

Josko Zec

Third Advisor

Veton Z. Kepuska

Fourth Advisor

Nasri Nesnas

Abstract

Understanding patterns of human mobility plays a vital role in urban planning, traffic management, disease control, environmental impact evaluation, provisioning of services by both public and private enterprise and other areas of human activity. In this thesis, the human mobility patterns are studied using crowd sourced cellular data. The study characterizes human mobility through a meaningful set of mobility parameters. Each parameter is clearly defined, extracted from the available data, and described using statistical modeling tools. The parameters are evaluated at different time scales. It has been determined that despite its apparent randomness on the individual level, human mobility on the population scale exhibits a high degree of consistency and predictability. The set used for the study consists of records for 130,000 individuals living in the Atlanta metropolitan area. The data provides sufficient time and space domain sampling for each individual to guarantee statistical significance of the results. The overall time span of the data is 30 days.

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