Influences of Temporal Factors on GPS-based Human Mobility Lifestyle

TL;DR

This study investigates how specific temporal factors influence human mobility patterns using GPS data from Japanese smartphone users, revealing habitual behaviors and their variations across different days.

Contribution

The paper introduces a model with 13 temporal patterns to analyze GPS-based mobility and applies regression to identify influential temporal factors.

Findings

People tend to maintain mobility habits on Thursdays and mid-month days.

Mobility habits decrease on Fridays.

Temporal factors significantly influence human mobility patterns.

Abstract

Analysis of human mobility from GPS trajectories becomes crucial in many aspects such as policy planning for urban citizens, location-based service recommendation/prediction, and especially mitigating the spread of biological and mobile viruses. In this paper, we propose a method to find temporal factors affecting the human mobility lifestyle. We collected GPS data from 100 smartphone users in Japan. We designed a model that consists of 13 temporal patterns. We then applied a multiple linear regression and found that people tend to keep their mobility habits on Thursday and the days in the second week of a month but tend to lose their habits on Friday. We also explained some reasons behind these findings.