An Entropy-Based Approach for Origin and Destination Activity Flow Estimation using Crowdsourced Data

Abstract

We developed an approach to estimate OD flows, including activities performed at destinations, using crowdsourced Google Popular Times data and mobile spatial statistics on population presence. Our method enables us to understand the activities that people engage in after their journey, enabling insights into demand sensitivities to urban activities. The study uses data from Kyoto, Japan with a focus on the Kyoto Station area. Results show that GPT data effectively estimate the time-varying population in each zone. Further analysis illustrates the origin of trips, and the activities engaged in.