Work

Population spatialization for route planning in activity-based models

Year: 2025

Type: article

Abstract: Activity-based and agent-based models are overcoming numerous limitations inherent in the trip-based model. However, this transition is unveiling new challenges that can influence the modeling outcomes. One notable obstacle in embracing activity-based models is the requirement for detailed, high-resolution input data at a disaggregate level, which are particularly important but difficult to gather. This article concentrates on spatializing populations and disaggregating travel data using sampling and interpolation methods. The Python-based toolkit developed herein is applied to a case study involving the population generation of Dresden in Germany. The outcome of the applied method comprises more than 2000 daily activity schedules with their respective points for each activity location. These results show the toolkit capabilities regarding population spatialization for activity-based models.

Source: Transportation research procedia

DOI: 10.1016/j.trpro.2025.04.010

Authors: Bladimir Toaza, Domokos Esztergár-Kiss

Institution: Budapest University of Technology and Economics

Language: English

Topic: Transportation Planning and Optimization

Subfield: Transportation

Field: Social Sciences

Domain: Social Sciences

SDG: Sustainable cities and communities

Open Access status: diamond

Funders: Hungarian Scientific Research Fund, Nemzeti Kutatási és Technológiai Hivatal, Nemzeti Kutatási Fejlesztési és Innovációs Hivatal