Synthetic Sweden Mobility (SySMo) Model Documentation
Preprint, 2022

This document describes a decision support framework using a combination of several state-of-the-art computing tools and techniques in synthetic information systems, and large-scale agent-based simulations. In this work, we create a synthetic population of Sweden and their mobility patterns that are composed of three major components: population synthesis, activity generation, and location assignment. The document describes the model structure, assumptions, and validation of results.

activity-based modeling

machine learning

agent-based modeling

synthetic population

Author

Çaglar Tozluoglu

Chalmers, Space, Earth and Environment, Physical Resource Theory

Swapnil Vilas Dhamal

Chalmers, Space, Earth and Environment, Physical Resource Theory

Yuan Liao

Chalmers, Space, Earth and Environment, Physical Resource Theory

Sonia Yeh

Chalmers, Space, Earth and Environment, Physical Resource Theory

Frances Sprei

Chalmers, Space, Earth and Environment, Physical Resource Theory

Devdatt Dubhashi

Chalmers, Computer Science and Engineering (Chalmers), Data Science and AI

Madhav Marathe

University of Virginia

Christopher Barrett

University of Virginia

The new future of mobility: Using a Synthetic Sweden to study transition pathways to autonomous, shared, and electromobility

Formas (2018-01768), 2019-01-01 -- 2023-11-30.

Subject Categories

Other Computer and Information Science

Transport Systems and Logistics

Driving Forces

Sustainable development

Areas of Advance

Transport

More information

Latest update

2/24/2023