Data Driven Validation Framework for Multi-agent Activity-based Models

TL;DR

This paper introduces VALFRAM, a six-step validation framework that uses real-world data to assess the accuracy of activity-based transport models by comparing their outputs with actual travel diaries and origin-destination data.

Contribution

The paper presents a novel, systematic validation framework specifically designed for activity-based models, filling a gap in model validation techniques.

Findings

VALFRAM effectively evaluates activity-based models against real-world data.

The framework is validated on three real-world transport models.

Results demonstrate the framework's usefulness in model validation.

Abstract

Activity-based models, as a specific instance of agent-based models, deal with agents that structure their activity in terms of (daily) activity schedules. An activity schedule consists of a sequence of activity instances, each with its assigned start time, duration and location, together with transport modes used for travel between subsequent activity locations. A critical step in the development of simulation models is validation. Despite the growing importance of activity-based models in modelling transport and mobility, there has been so far no work focusing specifically on statistical validation of such models. In this paper, we propose a six-step Validation Framework for Activity-based Models (VALFRAM) that allows exploiting historical real-world data to assess the validity of activity-based models. The framework compares temporal and spatial properties and the structure of activity schedules against real-world travel diaries and origin-destination matrices. We confirm the usefulness of the framework on three real-world activity-based transport models.