An Overview of Agent-based Traffic Simulators

TL;DR

This paper reviews agent-based traffic simulators, highlighting their suitability for modeling individual behaviors and addressing key mobility challenges like social dilemmas, connectivity, and new mobility forms.

Contribution

It provides a comprehensive overview of existing agent-based traffic simulators, assessing their features and identifying gaps for future development.

Findings

Simulators effectively model heterogeneous individual travel behaviors.

Identified gaps in simulator functionalities for advanced mobility research.

Agent-based models are promising for sustainable mobility studies.

Abstract

Individual traffic significantly contributes to climate change and environmental degradation. Therefore, innovation in sustainable mobility is gaining importance as it helps to reduce environmental pollution. However, effects of new ideas in mobility are difficult to estimate in advance and strongly depend on the individual traffic participants. The application of agent technology is particularly promising as it focuses on modelling heterogeneous individual preferences and behaviours. In this paper, we show how agent-based models are particularly suitable to address three pressing research topics in mobility: 1. Social dilemmas in resource utilisation; 2. Digital connectivity; and 3. New forms of mobility. We then explain how the features of several agent-based simulators are suitable for addressing these topics. We assess the capability of simulators to model individual travel behaviour, discussing implemented features and identifying gaps in functionality that we consider important.