An empirical test for cellular automaton models of traffic flow

TL;DR

This paper empirically tests various cellular automaton models of traffic flow against detailed single-vehicle data, categorizing models based on their level of agreement with real-world observations.

Contribution

It introduces a microscopic test scenario to evaluate cellular automaton models and classifies their accuracy levels, providing insights into model validity and traffic interactions.

Findings

Some models fail to reproduce key empirical observations.

Certain models align well on a macroscopic level with real data.

A few models accurately replicate microscopic traffic behavior.

Abstract

Based on a detailed microscopic test scenario motivated by recent empirical studies of single-vehicle data, several cellular automaton models for traffic flow are compared. We find three levels of agreement with the empirical data: 1) models that do not reproduce even qualitatively the most important empirical observations, 2) models that are on a macroscopic level in reasonable agreement with the empirics, and 3) models that reproduce the empirical data on a microscopic level as well. Our results are not only relevant for applications, but also shed new light on the relevant interactions in traffic flow.