Cellular Automata Simulating Experimental Properties of Traffic Flows

TL;DR

This paper introduces a discrete 1D cellular automaton model for traffic flow that is simple, fast, and capable of replicating experimental stop-and-go traffic patterns, with a deterministic instability mechanism.

Contribution

It presents a new cellular automaton model for traffic flow that aligns with empirical data and shares a deterministic instability mechanism with existing models.

Findings

Model replicates experimental traffic features

Easily calibrated to real data

Displays deterministic instability mechanism

Abstract

A model for 1D traffic flow is developed, which is discrete in space and time. Like the cellular automaton model by Nagel and Schreckenberg [J. Phys. I France 2, 2221 (1992)], it is simple, fast, and can describe stop-and-go traffic. Due to its relation to the optimal velocity model by Bando et al. [Phys. Rev. E 51, 1035 (1995)], its instability mechanism is of deterministic nature. The model can be easily calibrated to empirical data and displays the experimental features of traffic data recently reported by Kerner and Rehborn [Phys. Rev. E 53, R1297 (1996)].