Cellular automata models of traffic flow along a highway containing a junction

TL;DR

This paper explores advanced cellular automaton models for highway traffic flow, including junctions and realistic driver behaviors, revealing how disorderness and speed limits can improve junction efficiency.

Contribution

It introduces a slow-to-start rule and analyzes their effects on traffic flow at highway junctions, providing new insights into traffic dynamics modeling.

Findings

Disorderness and speed limits enhance junction efficiency.

Slow-to-start behavior affects queue length at entry points.

Model generalizations improve realism of traffic simulations.

Abstract

We examine various realistic generalizations of the basic cellular automaton model describing traffic flow along a highway. In particular, we introduce a {\em slow-to-start} rule which simulates a possible delay before a car pulls away from being stationary. Having discussed the case of a bare highway, we then consider the presence of a junction. We study the effects of acceleration, disorderness, and slow-to-start behavior on the queue length at the entrance to the highway. Interestingly, the junction's efficiency is {\it improved} by introducing disorderness along the highway, and by imposing a speed limit.