A hierarchical cellular automaton model of distributed traffic signal control

TL;DR

This paper presents a hierarchical cellular automaton model for distributed traffic signal control, aiming to reduce vehicle delays through self-organizing strategies in various traffic conditions.

Contribution

It introduces a novel hierarchical cellular automaton framework for traffic signal control that outperforms existing back pressure algorithms.

Findings

HCA-based control reduces vehicle delays more effectively.

The model performs well across different traffic densities.

Simulation results outperform current state-of-the-art methods.

Abstract

This paper introduces a hierarchical cellular automaton (HCA)model for simulation of distributed self-organizing control of traffic signals at intersections in road network. The proposed HCA consists of three hierarchy levels that describe the movement of particular vehicles, occupancy of traffic lanes, and signal phases at intersections. Update rule of the HCA was designed to control traffic signals and minimize delays of vehicles in the road network. The introduced update rule takes into account states of cells from different hierarchy levels of the HCA that represent neighboring traffic lanes and intersections. Simulation experiments were conducted for a wide range of traffic conditions - from free flow to saturated traffic in two scenarios: anhattan-like grid road network, and arterial road. Results of the simulations show that the proposed HCA-based traffic control strategy achieves better effectiveness in comparison with the state-of-the-art back pressure algorithm.