Optimised Traffic Flow at a Single Intersection: Traffic Responsive signalisation

TL;DR

This paper introduces a stochastic model for urban intersection traffic, utilizing probabilistic cellular automata to optimize traffic light signalization through adaptive algorithms that minimize total delay.

Contribution

It presents new traffic responsive signalization algorithms based on cut-off queue length and density, improving traffic flow at intersections.

Findings

Optimized traffic signalization reduces total delay at intersections.

Adaptive algorithms outperform fixed-time schemes in simulations.

Probabilistic cellular automata effectively model vehicular dynamics.

Abstract

We propose a stochastic model for the intersection of two urban streets. The vehicular traffic at the intersection is controlled by a set of traffic lights which can be operated subject to fix-time as well as traffic adaptive schemes. Vehicular dynamics is simulated within the framework of the probabilistic cellular automata and the delay experienced by the traffic at each individual street is evaluated for specified time intervals. Minimising the total delay of both streets gives rise to the optimum signalisation of traffic lights. We propose some traffic responsive signalisation algorithms which are based on the concept of cut-off queue length and cut-off density.