Intelligent Transportation Systems to Mitigate Road Traffic Congestion

TL;DR

This paper discusses the development of intelligent transportation systems, particularly multi-agent models, that significantly reduce traffic congestion and improve emergency vehicle response times through microscopic simulation.

Contribution

It introduces two novel traffic management models utilizing multi-agent systems and demonstrates their effectiveness with a SUMO-JADE simulation tool.

Findings

50% reduction in average time delay

Improved emergency vehicle response times

Enhanced overall traffic flow efficiency

Abstract

Intelligent transport systems have efficiently and effectively proved themselves in settling up the problem of traffic congestion around the world. The multi-agent based transportation system is one of the most important intelligent transport systems, which represents an interaction among the neighbouring vehicles, drivers, roads, infrastructure and vehicles. In this paper, two traffic management models have been created to mitigate congestion and to ensure that emergency vehicles arrive as quickly as possible. A tool-chain SUMO-JADE is employed to create a microscopic simulation symbolizing the interactions of traffic. The simulation model has showed a significant reduction of at least 50% in the average time delay and thus a real improvement in the entire journey time.