# Intelligent Transportation Systems to Mitigate Road Traffic Congestion

arXiv: https://arxiv.org/abs/2106.02315 · HTML: https://mlsanity.com/paper/2106.02315/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 13 references that are in the map.
- First posted on arXiv 4 Jun 2021.

## Builds on (most cited first, 1 of 1)

- [Intelligent Coordination among Multiple Traffic Intersections Using Multi-Agent Reinforcement Learning](https://mlsanity.com/paper/1912.03851/) (2019)

## Abstract (arXiv)

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.