---
title: "Alleviating Road Traffic Congestion with Artificial Intelligence"
authors:
  - "Guni Sharon"
doi: "10.24963/ijcai.2021/704"
url: "https://ijcai.org/proceedings/2021/704"
pdf: "https://ijcai.org/proceedings/2021/0704.pdf"
venue: "Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence"
year: 2021
pages: "4965-4969"
track: "Early Career"
keywords:
  - "Machine Learning Applications: Applications of Reinforcement Learning"
  - "Agent-based and Multi-agent Systems: Coordination and Cooperation"
  - "Multidisciplinary Topics and Applications: Computational Sustainability"
  - "Multidisciplinary Topics and Applications: Transportation"
---

# Alleviating Road Traffic Congestion with Artificial Intelligence

Guni Sharon

*Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence*, pages 4965-4969. DOI: [10.24963/ijcai.2021/704](https://doi.org/10.24963/ijcai.2021/704)

## Abstract

This paper reviews current AI solutions towards road traffic congestion alleviation. Three specific AI technologies are discussed, (1) intersection management protocols for coordinating vehicles through a roads intersection in a safe and efficient manner, (2) road pricing protocol that induce optimized traffic flow, and (3) partial or full autonomous driving that can stabilize traffic flow and mitigate adverse traffic shock waves. The paper briefly presents the challenges affiliated with each of these applications along with an overview of state-of-the-art solutions. Finally, real-world implementation gaps and challenges are discussed.