Work

AUTODRAITEC: An Infrastructure-Based AUTOnomous DRiving System Using Artificial Intelligence and TEleCommunication Technologies

Year: 2024

Type: conference-paper

Abstract: This paper introduces AUTODRAITEC, a novel AI-based system that is deployed on the road infrastructure to control the driving of Connected and Autonomous Vehicles (CAVs). For this purpose, we present a convincing proof of concept that demonstrates the effectiveness of our solution. The system deploys a hybrid machine learning approach comprised of a supervised learning classifier to characterize the behaviors of human drivers, with a deep reinforcement learning policy to provide speed recommendations for CAVs. This system is implemented using perception sensors and an industrial computer (IPC), which are intended to be deployed on the road infrastructure. Using a 1:18 scale testbed that faithfully replicates real-world driving scenarios, we demonstrate that AUTODRAITEC improves driving safety and efficiency while preserving the traffic flow rate.

Source: International Joint Conference on Artificial Intelligence

DOI: 10.24963/ijcai.2024/1013

Authors: Zine el abidine Kherroubi, Fouzi Boukhalfa, Thierry Lestable, Carlos-Faouzi Bader

Institution: Technology Innovation Institute

Language: English

Topic: Traffic control and management

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Sustainable cities and communities

Open Access status: bronze

OpenAlex ID: W4401023490