A Roadside Unit for Infrastructure Assisted Intersection Control of Autonomous Vehicles

TL;DR

This paper presents a cost-effective roadside unit system for intelligent intersection control of autonomous vehicles, demonstrating significant reductions in acceleration and braking to enhance safety and fuel efficiency.

Contribution

It introduces a novel infrastructure-assisted intersection control algorithm implemented in both simulation and real-world scenarios, showing substantial improvements over traditional methods.

Findings

Up to 75.35% reduction in acceleration and braking at intersections

Significant fuel efficiency improvements for electric and gas vehicles

Proof-of-concept for infrastructure-assisted traffic management

Abstract

Recent advances in autonomous vehicle technologies and cellular network speeds motivate developments in vehicle-to-everything (V2X) communications. Enhanced road safety features and improved fuel efficiency are some of the motivations behind V2X for future transportation systems. Adaptive intersection control systems have considerable potential to achieve these goals by minimizing idle times and predicting short-term future traffic conditions. Integrating V2X into traffic management systems introduces the infrastructure necessary to make roads safer for all users and initiates the shift towards more intelligent and connected cities. To demonstrate our control algorithm, we implement both a simulated and real-world representation of a 4-way intersection and crosswalk scenario with 2 self-driving electric vehicles, a roadside unit (RSU), and a traffic light. Our architecture reduces acceleration and braking through intersections by up to 75.35%, which has been shown to minimize fuel consumption in gas vehicles. We propose a cost-effective solution to intelligent and connected intersection control to serve as a proof-of-concept model suitable as the basis for continued research and development. Code for this project is available at https://github.com/MMachado05/REU-2024.