Design and Experimental Validation of a Distributed Interaction Protocol for Connected Autonomous Vehicles at a Road Intersection
Journal article, 2019

This paper presents a fully distributed interaction protocol for connected self-driving cars negotiating the access a traffic junction. The vehicles coordination has been reformulated as an equivalent virtual platoon control problem. The desired vehicles spacing within the platoon is chosen so to avoid the side and rear-end collisions and is controlled by a cooperative non-linear control algorithm, based on potential functions. The asymptotic stability of the closed-loop system has been analytically proved by leveraging the LaSalle's Invariance Principle. The analysis of the convergence rate has resulted in an effective tuning tool ensuring that the desired formation is achieved before vehicles reach the intersection. Most notably, results from an in-vehicle experimental validation are presented. The experiments were carried out on three self-driving cars connected through a V2V communication infrastructure based on the IEEE 802.11p protocol. The experimental results confirm the theoretical analysis and reveal the effectiveness of the control approach for autonomously and safely negotiating a generic traffic junction.

Autonomous traffic intersection

multi-agent systems

intelligent transportation systems

in-vehicle experimental test

vehicle-to-vehicle (V2V) communication

distributed control system

cooperative autonomous driving

Author

Marco Di Vaio

Universita degli Studi di Napoli Federico II

Paolo Falcone

Chalmers, Electrical Engineering, Systems and control, Mechatronics

Robert Hult

Chalmers, Electrical Engineering, Systems and control, Mechatronics

Alberto Petrillo

Universita degli Studi di Napoli Federico II

A. Salvi

Universita degli Studi di Napoli Federico II

S. Santini

Universita degli Studi di Napoli Federico II

IEEE Transactions on Vehicular Technology

0018-9545 (ISSN)

Vol. 68 10 9451-9465 8790807

Subject Categories

Vehicle Engineering

Robotics

Control Engineering

DOI

10.1109/TVT.2019.2933690

More information

Latest update

11/22/2019