Centralized Decision-Making for Platooning By Using SPaT-Driven Reference Speeds

TL;DR

This paper presents a centralized, V2X and SPaT data-driven control strategy for urban vehicle platooning that significantly reduces fuel consumption and improves traffic flow through optimized trajectory planning and communication.

Contribution

It introduces a novel centralized MPC-based approach utilizing real-time SPaT data for fuel-efficient urban platooning with dynamic platoon management.

Findings

Fuel savings up to 41.2% in simulations

Smoother traffic flow and fewer stops

Enhanced intersection throughput

Abstract

This paper introduces a centralized approach for fuel-efficient urban platooning by leveraging real-time Vehicle- to-Everything (V2X) communication and Signal Phase and Timing (SPaT) data. A nonlinear Model Predictive Control (MPC) algorithm optimizes the trajectories of platoon leader vehicles, employing an asymmetric cost function to minimize fuel-intensive acceleration. Following vehicles utilize a gap- and velocity-based control strategy, complemented by dynamic platoon splitting logic communicated through Platoon Control Messages (PCM) and Platoon Awareness Messages (PAM). Simulation results obtained from the CARLA environment demonstrate substantial fuel savings of up to 41.2%, along with smoother traffic flows, fewer vehicle stops, and improved intersection throughput.