Cyclic Modulation Control of Multi-Conflict Connected Automated Traffic

TL;DR

This paper introduces CMAT, a unified control framework for multi-conflict intersections that dynamically coordinates connected automated vehicles to improve safety, reduce delays, and increase throughput without manual tuning.

Contribution

CMAT is a geometry-agnostic, micro-phase based control method that optimizes vehicle coordination at complex intersections using mixed-integer linear programming.

Findings

Substantial delay reductions compared to existing methods.

Significant throughput improvements over traditional signals.

Effective coordination across various intersection complexities.

Abstract

Multi-conflict traffic is ubiquitous. Connected Automated Vehicles (CAVs) offer unprecedented opportunities to enhance safety, reduce emissions, and increase throughput through precise coordination and automation. However, existing CAV strategies remain confined to specialized scenarios, such as highway on-ramp merging or single-lane roundabouts, and traditional traffic signals sacrifice efficiency for safety via rigid phasing and all-red intervals. In this paper, we present Cyclic Modulation Control of Multi-Conflict Connected Automated Traffic (CMAT), a unified, geometry-agnostic framework that embeds each conflict point into a repeating sequence of "micro-phases". Vehicles dynamically form platoons with demand-responsive sizes and negotiate time slots for occupying conflict points, enabling collision-free traversal and high intersection utilization. CMAT aims to minimize delay, guarantee safety, and accommodate arbitrary merging, diverging, and crossing patterns without manual retuning. We formalize CMAT as a mixed-integer linear programming model constructed on a directed graph abstracted from the physical intersection layout. The performance of CMAT is evaluated across a suite of multi-conflict tests, including simple two-way crossings, four-leg intersections, complex connected intersections. The results demonstrate substantial reductions in delay and significant throughput improvements compared with state-of-the-art CAV coordination methods and traditional signal timing strategies.