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Cyclic Modulation Control of Multi-Conflict Connected Automated Traffic

Fan Pu, Zihao Li, Sivakumar Rathinam, Minghui Zheng, Yang Zhou

TL;DR

The paper tackles coordinating connected automated vehicles at multi-conflict intersections lacking fixed geometric constraints. It introduces CMAT, a geometry-agnostic framework that uses phantom micro-signals to form demand-responsive platoons and a unified cycle-based scheduling on a directed conflict graph, enabling conflict resolution at the platoon level while maintaining high throughput. The approach is formalized as a mixed-integer linear program with models M1 and M2 to optimize cycle length, platoon sizes, and sequencing, ensuring safety and feasibility across varying demand, including oversaturated scenarios. Numerical experiments across unsignalized, four-leg, shared-lane, and connected intersections show substantial capacity gains (often >50–80%) and large reductions in average delay compared with state-of-the-art CAV coordination and traditional signal timing, demonstrating a scalable, adaptable solution for high-throughput, safe automated traffic.

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.

Cyclic Modulation Control of Multi-Conflict Connected Automated Traffic

TL;DR

The paper tackles coordinating connected automated vehicles at multi-conflict intersections lacking fixed geometric constraints. It introduces CMAT, a geometry-agnostic framework that uses phantom micro-signals to form demand-responsive platoons and a unified cycle-based scheduling on a directed conflict graph, enabling conflict resolution at the platoon level while maintaining high throughput. The approach is formalized as a mixed-integer linear program with models M1 and M2 to optimize cycle length, platoon sizes, and sequencing, ensuring safety and feasibility across varying demand, including oversaturated scenarios. Numerical experiments across unsignalized, four-leg, shared-lane, and connected intersections show substantial capacity gains (often >50–80%) and large reductions in average delay compared with state-of-the-art CAV coordination and traditional signal timing, demonstrating a scalable, adaptable solution for high-throughput, safe automated traffic.

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.
Paper Structure (9 sections, 2 theorems, 28 equations, 10 figures, 1 table)

This paper contains 9 sections, 2 theorems, 28 equations, 10 figures, 1 table.

Table of Contents

  1. Introduction
  2. Motivating Example
  3. Problem description and mathematical formulation
  4. Numerical experiments
  5. Unsignalized single-conflict case
  6. Four-leg intersection with fully dedicated lanes
  7. Four-leg intersection with shared lanes
  8. Connected intersections with shared lanes
  9. Conclusions

Key Result

Proposition 1

Cycle length $C$ is a common multiple of the arrival headway for each unmuted movement, that is, $C=k_\mathbf{p}/q_\mathbf{p}$ for all $\mathbf{p}\in\mathbf{P}:1/q_\mathbf{p}\le\tau^{*}$, where $k_\mathbf{p}\in\mathbb{Z}^+$ is a positive integer.

Figures (10)

  • Figure 1: Comparison of control strategies in the single-conflict scenario
  • Figure 2: Illustration of functions used in the motivating example
  • Figure 3: Solution comparison in the multi-conflict scenario.
  • Figure 4: Illustration of the CMAT problem for a four-leg intersection (colored arrows indicate different movements.)
  • Figure 5: Illustration of decision variables
  • ...and 5 more figures

Theorems & Definitions (6)

  • Proposition 1
  • Proof
  • Remark 1
  • Proposition 2
  • Proof
  • Remark 2