A Provably Correct MPC Approach to Safety Control of Urban Traffic Networks

TL;DR

This paper introduces a provably correct model predictive control method for urban traffic networks that ensures safety over long periods by using a robust invariant set as a terminal constraint.

Contribution

The paper presents a novel MPC approach that guarantees safety in urban traffic networks through the use of a robust controlled invariant set, extending the reliability of traffic management strategies.

Findings

Guarantees safety over long time horizons

Uses a robust invariant set as terminal constraint

Demonstrates effectiveness with an illustrative example

Abstract

Model predictive control (MPC) is a popular strategy for urban traffic management that is able to incorporate physical and user defined constraints. However, the current MPC methods rely on finite horizon predictions that are unable to guarantee desirable behaviors over long periods of time. In this paper we design an MPC strategy that is guaranteed to keep the evolution of a network in a desirable yet arbitrary -safe- set, while optimizing a finite horizon cost function. Our approach relies on finding a robust controlled invariant set inside the safe set that provides an appropriate terminal constraint for the MPC optimization problem. An illustrative example is included.