Conditions to Provable System-Wide Optimal Coordination of Connected and Automated Vehicles

TL;DR

This paper develops a real-time, closed-form solution framework for the optimal coordination of connected and automated vehicles, enhancing energy efficiency and safety in traffic management.

Contribution

It introduces a condition-based computational framework and derives a closed-form analytical solution for the constrained optimal control problem of CAVs.

Findings

Framework improves computational efficiency over iterative methods

Closed-form solution suitable for real-time onboard implementation

Validated through numerical simulations demonstrating effectiveness

Abstract

Connected and automated vehicles (CAVs) provide the most intriguing opportunity to improve energy efficiency, traffic flow, and safety. In earlier work, we addressed the constrained optimal coordination problem of CAVs at different traffic scenarios using Hamiltonian analysis. In this paper, we investigate the properties of the unconstrained problem and provide conditions under which different combination of the state and control constraints become active. We present a condition-based computational framework that improves on the standard iterative solution procedure of the constrained Hamiltonian analysis. Finally, we derive a closed-form analytical solution of the constrained optimal control problem and validate the proposed framework using numerical simulation. The solution can be derived without any recursive steps, and thus it is appropriate for real-time implementation on-board the CAVs.