A Closed-Form Analytical Solution for Optimal Coordination of Connected and Automated Vehicles

TL;DR

This paper derives a comprehensive closed-form analytical solution for coordinating connected and automated vehicles, incorporating rear-end safety constraints into the optimal control framework for improved traffic management.

Contribution

It extends previous models by including rear-end collision avoidance as a state constraint, providing a complete analytical solution for vehicle coordination.

Findings

The analytical solution effectively incorporates safety constraints.

Simulation results demonstrate the solution's practical applicability.

The method improves coordination efficiency while ensuring safety.

Abstract

In earlier work, a decentralized optimal control framework was established for coordinating online connected and automated vehicles (CAVs) in merging roadways, urban intersections, speed reduction zones, and roundabouts. The dynamics of each vehicle were represented by a double integrator and the Hamiltonian analysis was applied to derive an analytical solution that minimizes the L2-norm of the control input. However, the analytical solution did not consider the rear-end collision avoidance constraint. In this paper, we derive a complete, closed-form analytical solution that includes the rear-end safety constraint in addition to the state and control constraints. We augment the double integrator model that represents a vehicle with an additional state corresponding to the distance from its preceding vehicle. Thus, the rear-end collision avoidance constraint is included as a state constraint. The effectiveness of the solution is illustrated through simulation.