Optimization-based Coordination of Traffic Lights and Automated Vehicles at Intersections

TL;DR

This paper presents an optimization framework for coordinating traffic lights and automated vehicles at intersections, improving traffic flow through a decomposition approach and parametric optimization techniques.

Contribution

It introduces a novel hierarchical optimization method combining traffic light timing and vehicle commands for better intersection management.

Findings

The proposed algorithm outperforms uncoordinated scenarios.

A decomposition approach effectively manages mixed-integer nonlinear problems.

Numerical examples demonstrate improved traffic flow and coordination.

Abstract

This paper tackles the challenge of coordinating traffic lights and automated vehicles at signalized intersections, formulated as a constrained finite-horizon optimal control problem. The problem falls into the category of mixed-integer nonlinear programming, posing challenges for solving large instances. To address this, we introduce a decomposition approach consisting of an upper-level problem for traffic light timing allocation and a set of lower-level problems that generate appropriate commands for automated vehicles in each intersection movement. By leveraging solutions from the lower-level problems and employing parametric optimization techniques, we solve the upper-level problem using a standard sequential quadratic programming approach. The paper concludes by presenting an illustrative numerical example that highlights the effectiveness of our algorithm compared to scenarios where no coordination between traffic lights and vehicles exists.