Optimal Path Planning for Connected and Automated Vehicles at Urban Intersections

TL;DR

This paper develops an advanced optimization framework for coordinating connected and automated vehicles at urban intersections, improving upon previous FIFO-based methods by incorporating lane choices and turn maneuvers.

Contribution

It introduces an upper-level optimization model that determines optimal crossing sequences and lane assignments for CAVs, including turns, enhancing intersection management.

Findings

The proposed method improves traffic flow efficiency.

Simulation results demonstrate better intersection throughput.

The approach accommodates lane changes and turns.

Abstract

In earlier work, a decentralized optimal control framework was established for coordinating online connected and automated vehicles (CAVs) at urban intersections. The policy designating the sequence that each CAV crosses the intersection, however, was based on a first-in-first-out queue, imposing limitations on the optimal solution. Moreover, no lane changing, or left and right turns were considered. In this paper, we formulate an upper-level optimization problem, the solution of which yields, for each CAV, the optimal sequence and lane to cross the intersection. The effectiveness of the proposed approach is illustrated through simulation.