A General Framework for Decentralized Safe Optimal Control of Connected and Automated Vehicles in Multi-Lane Intersections

TL;DR

This paper presents a decentralized control framework for connected and automated vehicles at multi-lane intersections, optimizing safety, time, and energy use while managing computational complexity.

Contribution

It introduces a novel framework converting multi-lane intersection control into decentralized problems using control barrier functions for efficiency and safety.

Findings

Effective control of CAVs in complex intersections demonstrated

Framework reduces computational complexity compared to prior methods

Simulation results show improved safety and efficiency

Abstract

We address the problem of optimally controlling Connected and Automated Vehicles (CAVs) arriving from four multi-lane roads at an intersection where they conflict in terms of safely crossing (including turns) with no collision. The objective is to jointly minimize the travel time and energy consumption of each CAV while ensuring safety. This problem was solved in prior work for single-lane roads. A direct extension to multiple lanes on each road is limited by the computational complexity required to obtain an explicit optimal control solution. Instead, we propose a general framework that first converts a multi-lane intersection problem into a decentralized optimal control problem for each CAV with less conservative safety constraints than prior work. We then employ a method combining optimal control and control barrier functions, which has been shown to efficiently track tractable unconstrained optimal CAV trajectories while also guaranteeing the satisfaction of all constraints. Simulation examples are included to show the effectiveness of the proposed framework under symmetric and asymmetric intersection geometries and different schemes for CAV sequencing.