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Bibliographic Details
Main Authors: Faris, Muhammad, Zanon, Mario, Falcone, Paolo
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2404.14048
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author Faris, Muhammad
Zanon, Mario
Falcone, Paolo
author_facet Faris, Muhammad
Zanon, Mario
Falcone, Paolo
contents In this paper, we address a coordination problem for connected and autonomous vehicles (CAVs) in mixed traffic settings with human-driven vehicles (HDVs). The main objective is to have a safe and optimal crossing order for vehicles approaching unsignalized intersections. This problem results in a mixed-integer quadratic programming (MIQP) formulation which is unsuitable for real-time applications. Therefore, we propose a computationally tractable optimization-based heuristic that monitors platoons of CAVs and HDVs to evaluate whether alternative crossing orders can perform better. It first checks the future constraint violation that consistently occurs between pairs of platoons to determine a potential swap. Next, the costs of quadratic programming (QP) formulations associated with the current and alternative orders are compared in a depth-first branching fashion. In simulations, we show that the heuristic can be a hundred times faster than the original and simplified MIQPs and yields solutions that are close to optimal and have better order consistency.
format Preprint
id arxiv_https___arxiv_org_abs_2404_14048
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Optimization-based Heuristic for Vehicle Dynamic Coordination in Mixed Traffic Intersections
Faris, Muhammad
Zanon, Mario
Falcone, Paolo
Systems and Control
In this paper, we address a coordination problem for connected and autonomous vehicles (CAVs) in mixed traffic settings with human-driven vehicles (HDVs). The main objective is to have a safe and optimal crossing order for vehicles approaching unsignalized intersections. This problem results in a mixed-integer quadratic programming (MIQP) formulation which is unsuitable for real-time applications. Therefore, we propose a computationally tractable optimization-based heuristic that monitors platoons of CAVs and HDVs to evaluate whether alternative crossing orders can perform better. It first checks the future constraint violation that consistently occurs between pairs of platoons to determine a potential swap. Next, the costs of quadratic programming (QP) formulations associated with the current and alternative orders are compared in a depth-first branching fashion. In simulations, we show that the heuristic can be a hundred times faster than the original and simplified MIQPs and yields solutions that are close to optimal and have better order consistency.
title Optimization-based Heuristic for Vehicle Dynamic Coordination in Mixed Traffic Intersections
topic Systems and Control
url https://arxiv.org/abs/2404.14048