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Intersection management for autonomous vehicles with vehicle-to-infrastructure communication
This paper proposes an intersection management strategy for autonomous vehicles under the vehicle-to-infrastructure circumstance. All vehicles are supposed to be fully autonomous and can communicate with the intersection management unit to check the traffic situation. Priority of passing the interse...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7331991/ https://www.ncbi.nlm.nih.gov/pubmed/32614893 http://dx.doi.org/10.1371/journal.pone.0235644 |
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author | Li, Yuying Liu, Qipeng |
author_facet | Li, Yuying Liu, Qipeng |
author_sort | Li, Yuying |
collection | PubMed |
description | This paper proposes an intersection management strategy for autonomous vehicles under the vehicle-to-infrastructure circumstance. All vehicles are supposed to be fully autonomous and can communicate with the intersection management unit to check the traffic situation. Priority of passing the intersection is decided by a static conflict matrix which represents the potential conflict between lanes of different directions and a dynamic information list which could capture the real-time occupation of each lane in the intersection. Compared with the existing approaches in the literature, the intersection management unit in our strategy is more like a database rather than a computational center, and therefore, requires less computational resource and more likely satisfies the real-time requirement in heavy traffic situations. Simulations are conducted using SUMO (Simulation of Urban MObility), in which the proposed strategy is compared with both fixed and adaptive traffic light methods. The results indicate that the proposed strategy could significantly reduce the average time delay caused by the intersection and the corresponding variance, which shows the efficiency and fairness of the proposed strategy in intersection management. |
format | Online Article Text |
id | pubmed-7331991 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-73319912020-07-14 Intersection management for autonomous vehicles with vehicle-to-infrastructure communication Li, Yuying Liu, Qipeng PLoS One Research Article This paper proposes an intersection management strategy for autonomous vehicles under the vehicle-to-infrastructure circumstance. All vehicles are supposed to be fully autonomous and can communicate with the intersection management unit to check the traffic situation. Priority of passing the intersection is decided by a static conflict matrix which represents the potential conflict between lanes of different directions and a dynamic information list which could capture the real-time occupation of each lane in the intersection. Compared with the existing approaches in the literature, the intersection management unit in our strategy is more like a database rather than a computational center, and therefore, requires less computational resource and more likely satisfies the real-time requirement in heavy traffic situations. Simulations are conducted using SUMO (Simulation of Urban MObility), in which the proposed strategy is compared with both fixed and adaptive traffic light methods. The results indicate that the proposed strategy could significantly reduce the average time delay caused by the intersection and the corresponding variance, which shows the efficiency and fairness of the proposed strategy in intersection management. Public Library of Science 2020-07-02 /pmc/articles/PMC7331991/ /pubmed/32614893 http://dx.doi.org/10.1371/journal.pone.0235644 Text en © 2020 Li, Liu http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Li, Yuying Liu, Qipeng Intersection management for autonomous vehicles with vehicle-to-infrastructure communication |
title | Intersection management for autonomous vehicles with vehicle-to-infrastructure communication |
title_full | Intersection management for autonomous vehicles with vehicle-to-infrastructure communication |
title_fullStr | Intersection management for autonomous vehicles with vehicle-to-infrastructure communication |
title_full_unstemmed | Intersection management for autonomous vehicles with vehicle-to-infrastructure communication |
title_short | Intersection management for autonomous vehicles with vehicle-to-infrastructure communication |
title_sort | intersection management for autonomous vehicles with vehicle-to-infrastructure communication |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7331991/ https://www.ncbi.nlm.nih.gov/pubmed/32614893 http://dx.doi.org/10.1371/journal.pone.0235644 |
work_keys_str_mv | AT liyuying intersectionmanagementforautonomousvehicleswithvehicletoinfrastructurecommunication AT liuqipeng intersectionmanagementforautonomousvehicleswithvehicletoinfrastructurecommunication |