Improving the Scalability of Automated Planning-based Vehicle Routing via Smart Routes Identification

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F23%3A00368791" target="_blank" >RIV/68407700:21230/23:00368791 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21730/23:00368791

Výsledek na webu

<a href="http://dx.doi.org/10.1109/MT-ITS56129.2023.10241639" target="_blank" >http://dx.doi.org/10.1109/MT-ITS56129.2023.10241639</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/MT-ITS56129.2023.10241639" target="_blank" >10.1109/MT-ITS56129.2023.10241639</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Improving the Scalability of Automated Planning-based Vehicle Routing via Smart Routes Identification

Popis výsledku v původním jazyce

Due to growing urbanisation, traffic infrastructures have to accommodate increasing demands of traffic volume. One promising way for supporting a better exploitation of traffic networks is vehicle routing, that can distribute traffic from congested links to under utilised ones. Automated Planning techniques, a research field of Artificial Intelligence, have demonstrated to be a suitable approach for performing effective centralised traffic distribution. However, a main weakness of this class of approaches is the limited scalability to large and complex networks. In this paper, we aim to improve the scalability of automated planning techniques for urban traffic distribution by introducing an approach for the identification of routes to be considered. The proposed technique can significantly improve the planning capabilities by simplifying the complexity of the urban network to be considered, as demonstrated by our extensive experimental analysis performed on realistic traffic data on part of the New York and Sydney urban areas.

Název v anglickém jazyce

Improving the Scalability of Automated Planning-based Vehicle Routing via Smart Routes Identification

Popis výsledku anglicky

Due to growing urbanisation, traffic infrastructures have to accommodate increasing demands of traffic volume. One promising way for supporting a better exploitation of traffic networks is vehicle routing, that can distribute traffic from congested links to under utilised ones. Automated Planning techniques, a research field of Artificial Intelligence, have demonstrated to be a suitable approach for performing effective centralised traffic distribution. However, a main weakness of this class of approaches is the limited scalability to large and complex networks. In this paper, we aim to improve the scalability of automated planning techniques for urban traffic distribution by introducing an approach for the identification of routes to be considered. The proposed technique can significantly improve the planning capabilities by simplifying the complexity of the urban network to be considered, as demonstrated by our extensive experimental analysis performed on realistic traffic data on part of the New York and Sydney urban areas.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

8th International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2023

ISBN

978-1-6654-5530-5

ISSN

—

e-ISSN

—

Počet stran výsledku

6

Strana od-do

—

Název nakladatele

IEEE Computer Society

Místo vydání

Los Alamitos

Místo konání akce

Nice

Datum konání akce

14. 6. 2023

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

001069745000045