Realistic traffic model for urban environments based on induction loop data

[EN] As we gradually move towards smarter cities, having greater control of the traffic in the city becomes of utmost importance. In addition, to efficiently manage such traffic, it is critical to be able to predict the impact of different traffic policies, and potential changes to the city road sys...

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Bibliographic Details
Authors: Padrón-Pérez, José Daniel|||0000-0001-6766-3034, Hernández-Orallo, Enrique|||0000-0002-3284-561X, Tavares De Araujo Cesariny Calafate, Carlos Miguel|||0000-0001-5729-3041, Cano, Juan-Carlos|||0000-0002-0038-0539, Manzoni, Pietro|||0000-0003-3753-0403, Soler Fernández, David
Format: article
Publication Date:2023
Country:España
Institution:Universitat Politècnica de València (UPV)
Repository:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Language:English
OAI Identifier:oai:riunet.upv.es:10251/204475
Online Access:https://riunet.upv.es/handle/10251/204475
Access Level:Open access
Keyword:DFROUTER
OD traffic matrix
Induction loop detectors
Traffic modeling
ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES
Description
Summary:[EN] As we gradually move towards smarter cities, having greater control of the traffic in the city becomes of utmost importance. In addition, to efficiently manage such traffic, it is critical to be able to predict the impact of different traffic policies, and potential changes to the city road systems structure. To this end, accurate traffic simulation models must be derived that can help in this task. This paper presents a tool that aims to improve the representativeness of traffic simulations by generating realistic Origin-Destination (OD) traffic matrices. In particular, we focus on cities whose source of traffic information are the induction loop detectors deployed through the different streets and avenues of the city. By comparing against the widely used DFROUTER tool, part of the SUMO open-source traffic simulation package, we show how we are able to improve the traffic model accuracy significantly. Specifically, we achieved more realistic route lengths and a better distribution of traffic sources and destinations.