MUSA–I. towards New Social Tools for Advanced Multi-Modal Transportation in Smart Cities

Urban mobility optimization problem has a great focus in the context of Smart cities. To its solution a very important factor is the transport demand, which is mostly inferred using Big Data and Artificial Intelligence techniques from Automatic Fare Collection (AFC) and mobile devices data. In this...

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Bibliographic Details
Published inProceedings Vol. 2; no. 19; p. 1215
Main Authors Víctor Manuel Padrón Nápoles, Manuel de Buenaga Rodríguez, Diego Gachet Páez, José Luis Esteban Penelas, Alba Gutiérrez García-Ochoa, Alfonso López Pérez
Format Journal Article
LanguageEnglish
Published MDPI AG 01.10.2018
Subjects
bus sensorization
explicit demand
smart bus stops
smart cities
Online AccessGet full text
ISSN2504-3900
DOI10.3390/proceedings2191215

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Summary:Urban mobility optimization problem has a great focus in the context of Smart cities. To its solution a very important factor is the transport demand, which is mostly inferred using Big Data and Artificial Intelligence techniques from Automatic Fare Collection (AFC) and mobile devices data. In this paper a novel approach, based on Transport Demand Management techniques is proposed, using technology to produce a more active social involvement in the planning and optimization of mobility. This paper describes, a first step to this long-term objective, the general architecture and current implementation of an explicit multi-modal transport demand system for Smart Cities, which is being developed in the frame of MUSA—I project in the city of Madrid.
ISSN:2504-3900
DOI:10.3390/proceedings2191215