Next Article in Journal
Improved Measurement of Blood Pressure by Extraction of Characteristic Features from the Cuff Oscillometric Waveform
Next Article in Special Issue
Managing Emergency Situations in the Smart City: The Smart Signal
Previous Article in Journal
A High Performance Banknote Recognition System Based on a One-Dimensional Visible Light Line Sensor
Previous Article in Special Issue
Socially Aware Heterogeneous Wireless Networks
Article Menu

Export Article

Open AccessArticle
Sensors 2015, 15(6), 14116-14141; doi:10.3390/s150614116

Analysis of Intelligent Transportation Systems Using Model-Driven Simulations

Departamento de Ingeniería del Software e Inteligencia Artificial, Facultad de Informática, Universidad Complutense de Madrid, 28040 Madrid, Spain
*
Author to whom correspondence should be addressed.
Academic Editors: Antonio Puliafito, Symeon Papavassiliou and Dario Bruneo
Received: 4 April 2015 / Revised: 27 May 2015 / Accepted: 10 June 2015 / Published: 15 June 2015
(This article belongs to the Special Issue Sensors and Smart Cities)
View Full-Text   |   Download PDF [1200 KB, uploaded 15 June 2015]   |  

Abstract

Intelligent Transportation Systems (ITSs) integrate information, sensor, control, and communication technologies to provide transport related services. Their users range from everyday commuters to policy makers and urban planners. Given the complexity of these systems and their environment, their study in real settings is frequently unfeasible. Simulations help to address this problem, but present their own issues: there can be unintended mistakes in the transition from models to code; their platforms frequently bias modeling; and it is difficult to compare works that use different models and tools. In order to overcome these problems, this paper proposes a framework for a model-driven development of these simulations. It is based on a specific modeling language that supports the integrated specification of the multiple facets of an ITS: people, their vehicles, and the external environment; and a network of sensors and actuators conveniently arranged and distributed that operates over them. The framework works with a model editor to generate specifications compliant with that language, and a code generator to produce code from them using platform specifications. There are also guidelines to help researchers in the application of this infrastructure. A case study on advanced management of traffic lights with cameras illustrates its use. View Full-Text
Keywords: intelligent transportation system; smart city; sensor; actuator; traffic lights; simulation; model-driven engineering; modeling language; agent-based modeling; code generation intelligent transportation system; smart city; sensor; actuator; traffic lights; simulation; model-driven engineering; modeling language; agent-based modeling; code generation
Figures

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Fernández-Isabel, A.; Fuentes-Fernández, R. Analysis of Intelligent Transportation Systems Using Model-Driven Simulations. Sensors 2015, 15, 14116-14141.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top