Optimized Sensor Network and Multi-Agent Decision Support for Smart Traffic Light Management
One of the biggest challenges in modern societies is to solve vehicular traffic problems. Sensor networks in traffic environments have contributed to improving the decision-making process of Intelligent Transportation Systems. However, one of the limiting factors for the effectiveness of these syste...
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2018-02-01
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doaj-7034d2b22af44f45bf1c1f977bc84f762020-11-25T00:08:12ZengMDPI AGSensors1424-82202018-02-0118243510.3390/s18020435s18020435Optimized Sensor Network and Multi-Agent Decision Support for Smart Traffic Light ManagementLuis Cruz-Piris0Diego Rivera1Susel Fernandez2Ivan Marsa-Maestre3Departamento de Automática, Escuela Politécnica Superior, Universidad de Alcalá, 28805 Alcalá de Henares, Madrid, SpainDepartamento de Automática, Escuela Politécnica Superior, Universidad de Alcalá, 28805 Alcalá de Henares, Madrid, SpainDepartamento de Automática, Escuela Politécnica Superior, Universidad de Alcalá, 28805 Alcalá de Henares, Madrid, SpainDepartamento de Automática, Escuela Politécnica Superior, Universidad de Alcalá, 28805 Alcalá de Henares, Madrid, SpainOne of the biggest challenges in modern societies is to solve vehicular traffic problems. Sensor networks in traffic environments have contributed to improving the decision-making process of Intelligent Transportation Systems. However, one of the limiting factors for the effectiveness of these systems is in the deployment of sensors to provide accurate information about the traffic. Our proposal is using the centrality measurement of a graph as a base to locate the best locations for sensor installation in a traffic network. After integrating these sensors in a simulation scenario, we define a Multi-Agent Systems composed of three types of agents: traffic light management agents, traffic jam detection agents, and agents that control the traffic lights at an intersection. The ultimate goal of these Multi-Agent Systems is to improve the trip duration for vehicles in the network. To validate our solution, we have developed the needed elements for modelling the sensors and agents in the simulation environment. We have carried out experiments using the Simulation of Urban MObility (SUMO) traffic simulator and the Travel and Activity PAtterns Simulation (TAPAS) Cologne traffic scenario. The obtained results show that our proposal allows to reduce the sensor network while still obtaining relevant information to have a global view of the environment. Finally, regarding the Multi-Agent Systems, we have carried out experiments that show that our proposal is able to improve other existing solutions such as conventional traffic light management systems (static or dynamic) in terms of reduction of vehicle trip duration and reduction of the message exchange overhead in the sensor network.http://www.mdpi.com/1424-8220/18/2/435sensor networksoptimized sensor deploymentmulti-agents systemintelligent transportation systemsmart citiestraffic simulationstraffic light management |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Luis Cruz-Piris Diego Rivera Susel Fernandez Ivan Marsa-Maestre |
spellingShingle |
Luis Cruz-Piris Diego Rivera Susel Fernandez Ivan Marsa-Maestre Optimized Sensor Network and Multi-Agent Decision Support for Smart Traffic Light Management Sensors sensor networks optimized sensor deployment multi-agents system intelligent transportation system smart cities traffic simulations traffic light management |
author_facet |
Luis Cruz-Piris Diego Rivera Susel Fernandez Ivan Marsa-Maestre |
author_sort |
Luis Cruz-Piris |
title |
Optimized Sensor Network and Multi-Agent Decision Support for Smart Traffic Light Management |
title_short |
Optimized Sensor Network and Multi-Agent Decision Support for Smart Traffic Light Management |
title_full |
Optimized Sensor Network and Multi-Agent Decision Support for Smart Traffic Light Management |
title_fullStr |
Optimized Sensor Network and Multi-Agent Decision Support for Smart Traffic Light Management |
title_full_unstemmed |
Optimized Sensor Network and Multi-Agent Decision Support for Smart Traffic Light Management |
title_sort |
optimized sensor network and multi-agent decision support for smart traffic light management |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2018-02-01 |
description |
One of the biggest challenges in modern societies is to solve vehicular traffic problems. Sensor networks in traffic environments have contributed to improving the decision-making process of Intelligent Transportation Systems. However, one of the limiting factors for the effectiveness of these systems is in the deployment of sensors to provide accurate information about the traffic. Our proposal is using the centrality measurement of a graph as a base to locate the best locations for sensor installation in a traffic network. After integrating these sensors in a simulation scenario, we define a Multi-Agent Systems composed of three types of agents: traffic light management agents, traffic jam detection agents, and agents that control the traffic lights at an intersection. The ultimate goal of these Multi-Agent Systems is to improve the trip duration for vehicles in the network. To validate our solution, we have developed the needed elements for modelling the sensors and agents in the simulation environment. We have carried out experiments using the Simulation of Urban MObility (SUMO) traffic simulator and the Travel and Activity PAtterns Simulation (TAPAS) Cologne traffic scenario. The obtained results show that our proposal allows to reduce the sensor network while still obtaining relevant information to have a global view of the environment. Finally, regarding the Multi-Agent Systems, we have carried out experiments that show that our proposal is able to improve other existing solutions such as conventional traffic light management systems (static or dynamic) in terms of reduction of vehicle trip duration and reduction of the message exchange overhead in the sensor network. |
topic |
sensor networks optimized sensor deployment multi-agents system intelligent transportation system smart cities traffic simulations traffic light management |
url |
http://www.mdpi.com/1424-8220/18/2/435 |
work_keys_str_mv |
AT luiscruzpiris optimizedsensornetworkandmultiagentdecisionsupportforsmarttrafficlightmanagement AT diegorivera optimizedsensornetworkandmultiagentdecisionsupportforsmarttrafficlightmanagement AT suselfernandez optimizedsensornetworkandmultiagentdecisionsupportforsmarttrafficlightmanagement AT ivanmarsamaestre optimizedsensornetworkandmultiagentdecisionsupportforsmarttrafficlightmanagement |
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