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Sensors 2018, 18(2), 435; doi:10.3390/s18020435

Optimized Sensor Network and Multi-Agent Decision Support for Smart Traffic Light Management

Departamento de Automática, Escuela Politécnica Superior, Universidad de Alcalá, 28805 Alcalá de Henares, Madrid, Spain
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Received: 15 December 2017 / Revised: 19 January 2018 / Accepted: 31 January 2018 / Published: 2 February 2018
(This article belongs to the Special Issue Smart Communication Protocols and Algorithms for Sensor Networks)
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Abstract

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. View Full-Text
Keywords: sensor networks; optimized sensor deployment; multi-agents system; intelligent transportation system; smart cities; traffic simulations; traffic light management sensor networks; optimized sensor deployment; multi-agents system; intelligent transportation system; smart cities; traffic simulations; traffic light management
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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).

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MDPI and ACS Style

Cruz-Piris, L.; Rivera, D.; Fernandez, S.; Marsa-Maestre, I. Optimized Sensor Network and Multi-Agent Decision Support for Smart Traffic Light Management. Sensors 2018, 18, 435.

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