This paper presents a Traffic Lights control system, inspired by Swarm intelligence methodologies, in which every intersection controller makes independent decisions to pursue common goals and is able to improve global traffic performance. The solution is low cost and widely applicable to different urban scenarios. This work is developed within the COLOMBO European project. Control methods are divided into macroscopic and microscopic control level methods. The former react to macroscopic key figures such as mean congestion length and mean traffic density and acts on the signal program choice or the development of the frame signal program. The latter include changes at short notice based on changes in the traffic flow: they include methods for signal program adaptation and development. The developed system has been widely tested on synthetic benchmarks with promising results.

Belletti, R., Bonfietti, A., Foschini, L., Milano, M., Krajzewicz, D. (2014). Swarm-based traffic lights policy selection. Association for Computing Machinery, Inc [10.1145/2656346.2656364].

Swarm-based traffic lights policy selection

BELLETTI, RICCARDO;BONFIETTI, ALESSIO;FOSCHINI, LUCA;MILANO, MICHELA;
2014

Abstract

This paper presents a Traffic Lights control system, inspired by Swarm intelligence methodologies, in which every intersection controller makes independent decisions to pursue common goals and is able to improve global traffic performance. The solution is low cost and widely applicable to different urban scenarios. This work is developed within the COLOMBO European project. Control methods are divided into macroscopic and microscopic control level methods. The former react to macroscopic key figures such as mean congestion length and mean traffic density and acts on the signal program choice or the development of the frame signal program. The latter include changes at short notice based on changes in the traffic flow: they include methods for signal program adaptation and development. The developed system has been widely tested on synthetic benchmarks with promising results.
2014
DIVANet 2014 - Proceedings of the 4th ACM Symposium on Development and Analysis of Intelligent Vehicular Networks and Applications
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Belletti, R., Bonfietti, A., Foschini, L., Milano, M., Krajzewicz, D. (2014). Swarm-based traffic lights policy selection. Association for Computing Machinery, Inc [10.1145/2656346.2656364].
Belletti, Riccardo; Bonfietti, Alessio; Foschini, Luca; Milano, Michela; Krajzewicz, Daniel
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/521431
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