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Performance evaluation of RED approach for traffic lights management
Road's traffic management is an important topic which is more and more covered by various actors in the Intelligent Transportation Systems field via many proposed solutions. Thus, in order to achieve the dream of a smart city, special attention was given to the treatment of cities' traffic...
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Main Authors: | , , |
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Format: | Conference Proceeding |
Language: | English |
Subjects: | |
Online Access: | Request full text |
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Summary: | Road's traffic management is an important topic which is more and more covered by various actors in the Intelligent Transportation Systems field via many proposed solutions. Thus, in order to achieve the dream of a smart city, special attention was given to the treatment of cities' traffic management problem; especially in junctions which constitute bottlenecks for traffic flow leading to a poor quality of urban mobility. The aim of this study is to examine further the RED approach for traffic lights management recently proposed for the design of an adaptive signal control system In the context of ITL (Intelligent Traffic Lights) systems, based generally on sensors, and communication technologies. Traffic management is a well known problematic in data networks. Thus, several researchers have studied methods for providing congestion avoidance at the gateway called also router. Inspired by advanced technologies in Internet traffic management, we propose a system based on the RED (Random Early Detection) mechanism widely used by routers to avoid congestion. Our contribution consists of the adaptation of this mechanism to the ITS context by applying it for traffic lights management. Our system will certainly contribute to decrease waiting times, fuel consumption and pollution. This paper will present the complete adaptation of the RED algorithm to the context of the intelligent transport systems. In addition, the RED-based design performance is compared with that of the pre-timed model to gain insights between the two systems. |
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ISSN: | 2164-7151 |
DOI: | 10.1109/ISDA.2015.7489254 |