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Title:
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TRAFFIC CONTROL SENSOR NETWORKS: A PREDICTIVE APPROACH |
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Author(s):
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Miguel Sánchez , Juan-carlos Cano |
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ISBN:
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972-8924-09-7 |
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Editors:
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Nuno Guimarães, Pedro Isaías and Ambrosio Goikoetxea |
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Year:
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2006 |
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Edition:
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Single |
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Keywords:
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Traffic control, Sensor networks. |
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Type:
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Full Paper |
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First Page:
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217 |
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Last Page:
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224 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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This paper evaluates the use of a new driving model and its positive impact on vehicles fuel consumption. Rising oil costs and the Kyoto protocol agreements are demanding new ways of improving our transit systems fuel efficiency. We present a new driving model named Predictive Intelligent Driver Model (IDMP) that provides an effective way to reduce fuel consumption. IDMP improves real world traffic by using the benefits of providing drivers with reliable information about when the light ahead will turn green or red. We based our approach on the use of a sensor network architecture that can be inexpensively and selectively deployed on certain city areas to provide drivers with additional information. We run some experiments to evaluate the performance and system behavior of the proposed model. We present our findings in terms of fuel consumption and average speed. Our preliminary results show that 25% savings are within range. |
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