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EcoTrec—A novel VANET-based approach to reducing vehicle emissions

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posted on 2017-04-05, 07:57 authored by Ronan Doolan, Gabriel-Miro Muntean
There are interdependent increases in vehicle numbers, vehicular traffic congestion, and carbon emissions that cause major problems worldwide. These problems include direct negative influences on people’s health, adverse economic effects, negative social impacts, local environmental damage, and risk of catastrophic global climate change. There is a drastic need to develop ways to reduce these emissions and EcoTrec, presented in this paper, is one of these innovative approaches. EcoTrec is a vehicular ad hoc network-based vehicle routing solution designed to reduce vehicle carbon emissions without significantly affecting the travel times of vehicles. The vehicles exchange messages related to traffic and road conditions, such as average speed on the road, road gradient, and surface condition. This information is used to build a fuel efficiency model of the routes, based on which the vehicles are recommended to takemore efficient routes. By routing vehicles more efficiently, the greenhouse emissions are reduced while also maintaining low traffic congestion levels. This paper presents results of extensive simulations, which show how EcoTrec outperforms other state-of-the-art solutions with different number of vehicles, vehicle penetration, and compliance rates, and when considering different real world road maps from Dublin and Koln.

History

Publication

IEEE Transactions on Intelligent Transportation Systems;18 (3), pp. 608-620

Publisher

IEEE Computer Society

Note

peer-reviewed

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SFI

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© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Language

English

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