Applications that recommend optimal speeds for specific road segments can yield emissions and fuel consumption savings of 5.3 percent and 11.6 percent, respectively, for cars.
A simulation of node to vehicle communication networks
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OSA: A VANET Application Focused on Fuel Saving and Reduction of CO2 Emissions

Summary Information

This paper focuses on answering the question of how to increase energy efficiency of moving vehicles (i.e. reduce fuel consumption and GHG emissions, particularly CO2) depending on the route they present. The result is the design, development and performance evaluation of Optimal Speed Advisory (OSA) application. OSA optimizes fuel usage and reduces greenhouse gas emissions of vehicles by informing the vehicle of the optimal speed while following a route. It combines the advantages of Vehicular Ad hoc Networks (VANETs) related with portability and scalability in order to reduce carbon dioxide emissions and fuel consumption. Performance evaluation of OSA was performed by analyzing fuel usage, Carbon dioxide emissions, packet loss, and packet error rate in a small number of nodes in a series of simulations. The simulations used software package SUMO to control vehicular traffic flow, and software OMNeT++ as a platform of data implementation, and framework Vehicles in Network Simulation (Veins) as a simulation frame to integrate SUMO and OMNeT++.


Simulation results verify the fuel consumption and emissions benefits of this application when vehicles traveling in nodes respect the optimal speed.

Use of the application and the optimal speed finds the percentage of savings for carbon dioxide emissions is 5.3 percent and fuel consumption is 11.6 percent for sedans and compact vehicles. However, use of the application was found to yield a 26.6 percent fuel savings for cargo vans. In simulation, the application appeared to have a greater effect with larger vehicles.

In each scenario and case studied, OSA demonstrated reliability and robustness as long as the packet error rate and packet loss values were lower in nodes using the application. This improvement in fuel efficiency was noted for every type of vehicle simulated: sedan/compact cars, buses, cargo vans, and heavy duty trucks.
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