Corcoba Magaña, V. and Muñoz-Organero, M. (2016) WATI: Warning of Traffic Incidents for Fuel Saving. Mobile Information Systems, 2016. 3091516. ISSN 1574-017X
Abstract
Traffic incidents (heavy traffic, adverse weather conditions, and traffic accidents) cause an increase in the frequency and intensity of the acceleration and deceleration. The result is a very significant increase in fuel consumption. In this paper, we propose a solution to reduce the impact of such events on energy consumption. The solution detects the traffic incidents based on measured telemetry data from vehicles and the different driver profiles. The proposal takes into account the rolling resistance coefficient, the road slope angle, and the vehicles speeds, from vehicles which are on the scene of the traffic incident, in order to estimate the optimal deceleration profile. Adapted advice and feedback are provided to the drivers in order to appropriately and timely release the accelerator pedal. The expert system is implemented on Android mobile devices and has been validated using a dataset of 150 tests using 15 different drivers. The main contribution of this paper is the proposal of a system to detect traffic incidents and provide an optimal deceleration pattern for the driver to follow without requiring sensors on the road. The results show an improvement on the fuel consumption of up to 13.47%.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2016 V. Corcoba Magaña and M. Muñoz-Organero. This is an open access article distributed under the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
Dates: |
|
Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > School of Health and Related Research (Sheffield) > ScHARR - Sheffield Centre for Health and Related Research |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 03 Nov 2016 16:52 |
Last Modified: | 03 Nov 2016 16:52 |
Published Version: | https://doi.org/10.1155/2016/3091516 |
Status: | Published |
Publisher: | Hindawi Publishing Corporation |
Refereed: | Yes |
Identification Number: | 10.1155/2016/3091516 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:106433 |