Corcoba Magaña, VíctorMuñoz Organero, Mario2018-02-222018-02-222016-01-01Mobile Information Systems, 2016 (3091516), pp. 161574-017Xhttps://hdl.handle.net/10016/25402Traffic 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%.16application/pdfeng© 2016 V. Corcoba Magaña and M. Muñoz-Organero. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Atribución-NoComercial-SinDerivadas 3.0 EspañaTraffic incidentsFuel consumptionOptimal deceleration patternEcodrivingresearch articleTelecomunicacioneshttps://doi.org/10.1155/2016/3091516open access116Journal of Mobile Information Systems2016 (3091516)AR/0000017787