Next Article in Journal
Electrochemical Immunoassay Using Open Circuit Potential Detection Labeled by Platinum Nanoparticles
Next Article in Special Issue
Hard Fusion Based Spectrum Sensing over Mobile Fading Channels in Cognitive Vehicular Networks
Previous Article in Journal
Analysis of Flow Cytometric Fluorescence Lifetime with Time-Delay Estimation of Pulse Signals
Previous Article in Special Issue
Game-Theoretical Design of an Adaptive Distributed Dissemination Protocol for VANETs
Article Menu

Export Article

Open AccessArticle
Sensors 2018, 18(2), 443; doi:10.3390/s18020443

Speed Bump Detection Using Accelerometric Features: A Genetic Algorithm Approach

Unidad Académica de Ingeniería Eléctrica, CONACyT—Universidad Autónoma de Zacatecas, Jardín Juárez 147, Centro Histórico, 98000 Zacatecas, Mexico
Unidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas, Jardín Juárez 147, Centro Histórico, 98000 Zacatecas, Mexico
Unidad Académica de Ingeniería I, Universidad Autónoma de Zacatecas, Jardín Juárez 147, Centro Histórico, 98000 Zacatecas, Mexico
Departamento de ingeniería, Universidad de Monterrey, Avenida Ignacio Morones Prieto 4500 Pte., Jesús M. Garza, 66238, San Pedro Garza García, Nuevo León, Mexico
Author to whom correspondence should be addressed.
Received: 10 November 2017 / Revised: 5 January 2018 / Accepted: 5 January 2018 / Published: 3 February 2018
(This article belongs to the Special Issue Smart Vehicular Mobile Sensing)
Download PDF [918 KB, uploaded 3 February 2018]


Among the current challenges of the Smart City, traffic management and maintenance are of utmost importance. Road surface monitoring is currently performed by humans, but the road surface condition is one of the main indicators of road quality, and it may drastically affect fuel consumption and the safety of both drivers and pedestrians. Abnormalities in the road, such as manholes and potholes, can cause accidents when not identified by the drivers. Furthermore, human-induced abnormalities, such as speed bumps, could also cause accidents. In addition, while said obstacles ought to be signalized according to specific road regulation, they are not always correctly labeled. Therefore, we developed a novel method for the detection of road abnormalities (i.e., speed bumps). This method makes use of a gyro, an accelerometer, and a GPS sensor mounted in a car. After having the vehicle cruise through several streets, data is retrieved from the sensors. Then, using a cross-validation strategy, a genetic algorithm is used to find a logistic model that accurately detects road abnormalities. The proposed model had an accuracy of 0.9714 in a blind evaluation, with a false positive rate smaller than 0.018, and an area under the receiver operating characteristic curve of 0.9784. This methodology has the potential to detect speed bumps in quasi real-time conditions, and can be used to construct a real-time surface monitoring system.
Keywords: smart car; surface monitoring; speed bump detection smart car; surface monitoring; speed bump detection
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. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Celaya-Padilla, J.M.; Galván-Tejada, C.E.; López-Monteagudo, F.E.; Alonso-González, O.; Moreno-Báez, A.; Martínez-Torteya, A.; Galván-Tejada, J.I.; Arceo-Olague, J.G.; Luna-García, H.; Gamboa-Rosales, H. Speed Bump Detection Using Accelerometric Features: A Genetic Algorithm Approach. Sensors 2018, 18, 443.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top