Citation

Alessandroni G, Carini A, Lattanzi E, Freschi V, Bogliolo A. Sensors (Basel) 2017; 17(2): s17020305.

Affiliation

DiSPeA-University of Urbino, 61029 Urbino, Italy. alessandro.bogliolo@uniurb.it.

Copyright

(Copyright © 2017, MDPI: Multidisciplinary Digital Publishing Institute)

DOI

10.3390/s17020305

PMID

28178224

Abstract

SmartRoadSense is a crowdsensing project aimed at monitoring the conditions of the road surface. Using the sensors of a smartphone, SmartRoadSense monitors the vertical accelerations inside a vehicle traveling the road and extracts a roughness index conveying information about the road conditions. The roughness index and the smartphone GPS data are periodically sent to a central server where they are processed, associated with the specific road, and aggregated with data measured by other smartphones. This paper studies how the smartphone vertical accelerations and the roughness index are related to the vehicle speed. It is shown that the dependence can be locally approximated with a gamma (power) law. Extensive experimental results using data extracted from SmartRoadSense database confirm the gamma law relationship between the roughness index and the vehicle speed. The gamma law is then used for improving the SmartRoadSense data aggregation accounting for the effect of vehicle speed.

Language: en

Keywords

SmartRoadSense; collaborative monitoring; road roughness index