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Sensors 2017, 17(2), 305;

A Study on the Influence of Speed on Road Roughness Sensing: The SmartRoadSense Case

DiSPeA—University of Urbino, 61029 Urbino, Italy
This paper is an extended version of our paper published in Proceedings of ISPA 2015 ( G. Alessandroni, A. Carini, E. Lattanzi, and A. Bogliolo, “Sensing Road Roughness via Mobile Devices: a Study on Speed Influence”, Zagreb, Croatia, 7–9 September 2015).
Author to whom correspondence should be addressed.
Academic Editor: Simon X. Yang
Received: 27 December 2016 / Revised: 31 January 2017 / Accepted: 2 February 2017 / Published: 7 February 2017
(This article belongs to the Special Issue Sensors for Transportation)
Full-Text   |   PDF [5987 KB, uploaded 7 February 2017]   |  


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. View Full-Text
Keywords: SmartRoadSense; collaborative monitoring; road roughness index SmartRoadSense; collaborative monitoring; road roughness index

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Alessandroni, G.; Carini, A.; Lattanzi, E.; Freschi, V.; Bogliolo, A. A Study on the Influence of Speed on Road Roughness Sensing: The SmartRoadSense Case. Sensors 2017, 17, 305.

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