Acceleration time histories and road elevation profiles

Low-cost smartphone-based sensing approaches have recently emerged as an
alternative to the traditional and oftentimes expensive or laborious road
surface monitoring technologies. We develop an approach, resting
on a rigorously derived mechanistic and stochastic model in spectral
domain, that relates the vertical acceleration signal measured by a
smartphone positioned in a moving car to road surface roughness
metrics. We illustrate that the inferred roughness metrics from
the acceleration data sets, acquired with different smartphones and
vehicle types, are in good agreement with the ones obtained from the
expensive laser measurements. The data set we used for our
analysis is hence comprised of (I) acceleration signals recorded by
smartphones placed at different locations of the vehicle, and (II)
laser-measured road longitudinal profiles. The validation
analysis is performed for two test tracks:  (1) 13.8 km
of a thoroughfare with a dominating inner-city component with
poor ride quality, and (2) 11.6 km of a highway with good ride quality.
The coordinates (latitude and longitude) of the two test tracks are also
available in the provided data set.