Roughness-induced vehicle energy dissipation from crowdsourced smartphone measurements through random vibration theory
Name
roughness-induced-vehicle-energy-dissipation-from-crowdsourced-smartphone-measurements-through-random-vibration-theory.pdf
Description
Published version
Size
2.46 MB
Format
Adobe PDF
Checksum (MD5)
2bdbe87d167e4f889c28209e3c6b3d30
Author(s)
Botshekan, Meshkat
Roxon, Jacob
Wanichkul, Athikom
Chirananthavat, Theemathas
Chamoun, Joy
Ziq, Malik
Anini, Bader
Daher, Naseem
Awad, Abdalkarim
Ghanem, Wasel
Date Issued
December 2020
Journal
Data-Centric Engineering
Publisher
Cambridge University Press (CUP)
Citation
Botshekan M, Roxon J, Wanichkul A, Chirananthavat T, Chamoun J, Ziq M, Anini B, Daher N, Awad A,
Ghanem W, Tootkaboni M, Louhghalam A and Ulm F.-J (2020). Roughness-induced vehicle energy dissipation from crowdsourced smartphone measurements through random vibration theory. Data-Centric Engineering, 1: e16
Version
Final published version
Abstract
We propose, calibrate, and validate a crowdsourced approach for estimating power spectral density (PSD) of road roughness based on an inverse analysis of vertical acceleration measured by a smartphone mounted in an unknown position in a vehicle. Built upon random vibration analysis of a half-car mechanistic model of roughness-induced pavement–vehicle interaction, the inverse analysis employs an L2 norm regularization to estimate ride quality metrics, such as the widely used International Roughness Index, from the acceleration PSD. Evoking the fluctuation–dissipation theorem of statistical physics, the inverse framework estimates the half-car dynamic vehicle properties and related excess fuel consumption. The method is validated against (a) laser-measured road roughness data for both inner city and highway road conditions and (b) road roughness data for the state of California. We also show that the phone position in the vehicle only marginally affects road roughness predictions, an important condition for crowdsourced capabilities of the proposed approach.
MIT Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Terms of Use
Creative Commons Attribution 4.0 International license
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1017/DCE.2020.17
