Road anomaly estimation: Model based pothole detection

Author

Zhaojian Li ; Kolmanovsky, Ilya ; Atkins, Ella ; Jianbo Lu ; Filev, Dimitar

Author_Institution

Dept. of Aerosp. Eng., Univ. of Michigan, Ann Arbor, MI, USA

fYear

2015

fDate

1-3 July 2015

Firstpage

1315

Lastpage

1320

Abstract

This paper describes a model-based pothole detection algorithm that exploits a multi-phase dynamic model. The responses of hitting potholes are empirically broken down into three phases governed by three simpler dynamic system sub-models. Each sub-model is based on a rigid-ring tire and quarter-car suspension model. The model is validated by comparing simulation results over various scenarios with FTire, a commercial simulation software for tire-road interaction. Based on the developed model, a pothole detection algorithm with Unscented Kalman Filter (UKF) and Bayesian estimation is developed and demonstrated.

Keywords

Bayes methods; Kalman filters; automotive components; estimation theory; mechanical engineering computing; nonlinear filters; suspensions (mechanical components); tyres; vehicle dynamics; Bayesian estimation; FTire; UKF; dynamic system submodels; model based pothole detection; multiphase dynamic model; pothole hitting; quarter-car suspension model; rigid-ring tire; road anomaly estimation; simulation software; tire-road interaction; unscented Kalman filter; Aerodynamics; Detection algorithms; Roads; Tires; Vehicle dynamics; Vehicles; Wheels;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference (ACC), 2015

Conference_Location

Chicago, IL

Print_ISBN

978-1-4799-8685-9

Type

conf

DOI

10.1109/ACC.2015.7170915

Filename

7170915