Road anomaly estimation: Model based pothole detection

被引：0
|
作者：
Li, Zhaojian [1 ]
Kolmanovsky, Ilya [1 ]
Atkins, Ella [1 ]
Lu, Jianbo [2 ]
Filev, Dimitar [2 ]
机构：
[1] Univ Michigan, Dept Aerosp Engn, Ann Arbor, MI 48105 USA
[2] Ford Motor Co, Res & Adv Engn, Dearborn, MI 48121 USA
来源：
2015 AMERICAN CONTROL CONFERENCE (ACC) | 2015年
关键词：
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
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.
引用
收藏
页码：1315 / 1320
页数：6
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