A sum-of-squares polynomial approach for road anomaly detection using vehicle sensor measurements

Dule Shu, Constantino Lagoa, Timothy Cleary

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

This paper presents a new method for road anomaly detection. The existence of road anomalies is determined by the behaviors of vehicles. A special polynomial named Sum-of-Squares (SOS) polynomial is used as a metric to evaluate the normality of vehicle behaviors. The method can process multiple types of sensor measurements. A feature extraction method is used to obtain concise representations of the sensor measurements. These representations, called feature points, are used to calculate the value of the SOS polynomial. Simulation results have been shown to demonstrate that the proposed method can effectively detect different types of road anomalies.

Original languageEnglish (US)
Title of host publicationMechatronics; Estimation and Identification; Uncertain Systems and Robustness; Path Planning and Motion Control; Tracking Control Systems; Multi-Agent and Networked Systems; Manufacturing; Intelligent Transportation and Vehicles; Sensors and Actuators; Diagnostics and Detection; Unmanned, Ground and Surface Robotics; Motion and Vibration Control Applications
PublisherAmerican Society of Mechanical Engineers
ISBN (Electronic)9780791858288
DOIs
StatePublished - 2017
EventASME 2017 Dynamic Systems and Control Conference, DSCC 2017 - Tysons, United States
Duration: Oct 11 2017Oct 13 2017

Publication series

NameASME 2017 Dynamic Systems and Control Conference, DSCC 2017
Volume2

Other

OtherASME 2017 Dynamic Systems and Control Conference, DSCC 2017
CountryUnited States
CityTysons
Period10/11/1710/13/17

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering
  • Mechanical Engineering

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