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

Dule Shu; Constantino Lagoa; Timothy Cleary

doi:10.1115/DSCC2017-5155

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

Dule Shu, Constantino Lagoa, Timothy Cleary

Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 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 language	English (US)
Title of host publication	Mechatronics; 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
Publisher	American Society of Mechanical Engineers
ISBN (Electronic)	9780791858288
DOIs	https://doi.org/10.1115/DSCC2017-5155
State	Published - 2017
Event	ASME 2017 Dynamic Systems and Control Conference, DSCC 2017 - Tysons, United States Duration: Oct 11 2017 → Oct 13 2017

Publication series

Name	ASME 2017 Dynamic Systems and Control Conference, DSCC 2017
Volume	2

Other

Other	ASME 2017 Dynamic Systems and Control Conference, DSCC 2017
Country/Territory	United States
City	Tysons
Period	10/11/17 → 10/13/17

All Science Journal Classification (ASJC) codes

Control and Systems Engineering
Industrial and Manufacturing Engineering
Mechanical Engineering

Access to Document

10.1115/DSCC2017-5155

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Shu, D., Lagoa, C., & Cleary, T. (2017). A sum-of-squares polynomial approach for road anomaly detection using vehicle sensor measurements. In Mechatronics; 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 (ASME 2017 Dynamic Systems and Control Conference, DSCC 2017; Vol. 2). American Society of Mechanical Engineers. https://doi.org/10.1115/DSCC2017-5155

Shu, Dule ; Lagoa, Constantino ; Cleary, Timothy. / A sum-of-squares polynomial approach for road anomaly detection using vehicle sensor measurements. Mechatronics; 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. American Society of Mechanical Engineers, 2017. (ASME 2017 Dynamic Systems and Control Conference, DSCC 2017).

@inproceedings{86a143bb90d74d4391bceb35158f848f,

title = "A sum-of-squares polynomial approach for road anomaly detection using vehicle sensor measurements",

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.",

author = "Dule Shu and Constantino Lagoa and Timothy Cleary",

year = "2017",

doi = "10.1115/DSCC2017-5155",

language = "English (US)",

series = "ASME 2017 Dynamic Systems and Control Conference, DSCC 2017",

publisher = "American Society of Mechanical Engineers",

booktitle = "Mechatronics; 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",

}

Shu, D, Lagoa, C & Cleary, T 2017, A sum-of-squares polynomial approach for road anomaly detection using vehicle sensor measurements. in Mechatronics; 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. ASME 2017 Dynamic Systems and Control Conference, DSCC 2017, vol. 2, American Society of Mechanical Engineers, ASME 2017 Dynamic Systems and Control Conference, DSCC 2017, Tysons, United States, 10/11/17. https://doi.org/10.1115/DSCC2017-5155

A sum-of-squares polynomial approach for road anomaly detection using vehicle sensor measurements. / Shu, Dule; Lagoa, Constantino; Cleary, Timothy.
Mechatronics; 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. American Society of Mechanical Engineers, 2017. (ASME 2017 Dynamic Systems and Control Conference, DSCC 2017; Vol. 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - A sum-of-squares polynomial approach for road anomaly detection using vehicle sensor measurements

AU - Shu, Dule

AU - Lagoa, Constantino

AU - Cleary, Timothy

PY - 2017

Y1 - 2017

N2 - 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.

AB - 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.

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UR - http://www.scopus.com/inward/citedby.url?scp=85036616737&partnerID=8YFLogxK

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DO - 10.1115/DSCC2017-5155

M3 - Conference contribution

AN - SCOPUS:85036616737

T3 - ASME 2017 Dynamic Systems and Control Conference, DSCC 2017

BT - Mechatronics; 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

PB - American Society of Mechanical Engineers

T2 - ASME 2017 Dynamic Systems and Control Conference, DSCC 2017

Y2 - 11 October 2017 through 13 October 2017

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Shu D, Lagoa C, Cleary T. A sum-of-squares polynomial approach for road anomaly detection using vehicle sensor measurements. In Mechatronics; 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. American Society of Mechanical Engineers. 2017. (ASME 2017 Dynamic Systems and Control Conference, DSCC 2017). doi: 10.1115/DSCC2017-5155

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

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