Research on information fusion algorithm for vehicle speed information and road adhesion property estimation

Dan Hu; Changfu Zong; Hsiaohsiang Na

doi:10.1109/ICMA.2009.5246209

Research on information fusion algorithm for vehicle speed information and road adhesion property estimation

Dan Hu, Changfu Zong, Hsiaohsiang Na

Jilin University

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding › peer-review

6 Citations (Scopus)

Abstract

To achieve the vehicle speed information and tire-road adhesion property is very important to the vehicle active safety control system. And how to utilize the sensors in vehicle to educe the needed information for these systems while ensuring the accuracy and real-time performance has great significance. In this paper, the state estimation theory of information fusion technology is applied to estimate the vehicle speed and tire-road friction coefficient based on a 3-degree-of-freedom vehicle model containing modified Dugoff tire model, which can not only satisfy the accuracy but also explain the relation of tire-road. Due to the nonlinear characteristic of tireroad behavior, the Extended Kalman Filter (EKJo') is applied. By comparing with the outputs signals from CarSim, high accuracy as well as effective availability of this algorithm have been demonstrated.

Original language	English
Title of host publication	2009 IEEE International Conference on Mechatronics and Automation, ICMA 2009
Publisher	IEEE
Pages	3229-3234
Number of pages	6
ISBN (Electronic)	9781424426935
ISBN (Print)	978-1-4244-2692-8
DOIs	https://doi.org/10.1109/ICMA.2009.5246209
Publication status	Published - 1 Dec 2009
Event	2009 IEEE International Conference on Mechatronics and Automation, ICMA 2009 - Changchun, China Duration: 9 Aug 2009 → 12 Aug 2009

Conference

Conference	2009 IEEE International Conference on Mechatronics and Automation, ICMA 2009
Country/Territory	China
City	Changchun
Period	9/08/09 → 12/08/09

Keywords

Estimation
Extended Kalman filter
Information fusion
Road friction coefficient
Vehicle state

ASJC Scopus subject areas

Computer Vision and Pattern Recognition
Control and Systems Engineering
Electrical and Electronic Engineering

Access to Document

10.1109/ICMA.2009.5246209

Cite this

Hu, D, Zong, C & Na, H 2009, Research on information fusion algorithm for vehicle speed information and road adhesion property estimation. in 2009 IEEE International Conference on Mechatronics and Automation, ICMA 2009., 5246209, IEEE, pp. 3229-3234, 2009 IEEE International Conference on Mechatronics and Automation, ICMA 2009, Changchun, China, 9/08/09. https://doi.org/10.1109/ICMA.2009.5246209

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title = "Research on information fusion algorithm for vehicle speed information and road adhesion property estimation",

abstract = "To achieve the vehicle speed information and tire-road adhesion property is very important to the vehicle active safety control system. And how to utilize the sensors in vehicle to educe the needed information for these systems while ensuring the accuracy and real-time performance has great significance. In this paper, the state estimation theory of information fusion technology is applied to estimate the vehicle speed and tire-road friction coefficient based on a 3-degree-of-freedom vehicle model containing modified Dugoff tire model, which can not only satisfy the accuracy but also explain the relation of tire-road. Due to the nonlinear characteristic of tireroad behavior, the Extended Kalman Filter (EKJo') is applied. By comparing with the outputs signals from CarSim, high accuracy as well as effective availability of this algorithm have been demonstrated.",

keywords = "Estimation, Extended Kalman filter, Information fusion, Road friction coefficient, Vehicle state",

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note = "2009 IEEE International Conference on Mechatronics and Automation, ICMA 2009 ; Conference date: 09-08-2009 Through 12-08-2009",

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N2 - To achieve the vehicle speed information and tire-road adhesion property is very important to the vehicle active safety control system. And how to utilize the sensors in vehicle to educe the needed information for these systems while ensuring the accuracy and real-time performance has great significance. In this paper, the state estimation theory of information fusion technology is applied to estimate the vehicle speed and tire-road friction coefficient based on a 3-degree-of-freedom vehicle model containing modified Dugoff tire model, which can not only satisfy the accuracy but also explain the relation of tire-road. Due to the nonlinear characteristic of tireroad behavior, the Extended Kalman Filter (EKJo') is applied. By comparing with the outputs signals from CarSim, high accuracy as well as effective availability of this algorithm have been demonstrated.

AB - To achieve the vehicle speed information and tire-road adhesion property is very important to the vehicle active safety control system. And how to utilize the sensors in vehicle to educe the needed information for these systems while ensuring the accuracy and real-time performance has great significance. In this paper, the state estimation theory of information fusion technology is applied to estimate the vehicle speed and tire-road friction coefficient based on a 3-degree-of-freedom vehicle model containing modified Dugoff tire model, which can not only satisfy the accuracy but also explain the relation of tire-road. Due to the nonlinear characteristic of tireroad behavior, the Extended Kalman Filter (EKJo') is applied. By comparing with the outputs signals from CarSim, high accuracy as well as effective availability of this algorithm have been demonstrated.

KW - Estimation

KW - Extended Kalman filter

KW - Information fusion

KW - Road friction coefficient

KW - Vehicle state

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Research on information fusion algorithm for vehicle speed information and road adhesion property estimation

Abstract

Conference

Keywords

ASJC Scopus subject areas

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