Using the Kalman filter for purposes of road condition assessment

Marcin Staniek

doi:10.1007/978-3-030-35543-2_20

Using the Kalman filter for purposes of road condition assessment

Marcin Staniek

Department of Transport Systems, Traffic Engineering and Logistics (RT/RT4)

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

1 Citation (Scopus)

Abstract

This article provides a discussion on the use of the Kalman filter at the stage of analysis of vehicle motion dynamics to assess the condition of the road transport infrastructure. The tool used to record the vehicle motion dynamics was the Road Condition Tool application designed and implemented as a part of the international S-mile project under the programme entitled ERA-NET: Transport – Sustainable logistics and supply chains. An outcome of the data recording and analysis is a description of the operating condition of road pavements. The concept addressed in the study, namely the implementation of the Kalman filter at the data analysis stage, makes it possible to reduce the input data set, which affects the measuring tool’s response time. On the other hand, the adopted signal filtration procedure allows for the infrastructure condition to be described in a more favourable manner from the perspective of the conclusions to be formulated.

Original language	English
Title of host publication	Smart and Green Solutions for Transport Systems - 16th Scientific and Technical Conference on Transport Systems. Theory and Practice, TSTP 2019, Selected Papers
Editors	Grzegorz Sierpinski
Publisher	Springer
Pages	254-264
Number of pages	11
ISBN (Print)	9783030355425
DOIs	https://doi.org/10.1007/978-3-030-35543-2_20
Publication status	Published - 2020
Event	16th Scientific and Technical Conference on Transport Systems Theory and Practice, TSTP 2019 - Katowice, Poland Duration: 16 Sept 2019 → 18 Sept 2019

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	1091 AISC
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Conference

Conference	16th Scientific and Technical Conference on Transport Systems Theory and Practice, TSTP 2019
Country/Territory	Poland
City	Katowice
Period	16/09/19 → 18/09/19

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure
SDG 11 Sustainable Cities and Communities
SDG 12 Responsible Consumption and Production

Keywords

Assessment of road infrastructure
ICT application
Road pavement condition
Smart city
Vehicle motion dynamics

ASJC Scopus subject areas

Control and Systems Engineering
General Computer Science

Access to Document

10.1007/978-3-030-35543-2_20

Cite this

Staniek, M. (2020). Using the Kalman filter for purposes of road condition assessment. In G. Sierpinski (Ed.), Smart and Green Solutions for Transport Systems - 16th Scientific and Technical Conference on Transport Systems. Theory and Practice, TSTP 2019, Selected Papers (pp. 254-264). (Advances in Intelligent Systems and Computing; Vol. 1091 AISC). Springer. https://doi.org/10.1007/978-3-030-35543-2_20

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title = "Using the Kalman filter for purposes of road condition assessment",

abstract = "This article provides a discussion on the use of the Kalman filter at the stage of analysis of vehicle motion dynamics to assess the condition of the road transport infrastructure. The tool used to record the vehicle motion dynamics was the Road Condition Tool application designed and implemented as a part of the international S-mile project under the programme entitled ERA-NET: Transport {\textendash} Sustainable logistics and supply chains. An outcome of the data recording and analysis is a description of the operating condition of road pavements. The concept addressed in the study, namely the implementation of the Kalman filter at the data analysis stage, makes it possible to reduce the input data set, which affects the measuring tool{\textquoteright}s response time. On the other hand, the adopted signal filtration procedure allows for the infrastructure condition to be described in a more favourable manner from the perspective of the conclusions to be formulated.",

keywords = "Assessment of road infrastructure, ICT application, Road pavement condition, Smart city, Vehicle motion dynamics",

author = "Marcin Staniek",

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Staniek, M 2020, Using the Kalman filter for purposes of road condition assessment. in G Sierpinski (ed.), Smart and Green Solutions for Transport Systems - 16th Scientific and Technical Conference on Transport Systems. Theory and Practice, TSTP 2019, Selected Papers. Advances in Intelligent Systems and Computing, vol. 1091 AISC, Springer, pp. 254-264, 16th Scientific and Technical Conference on Transport Systems Theory and Practice, TSTP 2019, Katowice, Poland, 16/09/19. https://doi.org/10.1007/978-3-030-35543-2_20

Using the Kalman filter for purposes of road condition assessment. / Staniek, Marcin.
Smart and Green Solutions for Transport Systems - 16th Scientific and Technical Conference on Transport Systems. Theory and Practice, TSTP 2019, Selected Papers. ed. / Grzegorz Sierpinski. Springer, 2020. p. 254-264 (Advances in Intelligent Systems and Computing; Vol. 1091 AISC).

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

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T1 - Using the Kalman filter for purposes of road condition assessment

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N2 - This article provides a discussion on the use of the Kalman filter at the stage of analysis of vehicle motion dynamics to assess the condition of the road transport infrastructure. The tool used to record the vehicle motion dynamics was the Road Condition Tool application designed and implemented as a part of the international S-mile project under the programme entitled ERA-NET: Transport – Sustainable logistics and supply chains. An outcome of the data recording and analysis is a description of the operating condition of road pavements. The concept addressed in the study, namely the implementation of the Kalman filter at the data analysis stage, makes it possible to reduce the input data set, which affects the measuring tool’s response time. On the other hand, the adopted signal filtration procedure allows for the infrastructure condition to be described in a more favourable manner from the perspective of the conclusions to be formulated.

AB - This article provides a discussion on the use of the Kalman filter at the stage of analysis of vehicle motion dynamics to assess the condition of the road transport infrastructure. The tool used to record the vehicle motion dynamics was the Road Condition Tool application designed and implemented as a part of the international S-mile project under the programme entitled ERA-NET: Transport – Sustainable logistics and supply chains. An outcome of the data recording and analysis is a description of the operating condition of road pavements. The concept addressed in the study, namely the implementation of the Kalman filter at the data analysis stage, makes it possible to reduce the input data set, which affects the measuring tool’s response time. On the other hand, the adopted signal filtration procedure allows for the infrastructure condition to be described in a more favourable manner from the perspective of the conclusions to be formulated.

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KW - ICT application

KW - Road pavement condition

KW - Smart city

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Staniek M. Using the Kalman filter for purposes of road condition assessment. In Sierpinski G, editor, Smart and Green Solutions for Transport Systems - 16th Scientific and Technical Conference on Transport Systems. Theory and Practice, TSTP 2019, Selected Papers. Springer. 2020. p. 254-264. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-030-35543-2_20

Using the Kalman filter for purposes of road condition assessment

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this