A Study on the Improvement of VDS Data Collection Algorithm Using Kalman Filter (칼만필터를 활용한 VDS 데이터 수집 알고리즘 개선에 관한 연구)

NakJin Choi (최낙진); SungJin Kim (김성진); YongWan Ju (주용완); Sangmin Suh (서상민); JaeHong Choi (최재홍); Lee Jun Dong (이준동)

doi:10.9708/jksci.2021.26.09.133

A Study on the Improvement of VDS Data Collection Algorithm Using Kalman Filter

Journal of The Korea Society of Computer and Information
Abbr : JKSCI
2021, 26(9), pp.133-141
DOI : 10.9708/jksci.2021.26.09.133
Publisher : The Korean Society Of Computer And Information
Research Area : Engineering > Computer Science
Received : August 26, 2021
Accepted : September 29, 2021
Published : September 30, 2021

NakJin Choi ¹, SungJin Kim ¹, YongWan Ju ¹, Sangmin Suh ¹, JaeHong Choi ¹, Lee Jun Dong ¹

¹강릉원주대학교

Accredited

ABSTRACT

The development and demand for the system that provides users with traffic information and efficient road use have continued. also, this system provides the basic technology of the Intelligent Transport System (ITS). The most used traffic information collection tools are Vehicle detectors (VDS) and short-range wireless communication (DSRC) on express way. In order to generate reliable traffic information, it is necessary to efficiently manage and utilize the collected data as well as high-quality traffic data collection and processing technology. In this study, traffic information collection⋅ processing⋅provision systems were investigated, and analyze the current status and problems of traffic information collected through VDS. Based on this, we would like to present an improved collection algorithm that utilizes the Kalman filter for vehicle information measurement of VDS data. By using the algorithm of this study, it is possible to minimize the time delay of the estimated value as well as the noise removal that inevitably occurs during measurement.

KEYWORDS

ITS, VDS, DSRC, Kalman filter, traffic information

Citation status

* References for papers published after 2023 are currently being built.

[report] KyungPyo Kang / 2010 / A study on how to collect and provide traffic information on urban arterial roads / Korea Transportation Research Institute, Korea Institute of Construction Technology

[other] GyeHyung Ahn / 2010 / The Development and Utilization Plan of Urban Traffic Information System (UTIS) Standard S/W / Transportation technical data 2010-2, Vol. 26

[confproc] DongMin Kim / 2012 / A study on building the platform and development of algorithm for collecting real-time traffic data / The Spring Conference of the Korea Information and Communication Society

[book] G. F. Franklin / 1997 / Digital Control of Dynamic Systems / Addison-Wesley Publishing Company

[web] / 2021 / https://www.gnu.org/software/octave/index / https://www.gnu.org/software/octave/index

[confproc] NakJin Choi / 2021 / A study on the development of a traffic information app to provide highway traffic information using VDS / The Summer Conference of the Korea Society of Computer and Information

[report] / 2020 / Detailed Design of Expressway Traffic Management System (exTMS) for ITS Processing System Reorganization / Korea Expressway Corporation

[report] / 2015 / A study on the integrated traffic data quality monitoring system / Korea Expressway Corporation

[thesis] NakJu Kim / 2011 / Research on establishing a traffic detection system to improve the accuracy of highway traffic information / Ajou University

[report] / 2008 / A study on ITS information reliability improvement and evaluation / Ministry of Land, Infrastructure and Transport

[other] Kumar, Nishant / 2013 / Optimal Design of FIR and IIR Filters using some Evolutionary Algorithms

This paper was written with support from the National Research Foundation of Korea.

KJCKorea
Journal Central

Journal of The Korea Society of Computer and Information 2023 KCI Impact Factor : 0.65

A Study on the Improvement of VDS Data Collection Algorithm Using Kalman Filter

ABSTRACT

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Citation status

* References for papers published after 2023 are currently being built.

Journal of The Korea Society of Computer and Information 2023 KCI Impact Factor : 0.65

A Study on the Improvement of VDS Data Collection Algorithm Using Kalman Filter

ABSTRACT

KEYWORDS

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* References for papers published after 2023 are currently being built.