KSVTs: Towards knowledge-based self-adaptive vehicle trajectory service

Jin Hong Kim; Eun Seok Lee

doi:10.1007/978-94-007-6996-0_40

KSVTs: Towards knowledge-based self-adaptive vehicle trajectory service

Jin Hong Kim
, Eun Seok Lee

Department of Computer Science and Engineering

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

1 Scopus citations

Abstract

The most of very large traffic system by growing the variety of services, the relationships between the vehicle network and the infrastructure are more complex. Moreover, intelligent transportation systems are getting more and more to develop a better combination of travel safety and efficiency since long time ago. Vehicle is being evolved and traffic environment is especially also organized well-defined schedules priorities, which is real time based wireless network traffic condition, variable traffic condition, and traffic pattern from the vehicle navigation system. Accordingly, we propose to Knowledge-based Self-adaptive Vehicle Trajectory Service using genetic algorithm in this paper.

Original language	English
Title of host publication	Information Technology Convergence
Subtitle of host publication	Security, Robotics, Automations and Communication
Publisher	Springer Verlag
Pages	387-393
Number of pages	7
ISBN (Print)	9789400769953
DOIs	https://doi.org/10.1007/978-94-007-6996-0_40
State	Published - 2013
Event	5th FTRA International Conference on Information Technology Convergence and Services, ITCS 2013 and the 3rd International Conference on Intelligent Robotics, Automations, Telecommunication Facilities, and Applications, IRoA 2013 - Fukuoka, Japan Duration: 8 Jul 2013 → 10 Jul 2013

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	253 LNEE
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	5th FTRA International Conference on Information Technology Convergence and Services, ITCS 2013 and the 3rd International Conference on Intelligent Robotics, Automations, Telecommunication Facilities, and Applications, IRoA 2013
Country/Territory	Japan
City	Fukuoka
Period	8/07/13 → 10/07/13

UN SDGs

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

SDG 11 Sustainable Cities and Communities

Keywords

Intelligent transportation system (ITS)
Knowledge-based trajectory data (KTD)
Self-adaptive trajectory service (STS)
Vehicle network

Access to Document

10.1007/978-94-007-6996-0_40

Cite this

@inproceedings{fea2b434bbb84999b15eef920a67f81d,

title = "KSVTs: Towards knowledge-based self-adaptive vehicle trajectory service",

abstract = "The most of very large traffic system by growing the variety of services, the relationships between the vehicle network and the infrastructure are more complex. Moreover, intelligent transportation systems are getting more and more to develop a better combination of travel safety and efficiency since long time ago. Vehicle is being evolved and traffic environment is especially also organized well-defined schedules priorities, which is real time based wireless network traffic condition, variable traffic condition, and traffic pattern from the vehicle navigation system. Accordingly, we propose to Knowledge-based Self-adaptive Vehicle Trajectory Service using genetic algorithm in this paper.",

keywords = "Intelligent transportation system (ITS), Knowledge-based trajectory data (KTD), Self-adaptive trajectory service (STS), Vehicle network",

author = "Kim, \{Jin Hong\} and Lee, \{Eun Seok\}",

year = "2013",

doi = "10.1007/978-94-007-6996-0\_40",

language = "English",

isbn = "9789400769953",

series = "Lecture Notes in Electrical Engineering",

publisher = "Springer Verlag",

pages = "387--393",

booktitle = "Information Technology Convergence",

note = "5th FTRA International Conference on Information Technology Convergence and Services, ITCS 2013 and the 3rd International Conference on Intelligent Robotics, Automations, Telecommunication Facilities, and Applications, IRoA 2013 ; Conference date: 08-07-2013 Through 10-07-2013",

}

Kim, JH & Lee, ES 2013, KSVTs: Towards knowledge-based self-adaptive vehicle trajectory service. in Information Technology Convergence: Security, Robotics, Automations and Communication. Lecture Notes in Electrical Engineering, vol. 253 LNEE, Springer Verlag, pp. 387-393, 5th FTRA International Conference on Information Technology Convergence and Services, ITCS 2013 and the 3rd International Conference on Intelligent Robotics, Automations, Telecommunication Facilities, and Applications, IRoA 2013, Fukuoka, Japan, 8/07/13. https://doi.org/10.1007/978-94-007-6996-0_40

KSVTs: Towards knowledge-based self-adaptive vehicle trajectory service. / Kim, Jin Hong; Lee, Eun Seok.
Information Technology Convergence: Security, Robotics, Automations and Communication. Springer Verlag, 2013. p. 387-393 (Lecture Notes in Electrical Engineering; Vol. 253 LNEE).

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

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AU - Kim, Jin Hong

AU - Lee, Eun Seok

PY - 2013

Y1 - 2013

N2 - The most of very large traffic system by growing the variety of services, the relationships between the vehicle network and the infrastructure are more complex. Moreover, intelligent transportation systems are getting more and more to develop a better combination of travel safety and efficiency since long time ago. Vehicle is being evolved and traffic environment is especially also organized well-defined schedules priorities, which is real time based wireless network traffic condition, variable traffic condition, and traffic pattern from the vehicle navigation system. Accordingly, we propose to Knowledge-based Self-adaptive Vehicle Trajectory Service using genetic algorithm in this paper.

AB - The most of very large traffic system by growing the variety of services, the relationships between the vehicle network and the infrastructure are more complex. Moreover, intelligent transportation systems are getting more and more to develop a better combination of travel safety and efficiency since long time ago. Vehicle is being evolved and traffic environment is especially also organized well-defined schedules priorities, which is real time based wireless network traffic condition, variable traffic condition, and traffic pattern from the vehicle navigation system. Accordingly, we propose to Knowledge-based Self-adaptive Vehicle Trajectory Service using genetic algorithm in this paper.

KW - Intelligent transportation system (ITS)

KW - Knowledge-based trajectory data (KTD)

KW - Self-adaptive trajectory service (STS)

KW - Vehicle network

UR - https://www.scopus.com/pages/publications/84881185104

U2 - 10.1007/978-94-007-6996-0_40

DO - 10.1007/978-94-007-6996-0_40

M3 - Conference contribution

AN - SCOPUS:84881185104

SN - 9789400769953

T3 - Lecture Notes in Electrical Engineering

SP - 387

EP - 393

BT - Information Technology Convergence

PB - Springer Verlag

Y2 - 8 July 2013 through 10 July 2013

ER -

KSVTs: Towards knowledge-based self-adaptive vehicle trajectory service

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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Cite this