Design of Smart Vehicular Traffic Network for Self-Adaptive Prediction Service (자가 적응형 예측 서비스를 위한 스마트 차량 네트워크 설계)

Ahn cheolbum (안철범); KIM, JIN HONG (김진홍)

doi:10.34163/jkits.2020.15.6.014

Design of Smart Vehicular Traffic Network for Self-Adaptive Prediction Service

Journal of Knowledge Information Technology and Systems
Abbr : JKITS
2020, 15(6), pp.1065-1073
DOI : 10.34163/jkits.2020.15.6.014
Publisher : Korea Knowledge Information Technology Society
Research Area : Interdisciplinary Studies > Interdisciplinary Research
Received : September 23, 2020
Accepted : December 11, 2020
Published : December 31, 2020

Ahn cheolbum ¹, KIM, JIN HONG ²

¹서일대학교
²배재대학교

Accredited

ABSTRACT

Recently, A variety of vehicular network services are key technologies to estimate that vehicle could be located, and Intelligent Transportation Systems have a solution to this problem. In addition, Vehicular Ad hoc Networks emerge as ITS component that provides cooperative communication with vehicles and the necessary infrastructure to improve the flow of vehicles in cities. By the result, it has been a proliferation of challenges for authorities with regard to traffic management. Especially, according to consequence of congestion on traffic, accidents, and pollution, they are a still major cause, despite the development of well-made systems for traffic management and other technologies linked with vehicles. After all, it is necessary that a general system for accident management is developed. Such as, traffic congestion in most urban areas can be alleviated by the real-time planning of routes. Nevertheless, the designing of an efficient route planning algorithm to attain a globally optimal vehicle control is still a challenge that needs to be solved, particularly when the unique preferences of drivers are considered. The development of the vehicular network prediction algorithms using dynamic models, often required building a system model with complex equations. Accordingly, we propose the protocol of vehicular traffic that will receive a popular interesting in the vehicular network service in this paper. It has proven the usefulness of the system in order to apply toward an existing vehicular communication network. Among the experimented existing algorithm performance, we confirmed the effectiveness of all range from a single data, to verify the proposed algorithm.

KEYWORDS

Vehicular network services, Intelligent transportation system, Traffic management, Realtime planning, Vehicular network prediction algorithms, Vehicular communi- cation network

Citation status

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Journal of Knowledge Information Technology and Systems 2023 KCI Impact Factor : 0.89

Design of Smart Vehicular Traffic Network for Self-Adaptive Prediction Service

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Citation status

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

Journal of Knowledge Information Technology and Systems 2023 KCI Impact Factor : 0.89

Design of Smart Vehicular Traffic Network for Self-Adaptive Prediction Service

ABSTRACT

KEYWORDS

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