Authors:
Sung-Phil Heo
1
;
Wansu Lim
1
;
Sung-Chul Hur
2
and
Dong-Seong Kim
1
Affiliations:
1
Kumoh National Institute of Technology, Korea, Republic of
;
2
Samsung Heavy Industries Co. and Ltd., Korea, Republic of
Keyword(s):
Traffic Condition, Location Information, ITS.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence and Decision Support Systems
;
Data Communication Networking
;
Enterprise Information Systems
;
Geographical Information Systems
;
Human-Computer Interaction
;
Intelligent Transportation System
;
Internet of Things
;
Sensor Networks
;
Software Agents and Internet Computing
;
Software and Architectures
;
Telecommunications
Abstract:
With respect to traditional method which relates to identifying a traffic state of a particular road from a remote point, there is a scheme for collecting data sensed by a traffic sensing apparatus of a freeway traffic management system(FTMS), such as a loop type vehicle detector, which is provided on a road to detect traffic states, a video type vehicle sensor, Which is configured to identify traffic states on a road through the use of video photographing, a closed circuit television (CCTV), and an emergency call.. The FTMS is a freeway intelligent traffic system (ITS) constructed by the Korea Highway Corporation to provide users of a freeway with exact road information and to manage traffic conditions. However, in order to implement a system for measuring a speed of a vehicle by using the loop type detection system, installation of a loop coil detector typically requires earthworks and/or other types of construction, thereby causing delay and/or inconvenience in transportation duri
ng the earthworks and/or construction. Further, in order to collect information, it is typically necessary to install a separate private cable or to lease a dedicated line. In this paper, we describe a system for detecting a peripherally located vehicle based on a location of a user or a particular point on a map which point is selected by a user, so as to be provided with traffic images captured by a smart device installed in the detected vehicle.
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