VALIDASI PENGGUNAAN VIDEO IMAGE RECOGNITION TECHNOLOGY (VIRT) DALAM MENDETEKSI ARUS LALULINTAS
Traffic flow condition is a crucial part on transportation planning. The common method until today to get the traffic data is a manual survei, handled by some surveyors on field. That old fashioned survei is such of waste of time and money. By using VIRT, there are a lot of advantages that we could...
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| Main Authors: | , |
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| 格式: | Theses and Dissertations NonPeerReviewed |
| 出版: |
[Yogyakarta] : Universitas Gadjah Mada
2012
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| 在線閱讀: | https://repository.ugm.ac.id/98737/ http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=54796 |
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| 機構: | Universitas Gadjah Mada |
| 總結: | Traffic flow condition is a crucial part on transportation planning. The common
method until today to get the traffic data is a manual survei, handled by some surveyors
on field. That old fashioned survei is such of waste of time and money. By using VIRT,
there are a lot of advantages that we could reach, such as time and money efficiency.
VIRT method is by placing video camera on specific angle and elevation to get traffic
flow data.
VIRT is a software that developed by UGM�s research team, consists of two
following phases, vehicle detection and vehicle recognition. The first phase is moving
object detection, applying temporal difference method. The second phase is shadow
removal to avoid errors on vehicle type recognition. Segmentation and recognition
method based on feature of area, length, width, used for vehicle type classification. The
vehicle type classification, define as motorcycle, cars, truck etc. obtained from template
matching method. VIRT is able to classify and measure 3 types of vehicle as follows :
Motorcycle (MC), Light Vehicle (LV), and Heavy Vehicle in certain time period.
The validation process is done by comparing two different methods, manual survei
and VIRT. From the validation result using linear regression (scatter diagram and Boxplot
method), is shown that each variabel has a positive correlation. The paired samples T-
Test result shown that from 4 tested variabels (MC, LV, HV, and SMP), LV has 95 % of
confidence level lies in validation test between reality and VIRT. From the analysis using
definite integral to get the correlation between traffic volume and time interval, the HV
has the weakest correlation level because the VIRT doesn�t have enough parameter data
related to this vehicle type.
From the validation process, knows that the VIRT software is a solution in
transport world especially to identify the traffic characteristic on road directly and needs
further developing process in order to get higher accuration and able to detect the traffic
congestion effectively and efficiently. |
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