Geographical Information System for Mapping Accident-Prone Roads and Development of New Road Using Multi-Attribute Utility Method

Anik Vega, Vitianingsih and Dwi, Cahyono (2017) Geographical Information System for Mapping Accident-Prone Roads and Development of New Road Using Multi-Attribute Utility Method. In: 2016 2nd International Conference on Science and Technology-Computer (ICST), 27-28 October 2016, Yogyakarta, Indonesia.

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Official URL: https://ieeexplore.ieee.org/document/7877349

Abstract

The means of transportation development which are not offset by adequate roads construction will lead the traffic density exceeds the volume capacity of the roads. This will cause the access road difficult to pass thus often raises the risk of traffic congestion and lead to traffic accidents. This paper will discuss the use of Geographical Information System (GIS) technology in analyzing spatial data and attribute data (geoprocessing layer) in the form of mapping accident-prone roads and mapping dense traffic lanes as an alternative to the development of new road using Multiple-Attribute Utility Theory (MAUT) method. Geoprocessing layer test conducted on the roads in Gresik District, Indonesia shows the accident-prone roads mapping points, with the average yield of low-risk accident-prone roads are 58%, 24% are low-risk accident-prone roads and 18% roads condition are high-risk accident-prone roads. Geoprocessing for alternative development of new road as the consequences of the density of traffic lanes, in which the uncrowded road categories are 36%, dense road 32% and very dense roads 32%. This system can be used by the government of Gresik District as the decision makers to plan for the alternative development of new road area, therefore traffic density can be minimized.

Item Type: Conference or Workshop Item (Keynote)
Uncontrolled Keywords: GIS; MAUT; geoprocessing, layer, dense traffic lanes; accident-prone lanes
Subjects: T Technology > TE Highway engineering. Roads and pavements
Divisions: Fakultas Teknik > Teknik Informatika
Depositing User: Vega Vitianingsih
Date Deposited: 17 Jan 2023 14:43
Last Modified: 17 Jan 2023 14:43
URI: http://repository.unitomo.ac.id/id/eprint/3382

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