Ofyar Z. Tamin, Heriansyah, Siti Raudhatul Fadilah
Big data is a huge collection of electronic data which is currently popular to be developed in various scientific fields, including the transportation sector. Several data categories that can be used for transportation infrastructure planning are real-time location/position and timestamp of road users. This technological sophistication addresses a very crucial transportation planning problem that has been faced for many years, that is the inaccurate and unrepresentative prediction of the Origin-Destination Matrix. Up to this point, the Origin-Destination Matrix has been obtained using conventional and unconventional methods. Data was collected through manual traffic counts survey and direct interview in the study area. This results in unreliable data and inadequate sampling rates, which are only able to cover 20% of the population. In addition, the application of these techniques is expensive, time-consuming, and require a lot of human resources. Therefore, this study tries to develop a model capable of predicting the origin and destination of mobility, which in this case is represented by the sub-district boundary as a zone. As a result, an Origin-Destination Matrix can be obtained with a high degree of accuracy. The case study used is Bandung city. In the future, this research is expected to become a milestone in elaborating a validated Origin-Destination Matrix estimation model that can be used in various areas. © Published under licence by IOP Publishing Ltd.
Department of Civil Engineering, Institut Teknologi Sumatera, Lampung, Indonesia; Department of Electrical Engineering, Institut Teknologi Sumatera, Lampung, Indonesia; Department of Civil Engineering, Institut Teknologi Bandung, Bandung, Indonesia
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