Modeling Traffic Flows with Fluid Flow Model

Autor: Paulus Setiawan Suryadjaja, Maclaurin Hutagalung, Herman Yoseph Sutarto
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: International Journal of Informatics, Information System and Computer Engineering, Vol 1, Iss 1, Pp 1-12 (2020)
Druh dokumentu: article
ISSN: 2810-0670
2775-5584
DOI: 10.34010/injiiscom.v1i1.4860
Popis: This Research presents a macroscopic model of traffic flow as the basis for making Intelligent Transportation System (ITS). The data used for modeling is The number of passing vehicles per three minutes. The traffic flow model created in The form of Fluid Flow Model (FFM). The parameters in The model are obtained by mixture Gaussian distribution approach. The distribution consists of two Gaussian distributions, each representing the mode of traffic flow. In The distribution, intermode shifting process is illustrated by the first-order Markov chain process. The parameters values are estimated using The Expectation-maximization (EM) algorithm. After The required parameter values are obtained, traffic flow is estimated using the Observation and transition-based most likely estimates Tracking Particle Filter (OTPF). To Examine the accuracy of the model has been made, the model estimation results are compared with the actual traffic flow data. Traffic flow data is collected on Monday 20 September 2017 at 06.00 to 10.00 on Dipatiukur Road, Bandung. The proposed model has accuracy with MAPE value below 10%, or falls into highly accurate categories.
Databáze: Directory of Open Access Journals