A fluid flow model for SCTP traffic over the Internet

Author(s):  
Peer Azmat Shah ◽  
Sadaf Yasmin ◽  
Sohail Asghar ◽  
Amir Qayyum ◽  
Halabi B Hasbullah
Keyword(s):  
2018 ◽  
Vol 9 (7) ◽  
pp. 871-879
Author(s):  
Rajesh Shrivastava ◽  
R. S. Chandel ◽  
Ajay Kumar ◽  
Keerty Shrivastava and Sanjeet Kumar

1995 ◽  
Vol 78 (9) ◽  
pp. 2497-2503 ◽  
Author(s):  
Rangarajan Pitchumani ◽  
Vistasp M. Karbhari

The traffic flow conditions in developing countries are predominantly heterogeneous. The early developed traffic flow models have been derived from fluid flow to capture the behavior of the traffic. The very first two-equation model derived from fluid flow is known as the Payne-Whitham or PW Model. Along with the traffic flow, this model also captures the traffic acceleration. However, the PW model adopts a constant driver behavior which cannot be ignored, especially in the situation of heterogeneous traffic.This research focuses on testing the PW model and its suitability for heterogeneous traffic conditions by observing the model response to a bottleneck on a circular road. The PW model is mathematically approximated using the Roe Decomposition and then the performance of the model is observed using simulations.


Author(s):  
Paulus Setiawan Suryadjaja ◽  
◽  
Maclaurin Hutagalung ◽  
Herman Yoseph Sutarto ◽  
◽  
...  

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-basedmost 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 DipatiukurRoad, Bandung. The proposed model has accuracy with MAPE value below 10%, or falls into highly accurate categories


2017 ◽  
pp. 115-126
Author(s):  
Steve Davies ◽  
Mary Sharpe ◽  
Daniel T. Wilcox

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