A cellular automation model for convoy traffic in Arctic waters

2019 ◽  
Vol 164 ◽  
pp. 102783 ◽  
Author(s):  
Bushra Khan ◽  
Faisal Khan ◽  
Brian Veitch
Author(s):  
Yang Zhang ◽  
Changsong Wu ◽  
Yanjia Gao ◽  
Bin Yang

A reconstruction-based image processing algorithm is developed to automatically extract feature points of digitalized 2D objects. This algorithm, which is introduced using a bumblebee flight case, is made up of two parts: a four-connected dot chasing rearrangement scheme and an extreme point extraction on a polarized contour. It is then applied to a dune evolution case that is simulated with a cellular automation model. The results show that the proposed algorithm is effective in characterizing individual moving objects. An additional algorithm is developed to categorize the extracted feature points of a bumblebee with translucent wings.


2004 ◽  
Vol 191 (3-4) ◽  
pp. 343-358 ◽  
Author(s):  
Mark S Alber ◽  
Yi Jiang ◽  
Maria A Kiskowski

2015 ◽  
Vol 29 (26) ◽  
pp. 1550153
Author(s):  
Yong Zhang ◽  
Shi-Gao Li

It is well known that traffic flow presents multi-fractal characteristics at time scales. The aim of this study is to test its multi-fractality at spacial scales. The vehicular cellular automation (CA) model is chosen as a tool to get vehicle positions on a single lane road. First, multi-fractal of vehicle distribution is checked, and multi-fractal spectrums are plotted. Second, analysis results show that the width of a multi-fractal spectrum expresses the ratio of the maximum to minimum densities, and the height difference between the left and right vertexes represents the relative size between the numbers of sections with the maximum and minimum densities. Finally, the effects of the random deceleration probability and the average density on homogeneity of vehicle distribution are analyzed. The results show that random deceleration increases the ratio of the maximum to minimum densities, and deceases the relative size between the numbers of sections with the maximum and minimum densities, when the global density is limited to a specific range. Therefore, the multi-fractal spectrum can be used to quantify the homogeneity of spacial distribution of traffic flow.


2013 ◽  
Vol 409-410 ◽  
pp. 1075-1080
Author(s):  
Lin Peng Kong ◽  
Xing Gang Li

As a typical traffic bottleneck, the freeway weaving section is one source of vehicle conflict and an accident-prone area. This paper presents a cellular automaton model to characterize accident-induced traffic behavior around the weaving section, in which different accident sites are considered. The spatial-temporal profiles are presented after the numerical simulation. It is shown that the accident car not only causes a local jam behind the accident car, but also causes vehicles to cluster in the bypass lane. The accident occurring in lane 1 (the left lane) in the weaving section are more inclined to cause traffic jam and the decrease of traffic capacity than in lane 2 (the right lane). Furthermore, the curves of saturated flux of weaving section against different accident sites are given. It is found that the capacity of weaving section will decrease fastest when the accident is located in the downstream of weaving section.


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