scholarly journals Road Network Traffic Congestion Evaluation Simulation Model based on Complex Network

Author(s):  
Chao Luo
2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Haitao Xu ◽  
Jing Chen ◽  
Jie Xu

An improved model-based predictive control approach integrating model-based signal control and queue spillover control is proposed in this paper, which includes three modules: model-based signal control, queue spillover identification, and spillover control to deal with the problem of traffic congestion for urban oversaturated signalized intersection. The main steps are as follows. First of all, according to the real-time traffic flow data, the green time splits for all intersections will be solved online by the model-based signal control controller whose optimization model is based on model-predictive control (MPC) strategy. Second, the queue spillover identification module will be used to detect the potential queue spillover. If potential queue spillover is detected, the spillover control module will be activated to prevent vehicles from the upstream link of the link with possible spillover from entering the downstream link to avoid traffic congestion. The experiment is performed on a simulated road network. The results verify that the proposed scheme can significantly decrease the delay which reflects the overall performance of the studied intersection.


Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Xin Feng ◽  
Yue Zhang ◽  
Shuo Qian ◽  
Liming Sun

At present, urban traffic congestion is a common problem of urban development in China. Therefore, China’s government issued the policy of opening the gated communities in 2016, hoping to alleviate traffic pressure to some extent. But, at present, the quantitative empirical research on the effect of the policy implementation is less and more idealistic. In order to complete the leap from research on local isolated traffic capacity of static gated communities to research on global coupling traffic capacity of dynamic multilayer network and, to a certain extent, reflect the innovation of the research model and method, we make a quantitative analysis of the effect of the policy more consistent with the actual situation, which provides a quantitative management basis for the implementation of the policy. Based on literature review, this paper carried out two stages of research. Stage one consists of constructing traffic capacity assessment model—Road Capacity Assessment (RCA) model based on BPR (Bureau of Public Roads) impedance function from a simple local static perspective. Considering the factors such as delay of signalized intersection and travel time, through modeling analysis and empirical test, it is found that about 12% of local traffic capacity can be improved after open community. Stage two consists of constructing a global capacity model based on multilayer complex network coupling from the perspective of complex global dynamics. Considering the various network nodes of pedestrians, nonmotor vehicles, and other factors, we construct a multilayer complex network and dynamic superposition coupling. The empirical data show that the overall traffic capacity of the open community is improved by at least 11.3%. Finally, it can be concluded that a significant increase in the global traffic capacity of complex urban road networks means that the losses caused by traffic congestion will be reduced. In some first-tier cities, the direct monthly income of the open-gated community is as high as 230 million yuan, not to mention its overall economic, social, and environmental benefits.


2021 ◽  
Vol 27 (7) ◽  
pp. 369-379
Author(s):  
A. S. Akopov ◽  
◽  
L. A. Beklaryan ◽  
A. L. Beklaryan ◽  
F. A. Belousov ◽  
...  

A new approach to modeling the spatial dynamics of unmanned ground vehicles (UV) and conventional vehicles (CV) using the FLAME GPU supercomputer agent-based simulation platform is presented. A new simulation model of an artificial road network (ARN) of the "Manhattan Grid" type is proposed, within the framework of which the spatial dynamics of the UV and CV ensemble is studied under various scenario conditions. The effects of "turbulence" and "crush" (traffic congestion) resulting from intensive and dense traffic of vehicles are investigated.


2020 ◽  
Vol 17 (2) ◽  
pp. 66-73
Author(s):  
R. D. Oktyabrskiy

The article is devoted to the justification of the need to reduce the population density in the residential development of cities. The analysis of vulnerability of the urban population from threats of emergency situations of peace and war time, and also an assessment of provision of the city by a road network is given. Proposals have been formulated to reduce the vulnerability of the urban population in the long term and to eliminate traffic congestion and congestion — jams.


2021 ◽  
Vol 13 (9) ◽  
pp. 5108
Author(s):  
Navin Ranjan ◽  
Sovit Bhandari ◽  
Pervez Khan ◽  
Youn-Sik Hong ◽  
Hoon Kim

The transportation system, especially the road network, is the backbone of any modern economy. However, with rapid urbanization, the congestion level has surged drastically, causing a direct effect on the quality of urban life, the environment, and the economy. In this paper, we propose (i) an inexpensive and efficient Traffic Congestion Pattern Analysis algorithm based on Image Processing, which identifies the group of roads in a network that suffers from reoccurring congestion; (ii) deep neural network architecture, formed from Convolutional Autoencoder, which learns both spatial and temporal relationships from the sequence of image data to predict the city-wide grid congestion index. Our experiment shows that both algorithms are efficient because the pattern analysis is based on the basic operations of arithmetic, whereas the prediction algorithm outperforms two other deep neural networks (Convolutional Recurrent Autoencoder and ConvLSTM) in terms of large-scale traffic network prediction performance. A case study was conducted on the dataset from Seoul city.


2013 ◽  
Vol 676 ◽  
pp. 321-324
Author(s):  
Lei Guo ◽  
Qun Zhan Li

Accidents of icing on catenary have great impacts on normal operation of trains. An on-line anti-icing technology used static var generator (SVG) for catenary was proposed, which can prevent icing formation without interrupting trains normal operation. The heat balance equations for catenary were solved, whose results were compared with data provided by TB/T 3111 and testing show the equation was correct. The simulation model based on Matlab was bulit , whose results and analysis show the correctness of the method.


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