A study of a main-road cellular automata traffic flow model

2002 ◽  
Vol 11 (7) ◽  
pp. 678-683 ◽  
Author(s):  
Huang Ping-Hua ◽  
Kong Ling-Jiang ◽  
Liu Mu-Ren
2012 ◽  
Vol 54 ◽  
pp. 1350-1359 ◽  
Author(s):  
Öznur Yeldan ◽  
Alberto Colorni ◽  
Alessandro Luè ◽  
Emanuele Rodaro

2003 ◽  
Vol 14 (10) ◽  
pp. 1295-1303 ◽  
Author(s):  
BIN JIA ◽  
RUI JIANG ◽  
QING-SONG WU

As a kind of bottleneck, the lane closing has seldomly been investigated with cellular automata model. In this paper, we study this issue using the cellular automata traffic flow model. The capacity and the density distribution of this kind of bottleneck are discussed in details. We find that (i) the capacity of the bottleneck is a little smaller than the maximum flow rate of single-lane road; (ii) different regulations may lead to different density distributions of the vehicles upstream of the lane closing. Moreover, the density inversion phenomenon is reported under certain conditions. This enlightens us to propose that the phenomenon of density inversion reported in many publications may be caused by the bottlenecks on the highway.


2019 ◽  
Vol 33 (20) ◽  
pp. 1950228 ◽  
Author(s):  
Yu-Qing Wang ◽  
Chao-Fan Zhou ◽  
Jia-Wei Wang ◽  
Xin-Peng Ni

Proposing realistic hybrid traffic flow model is a promising and hot topic in the area of fluid mechanics and nonlinear dynamics, since they can take advantages of combining dynamical properties of each individual vehicle and macroscopic characteristics of the global system. In this paper, different from the previous work, we propose a hybrid traffic flow model considering the dynamical competition between ramps and main roads. Afterwards, the dynamical control equations of the proposed system are established. Then, by means of performing finite difference analyses, nonlinear dynamical characteristics and specific properties of the proposed system are investigated. Evolvement laws of characteristic order parameters of the proposed traffic flow system are obtained by analyzing the change of density, velocity and current in various circumstances. Moreover, matrices of partition coefficient are employed into the proposed traffic network composed of a main road and varied ramps. Additionally, linear and nonlinear stability analyses are considered in different phase spaces. Therefore, the robustness of the proposed system is tested by both linear and nonlinear dynamics. Our work will be helpful to understand mesoscopic dynamical behaviors of each individual vehicle and inner interactions between them.


2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Facundo Storani ◽  
Roberta Di Pace ◽  
Francesca Bruno ◽  
Chiara Fiori

Abstract Background This paper compares a hybrid traffic flow model with benchmark macroscopic and microscopic models. The proposed hybrid traffic flow model may be applied considering a mixed traffic flow and is based on the combination of the macroscopic cell transmission model and the microscopic cellular automata. Modelled variables The hybrid model is compared against three microscopic models, namely the Krauß model, the intelligent driver model and the cellular automata, and against two macroscopic models, the Cell Transmission Model and the Cell Transmission Model with dispersion, respectively. To this end, three main applications were considered: (i) a link with a signalised junction at the end, (ii) a signalised artery, and (iii) a grid network with signalised junctions. Results The numerical simulations show that the model provides acceptable results. Especially in terms of travel times, it has similar behaviour to the microscopic model. By contrast, it produces lower values of queue propagation than microscopic models (intrinsically dominated by stochastic phenomena), which are closer to the values shown by the enhanced macroscopic cell transmission model and the cell transmission model with dispersion. The validation of the model regards the analysis of the wave propagation at the boundary region.


2020 ◽  
Vol 16 (4) ◽  
pp. 229
Author(s):  
Changbing Jiang ◽  
Ruolan Li ◽  
Tinggui Chen ◽  
Chonghuan Xu ◽  
ang Li ◽  
...  

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