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A traffic flow cellular automaton model to considering drivers' learning and forgetting behaviour |
Ding Jian-Xun(丁建勋), Huang Hai-Jun(黄海军)†, and Tian Qiong(田琼) |
School of Economics and Management, Beihang University, Beijing 100191, China |
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Abstract It is known that the commonly used NaSch cellular automaton (CA) model and its modifications can help explain the internal causes of the macro phenomena of traffic flow. However, the randomization probability of vehicle velocity used in these models is assumed to be an exogenous constant or a conditional constant, which cannot reflect the learning and forgetting behaviour of drivers with historical experiences. This paper further modifies the NaSch model by enabling the randomization probability to be adjusted on the bases of drivers' memory. The Markov properties of this modified model are discussed. Analytical and simulation results show that the traffic fundamental diagrams can be indeed improved when considering drivers' intelligent behaviour. Some new features of traffic are revealed by differently combining the model parameters representing learning and forgetting behaviour.
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Received: 26 July 2010
Revised: 30 August 2010
Accepted manuscript online:
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PACS:
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89.40.-a
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(Transportation)
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45.70.Vn
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(Granular models of complex systems; traffic flow)
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64.60.Ak
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Fund: Project supported by the National Natural Science Foundation of China (Grant No. 70821061) and the National Basic Research Program of China (Grant No. 2006CB705503). |
Cite this article:
Ding Jian-Xun(丁建勋), Huang Hai-Jun(黄海军), and Tian Qiong(田琼) A traffic flow cellular automaton model to considering drivers' learning and forgetting behaviour 2011 Chin. Phys. B 20 028901
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