Gravity Model for Transportation Network Based on Optimal Expected Traffic
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作者:
Qian, Jiang-Hai
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E China Normal Univ, Sch Informat Sci & Technol, Shanghai 200241, Peoples R ChinaE China Normal Univ, Sch Informat Sci & Technol, Shanghai 200241, Peoples R China
Qian, Jiang-Hai
[1
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Han, Ding-Ding
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E China Normal Univ, Sch Informat Sci & Technol, Shanghai 200241, Peoples R ChinaE China Normal Univ, Sch Informat Sci & Technol, Shanghai 200241, Peoples R China
Han, Ding-Ding
[1
]
机构:
[1] E China Normal Univ, Sch Informat Sci & Technol, Shanghai 200241, Peoples R China
We propose a spatial network model for transportation system based on the optimal expected traffic. The expected traffic represents the prediction of the flow created by two vertices and is calculated by the improved gravity equation w(ij) = (KMiMj alpha)-M-alpha/D-ij(gamma). The model maximizes the toe, tal expected traffic of the network. By changing the two parameters a and gamma which controls the fitness and the geographical constraints, the model can vary its topology from the star-like network to the decentralized road-like network. The simulation for the Chinese city airline network reproduced many properties of the real network. In the end of this paper the relationship of the expected traffic and the real traffic is discussed.
机构:
Silesian University of Technology, Faculty of Transport, Department of Transportation Systems and Traffic Engineering, Katowice, PolandSilesian University of Technology, Faculty of Transport, Department of Transportation Systems and Traffic Engineering, Katowice, Poland
Karoń, Grzegorz
Zochowska, Renata
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Silesian University of Technology, Faculty of Transport, Department of Transportation Systems and Traffic Engineering, Katowice, PolandSilesian University of Technology, Faculty of Transport, Department of Transportation Systems and Traffic Engineering, Katowice, Poland
机构:
LONDON GRAD SCH BUSINESS STUDIES,TRANSPORT NETWORK THEORY UNIT,LONDON,ENGLANDLONDON GRAD SCH BUSINESS STUDIES,TRANSPORT NETWORK THEORY UNIT,LONDON,ENGLAND