Abstract
Urban rail transit is in a booming stage in China. Rail transit has the advantages of large capacity, fast speed, safety, punctuality, energy conservation and land use. However, neither the number of urban rail transit stations nor the density of the network can be compared with conventional buses. The coverage is limited and the accessibility is relatively low. Therefore, only by effectively connecting with other modes of transportation, rail transit can attract more passenger flows and give full play to the service capabilities of urban rail systems. This article first combs the related theories of the Nested Logit model, builds the Nested Logit model on this basis, and assigns and calibrates the variables and parameters of the model. Finally, the model established in this study was tested, and it was found that the model variables established in this paper were selected correctly, the fitting effect was good, and the vehicle branch structure model had high accuracy.
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Liu, T. (2021). Selection of Urban Rail Transit Connection Mode Under Nested Logit Model. In: Sugumaran, V., Xu, Z., Zhou, H. (eds) Application of Intelligent Systems in Multi-modal Information Analytics. MMIA 2020. Advances in Intelligent Systems and Computing, vol 1234. Springer, Cham. https://doi.org/10.1007/978-3-030-51556-0_11
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DOI: https://doi.org/10.1007/978-3-030-51556-0_11
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