Path Size Modeling in Multimodal Route Choice Analysis

Author(s):  
Sascha Hoogendoorn-Lanser ◽  
Rob van Nes ◽  
Piet Bovy

Travelers in multimodal networks make many choices (e.g., main mode, access modes, egress modes, boarding nodes, transfer nodes, and egress nodes). One way to address this complexity of choices is to analyze choice sets of multimodal routes. However, choice sets for multimodal networks are large, and overlap of routes within choice sets is substantial. This paper focuses on overlap in multimodal transport networks. An overview of the topic of overlap and route choice modeling is given and is followed by an analysis of how overlap might be defined in the context of multimodal networks. Three definitions of “overlap” are proposed, based on number of legs, time, or distance. The different definitions are analyzed using path size logit estimations, which show that path size must be accounted for. Furthermore, the definition of “path size” for multimodal transport networks should be different from that used for road networks: for multimodal transport networks, a definition using number of legs yields substantially better results. Estimation results suggest that the weighting parameter corresponding with the path size variable should be equal to 1, implying that the path size variable based on number of legs accounts for the correlation of error terms of overlapping parts.

2009 ◽  
Vol 2009 ◽  
pp. 1-15 ◽  
Author(s):  
Carlos Galvez-Fernandez ◽  
Djamel Khadraoui ◽  
Hedi Ayed ◽  
Zineb Habbas ◽  
Enrique Alba

This paper presents an alternative approach for time-dependent multimodal transport problem. We describe a new graph structure to abstract multimodal networks, calledtransfer graph, which adapts to the distributed nature of real information sources of transportation networks. A decomposition of the Shortest Path Problem intransfer graphis proposed to optimize the computation time. This approach was computationally tested in several experimental multimodal networks having different size and complexity. The approach was integrated in the multimodal transport service of the European Carlink platform, where it has been validated in real scenarios. Comparision with other related works is provided.


Author(s):  
A. B. Pleasants ◽  
G. C. Wake ◽  
A. L. Rae

AbstractThe allometric hypothesis which relates the shape (y) of biological organs to the size of the plant or animal (x), as a function of the relative growth rates, is ubiquitous in biology. This concept has been especially useful in studies of carcass composition of farm animals, and is the basis for the definition of maintenance requirements in animal nutrition.When the size variable is random the differential equation describing the relative growth rates of organs becomes a stochastic differential equation, with a solution different from that of the deterministic equation normally used to describe allometry. This is important in studies of carcass composition where animals are slaughtered in different sizes and ages, introducing variance between animals into the size variable.This paper derives an equation that relates values of the shape variable to the expected values of the size variable at any point. This is the most easily interpreted relationship in many applications of the allometric hypothesis such as the study of the development of carcass composition in domestic animals by serial slaughter. The change in the estimates of the coefficients of the allometric equation found through the usual deterministc equation is demonstrated under additive and multiplicative errors. The inclusion of a factor based on the reciprocal of the size variable to the usual log - log regression equation is shown to produce unbiased estimates of the parameters when the errors can be assumed to be multiplicative.The consequences of stochastic size variables in the study of carcass composition are discussed.


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