Application of Cross-Nested Logit Model to Mode Choice in Tel Aviv, Israel, Metropolitan Area

Author(s):  
Peter Vovsha

Currently, modal split modeling is done mainly by means of disaggregated mode choice models. The almost absolute dominance of multinomial and nested logit models over other mode choice models among applied transportation modelers is attributable to their theoretical soundness, to their simple and understandable analytical structure, and to the calibration procedures that have been developed. Typical urban transport systems, however, are characterized by a variety of modes including private (automobile), public transit (bus, suburban rail, light rail, and subway), and various combinations of these. Analysis reveals that the nested logit model based on the assumption of groupwise similarities among modes is not a suitable modeling tool in such situations. A cross-nested model that is derived from the generalized extreme value class and that can be thought of as a generalization of the nested logit model is proposed. The model takes into account the cross similarities between different pure and combined modes. The cross-nested structure allows for the introduction of the differentiated measurement of pairwise similarities among modes as opposed to the inflexible groupwise similarities permitted by the nested logit model. The proposed model is described, and it is compared with alternative modeling constructs.

Author(s):  
J. N. Prashker ◽  
S. Bekhor

The network loading process of stochastic traffic assignment is investigated. A central issue in the assignment problem is the behavioral assumption governing route choice, which concerns the definition of available routes and the choice model. These two problems are addressed and reviewed. Although the multinomial logit model can be implemented efficiently in stochastic network loading algorithms, the model suffers from theoretical drawbacks, some of them arising from the independence of irrelevant alternatives property. As a result, the stochastic loading on routes that share common links is overloaded at the overlapping parts of the routes. Other logit-family models recently have been proposed to overcome some of the theoretical problems while maintaining the convenient analytical structure. Three such models are investigated: the C-logit model, which was specifically defined for route choice; and two general discrete-choice models, the cross-nested logit model and the paired combinatorial logit model. The two latter models are adapted to route choice, and simple network examples are presented to illustrate the performance of the models with respect to the overlapping problem. The results indicate that all three models perform better than does the multinomial logit model. The cross-nested logit model has an advantage over the two other generalized models because it enables performing stochastic loading without route enumeration. The integration of this model with the stochastic equilibrium problem is discussed, and a specific algorithm using the cross-nest logit model is presented for the stochastic loading phase.


2015 ◽  
Vol 44 ◽  
pp. 76-88 ◽  
Author(s):  
Xiao-Shan Lu ◽  
Tian-Liang Liu ◽  
Hai-Jun Huang

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