Simultaneous estimation of residential, workplace location and travel mode choice based on Nested Logit model

2010 ◽  
Author(s):  
Xia Li ◽  
Chunfu Shao ◽  
Liya Yang
Keyword(s):  
Logit Model ◽  
Mode Choice ◽  
Simultaneous Estimation ◽  
Nested Logit ◽  
Nested Logit Model ◽  
Travel Mode ◽  
Travel Mode Choice

Study of Travel Mode Choice Behavior Based on Nested Logit Model

2012 ◽  
Vol 253-255 ◽  
pp. 1345-1350
Author(s):  
Bin Shang ◽  
Xiao Ning Zhang
Keyword(s):  
Choice Behavior ◽  
Likelihood Function ◽  
Stated Preference ◽  
Mode Choice ◽  
Estimation Method ◽  
Simultaneous Estimation ◽  
Nested Logit ◽  
Travel Mode ◽  
Factors Affecting ◽  
Travel Mode Choice

Not only multinomial logit (ML) model is usually used in the analysis of travel mode split, but also nested logit (NL) with the method of phased estimation is used. NL model was developed in the paper which used the simultaneous estimation method to analyze travel mode choice behavior on the basis of the basic theory of disaggregate model and data of stated preference survey (SP). In the course of estimating the parameters, the multi-constrained optimization function in optimal tool of MATLAB was used to solve the maximum likelihood function. Using this method, the parameters of model could be calibrated at the same time. The hit ratios are also accurate. It is found that the NL model approach can consider more factors affecting the travel mode choice of residents, improve the prediction accuracy of model and practicality.

Pricing and mode choice based on nested logit model with trip-chain costs

2015 ◽  
Vol 44 ◽  
pp. 76-88 ◽  
Author(s):  
Xiao-Shan Lu ◽  
Tian-Liang Liu ◽  
Hai-Jun Huang
Keyword(s):  
Logit Model ◽  
Mode Choice ◽  
Nested Logit ◽  
Nested Logit Model ◽  
Trip Chain

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

1997 ◽  
Vol 1607 (1) ◽  
pp. 6-15 ◽  
Author(s):  
Peter Vovsha
Keyword(s):  
Logit Model ◽  
Mode Choice ◽  
Choice Models ◽  
Urban Transport ◽  
Transport Systems ◽  
Light Rail ◽  
Nested Logit ◽  
Nested Logit Model ◽  
Proposed Model ◽  
The Cross

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.

Sign in / Sign up

Export Citation Format

Share Document