scholarly journals Analysis of Mode Choice Models Considering Individual Heterogeneity

1995 ◽  
Vol 12 ◽  
pp. 425-434 ◽  
Author(s):  
Yoriyasu SUGIE ◽  
Junyi ZHANG ◽  
Akimasa FUJIWARA
Keyword(s):  
Mode Choice ◽  
Choice Models ◽  
Individual Heterogeneity

A Selective Review of Travel-Mode Choice Models

1982 ◽  
Vol 8 (4) ◽  
pp. 370 ◽  
Author(s):  
Richard Barff ◽  
David Mackay ◽  
Richard W. Olshavsky
Keyword(s):  
Mode Choice ◽  
Choice Models ◽  
Travel Mode ◽  
Selective Review ◽  
Travel Mode Choice

scholarly journals Mode choice analysis using discrete choice model from transport user (Case study: Jakarta LRT, Indonesia)

2018 ◽  
Vol 181 ◽  
pp. 03001
Author(s):  
Dwi Novi Wulansari ◽  
Milla Dwi Astari
Keyword(s):  
Discrete Choice ◽  
Public Transportation ◽  
Choice Model ◽  
Stated Preference ◽  
Mode Choice ◽  
Choice Models ◽  
Discrete Choice Models ◽  
Light Rail ◽  
Choice Analysis ◽  
Mode Choice Model

Jakarta Light Rail Transit (Jakarta LRT) has been planned to be built as one of mass rail-based public transportation system in DKI Jakarta. The objective of this paper is to obtain a mode choice models that can explain the probability of choosing Jakarta LRT, and to estimate the sensitivity of mode choice if the attribute changes. Analysis of the research conducted by using discrete choice models approach to the behavior of individuals. Choice modes were observed between 1) Jakarta LRT and TransJakarta Bus, 2) Jakarta LRT and KRL-Commuter Jabodetabek. Mode choice model used is the Binomial Logit Model. The research data obtained through Stated Preference (SP) techniques. The model using the attribute influences such as tariff, travel time, headway and walking time. The models obtained are reliable and validated. Based on the results of the analysis shows that the most sensitive attributes affect the mode choice model is the tariff.

scholarly journals Comparison of Different Mode Choice Models for Work Trips using Data Mining Process

2017 ◽  
Vol 10 (17) ◽  
pp. 1-3
Author(s):  
Jayesh Juremalani ◽  
Krupesh A. Chauhan ◽  
◽  
Keyword(s):  
Data Mining ◽  
Mode Choice ◽  
Choice Models ◽  
Using Data

Could a New Mode Alternative Modify Psycho-Attitudinal Factors and Travel Behavior?

2019 ◽  
Vol 2673 (9) ◽  
pp. 94-106
Author(s):  
Eleonora Sottile ◽  
Francesco Piras ◽  
Italo Meloni
Keyword(s):  
Travel Behavior ◽  
Latent Variables ◽  
Mode Choice ◽  
Choice Models ◽  
Individual Characteristics ◽  
Policy Implications ◽  
Light Rail ◽  
Attitudinal Factors ◽  
The Impact ◽  
Over Time

There is ample consensus that, besides objective characteristics, psycho-attitudinal factors play a key role in influencing people’s mode choice. Hybrid choice models use these theoretical frameworks so as to include latent constructs for capturing the impact of subjective factors on mode choice. But recent work in transportation research raised the question about the ability of hybrid choice models to derive policy implications that aim to change travel behavior, given the focus on cross-sectional data. To address this problem we designed a survey for collecting longitudinal data (socio-economic and psycho-attitudinal) to evaluate, on the one hand, the long-term effects on travel mode choice of the implementation of a new light rail line in the metropolitan area of Cagliari (Italy), on the other to detect any changes in the psycho-attitudinal factors and socio-economic characteristics after implementation of those measures. In particular, the objective of the study is to analyze whether these changes in individual characteristics are able to affect mode choice from a modeling perspective, through the specification and estimation of hybrid models. Our results show that latent variables were not significantly different over waves, showing that the impact of the psychological construct remained stable over time, even after the introduction of the new light rail. Additionally, we found some evidence that the variables that explain the latent variables could change over time.

Development of disaggregate mode choice models of intercity travel in Canada

1992 ◽  
Vol 19 (6) ◽  
pp. 965-974 ◽  
Author(s):  
Walid M. Abdelwahab ◽  
J. David Innes ◽  
Albert M. Stevens
Keyword(s):  
Travel Behavior ◽  
Mode Choice ◽  
Geographical Location ◽  
Predictive Ability ◽  
Multinomial Logit ◽  
Choice Models ◽  
Trip Purpose ◽  
Market Shares ◽  
Intercity Travel ◽  
Statistics Canada

This paper reports and discusses the results of an effort to develop disaggregate behavioral mode choice models of intercity travel in Canada. Currently available data bases of intercity travel in Canada are reviewed. The feasibility of using data from national travel surveys to develop statistically reliable intercity mode choice models is examined, and directions for future disaggregate data collection efforts are offered. The models developed are of the multinomial logit (MNL) type which included all intercity passenger travel modes: auto, air, bus, and rail. For purposes of estimation, the travel market was segmented by trip length (short, long); trip purpose (business, recreational); and geographical location of the trip (east, west). Then, a separate model was estimated in each sector. The models were estimated using the data collected by Statistics Canada as a part of the Labor Force Survey (The Canadian Travel Survey, CTS). The quality of the calibrated models varied from one region to another and from one travel sector to another. Overall, the models were reasonably accurate in predicting modal shares of the most frequently used modes (auto and air). The underrepresentation of the bus and rail modes in the data sets led to a deterioration in the performance of the models in predicting market shares of these two modes. More specifically, the predictive ability of the models measured by the likelihood ratio index varied from a low of 0.58 in the short travel sector to a high of 0.94 in the long travel sector. The transferability of the models described in this study was recently examined by Abdelwahab (1991). Key words: mode choice, disaggregate, travel behavior, multinomial logit, intercity, data base.

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