Disaggregate mode choice models for intercity passenger travel in Canada

1990 ◽  
Vol 17 (2) ◽  
pp. 184-191 ◽  
Author(s):  
Frank R. Wilson ◽  
Sundar Damodaran ◽  
J. David Innes
Keyword(s):  
Data Base ◽  
Goodness Of Fit ◽  
Impact Analysis ◽  
Planning Process ◽  
Mode Choice ◽  
Choice Models ◽  
Travel Survey ◽  
Multinomial Logit Models ◽  
Passenger Travel ◽  
Disaggregate Models

Disaggregate mode choice models were calibrated for intercity passenger travel in Canada using a data base drawn from the Canadian Travel Survey. Multinomial logit models were calibrated for business and nonbusiness trips in the eastern and the western regions of Canada. The calibrated models produced reliable results in terms of goodness-of-fit measures. The likelihood ratio index, ρ2(c), varied from 0.282 to 0.436. Results obtained were comparable to those of previous studies. The research identified the significance of level-of-service factors in determining mode choice. The findings from the study indicated that the Canadian Travel Survey data could be used for developing disaggregate models for possible use in policy impact analysis. The potential for the use of this data base in the transportation planning process could be enhanced if some relatively minor modifications were made. Key words: models, disaggregate, choice, intercity, passenger, travel time, cost, frequency, service.

Review of advantages and applications of disaggregate mode choice models in intercity passenger travel

1987 ◽  
Vol 14 (6) ◽  
pp. 763-770 ◽  
Author(s):  
N. S. Ghoneim ◽  
M. Sargious
Keyword(s):  
Mode Choice ◽  
Travel Behaviour ◽  
Choice Models ◽  
Logit Analysis ◽  
Choice Behaviour ◽  
Advantages And Disadvantages ◽  
Passenger Travel ◽  
Modelling Techniques ◽  
Analysis Mode ◽  
Disaggregate Models

The use of disaggregate models in modelling intercity passengers mode choice behaviour has emerged over the past 20 years. In an attempt to encourage this use, the present paper addresses the advantages and disadvantages of the disaggregate approach as opposed to the conventional aggregate techniques. The results of a literature review in this regard indicate that disaggregation is statistically and behaviourally necessary to model human travel behaviour while being sensitive in selecting the unit of analysis. The paper also compares the logit analysis with other modelling techniques available for application in order to identify the most suitable one. A critical review of previous modelling efforts in the U.S. and Canada, based on the disaggregate logit analysis is presented to demonstrate the applicability of this technique to modelling intercity passengers mode choice behaviour. Some modelling drawbacks and the general findings of the studies are emphasized to provide useful insight for future modelling considerations. Key words: behavioural, disaggregate, logit analysis, mode choice, models, passenger travel.

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.

Assessing Goodness of Fit of Hybrid Choice Models

2015 ◽  
Vol 2495 (1) ◽  
pp. 131-141 ◽  
Author(s):  
Yutaka Motoaki ◽  
Ricardo A. Daziano
Keyword(s):  
Goodness Of Fit ◽  
Choice Models

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

Applications of FTA National Transit Data Base for the Intermodal Surface Transportation Efficiency Act Management System Requirements

1996 ◽  
Vol 1521 (1) ◽  
pp. 45-48
Author(s):  
William M. Lyons ◽  
John Collura ◽  
Sean Libberton ◽  
Paul Branch
Keyword(s):  
Data Base ◽  
Public Transportation ◽  
Management System ◽  
Planning Process ◽  
Management Systems ◽  
Transit Systems ◽  
Multimodal Transportation ◽  
Metropolitan Planning ◽  
Surface Transportation ◽  
And Performance

The Intermodal Surface Transportation Efficiency Act of 1991 (ISTEA) requires states in conjunction with metropolitan planning organizations (MPOs) to develop, establish, and implement several systems to better manage and improve the efficiency of transportation infrastructure. Among other things, the National Highway System Designation Act of 1995 allows states not to implement one or more of the ISTEA management systems. Although the management systems are now optional, FHWA and FTA continue to believe that the management and monitoring of the performance and condition of the multimodal transportation system should remain an important element of statewide and metropolitan planning. How FTA's National Transit Data Base (NTD) can provide an important source of information as agencies develop the ISTEA management systems or similar mechanisms for managing and monitoring transit facilities and equipment is analyzed. NTD, which contains information on the financial and nonfinancial operations, system performance, and equipment of national public transit systems, is used primarily by transit operators and others in the transit industry. How NTD can contribute to development and operations of the Public Transportation Management System as well as the Congestion and other management systems is discussed. Development of applications for ISTEA management systems, or for similar planning tools, broadens applications of NTD beyond its transit customer base to aid states and MPOs. By contributing comprehensive transit data to systems for managing and monitoring condition and performance of multimodal transportation, NTD can improve representation of transit needs and performance in the ISTEA planning process.

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