scholarly journals DEVELOPMENT OF FUZZY LOGIC BASED MODE CHOICE MODEL CONSIDERING VARIOUS PUBLIC TRANSPORT POLICY OPTIONS

2013 ◽  
Vol 3 (4) ◽  
pp. 408-425 ◽  
Author(s):  
Mukesh Kumar ◽  
Pradip Sarkar ◽  
Errampalli Madhu
2011 ◽  
Vol 97-98 ◽  
pp. 606-610
Author(s):  
Huseyın Onur Tezcan ◽  
Fatih Yonar ◽  
Sabahat Topuz Kiremitci

The aim of this study is to understand the reasons behind the mode choice preferences of passengers using a public transport transfer center. For this aim, a questionnaire data obtained at an interim transfer center in Istanbul is utilized. This interim center hosts stops for paratransit, bus and metro modes. A multinomial logit model of modal preferences is estimated and the coefficient results of this model are used to analyze and compare modes.


2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Jian Chen ◽  
Shoujie Li

Mode choice model for public transport, which integrates structural equation model (SEM) and discrete choice model (DCM) with categorized latent variables, was presented in this paper. Apart from identifying those important latent variables that affect mode choice for public transport, the objective of this study was also to develop an improved disaggregative model that better explains travel behavior of those decision-makers in choosing public transport. After extensive observations, selective latent variable sets which consist of latent variable components were chosen together with explicit variables in formulating the utility functions. Data collected in Chengdu city, China, were used to calibrate and validate the model. Results showed that the impact of fare on mode choice of public transport escalated in the SEM-DCM integrated model compared with the traditional logit model. The goodness of fit for the integrated model with latent variable sets is 0.201 higher than that of the traditional logit model, which proves that latent variables have an obvious impact on mode choice behavior, and the SEM-DCM integrated model has higher accuracy and stronger explanatory ability. The results are especially helpful for public transport operators to achieve higher mode share split by improving the service quality of public transport in terms of providing more convenience and better service environment for public transport users.


2008 ◽  
Vol 42 (2) ◽  
pp. 208-219 ◽  
Author(s):  
Marcela Munizaga ◽  
Sergio Jara-Díaz ◽  
Paulina Greeven ◽  
Chandra Bhat

2018 ◽  
Vol 181 ◽  
pp. 03001
Author(s):  
Dwi Novi Wulansari ◽  
Milla Dwi Astari

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.


2021 ◽  
Author(s):  
Mirjam Schindler ◽  
JYT Wang ◽  
RD Connors

Air pollution is an increasing concern to urban residents. In response, residents are beginning to adapt their travel behaviour and to consider local air quality when choosing a home. We study implications of such behaviour for the morphology of cities and population exposure to traffic-induced air pollution. To do so, we propose a spatially explicit and integrated residential location and transport mode choice model for a city with traffic-induced air pollution. Intra-urban spatial patterns of population densities, transport mode choices, and resulting population exposure are analysed for urban settings of varying levels of health concern and air pollution information available to residents. Numerical analysis of the feedback between residential location choice and transport mode choice, and between residents' choices and the subsequent potential impact on their own health suggests that increased availability of information on spatially variable traffic-induced health concerns shifts population towards suburban areas with availability of public transport. Thus, health benefits result from reduced population densities close to urban centres in this context. To mitigate population exposure, our work highlights the need for spatially explicit information on peoples' air pollution concerns and, on this basis, spatially differentiated integrated land use and transport measures.


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