scholarly journals A study on the competitiveness of eight different estimation algorithms for multinomial logit mode choice modelling using analytical derivatives

2007 ◽  
Author(s):  
Hyuk-Jae Roh
Keyword(s):  
Mode Choice ◽  
Multinomial Logit ◽  
Choice Modelling ◽  
Estimation Algorithms ◽  
Analytical Derivatives

scholarly journals Multi-route choice modelling in a metropolitan context: A comparative analysis using Multinomial Logit and Fuzzy Logic based approaches

2020 ◽  
Vol 79 (ET.2020) ◽  
pp. 1-17
Author(s):  
Sowjanya Dhulipala
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Choice Model ◽  
Route Choice ◽  
Fuzzy Rule ◽  
Multinomial Logit ◽  
Choice Modelling ◽  
Choice Behaviour ◽  
Linguistic Rules ◽  
Mnl Model

Route choice plays a vital role in the traffic assignment and network building, as it involves decision making on part of riders. The vagueness in travellers’ perceptions of attributes of the available routes between any two locations adds to the complexities in modelling the route choice behaviour. Conventional Logit models fail to address the uncertainty in travellers’ perceptions of route characteristics (especially qualitative attributes, such as environmental effects), which can be better addressed through the theory of fuzzy sets and linguistic variables. This study thus attempts to model travellers’ route choice behaviour, using a fuzzy logic approach that is based on simple and logical ‘if-then’ linguistic rules. This approach takes into consideration the uncertainty in travellers’ perceptions of route characteristics, resembling humans’ decision-making process. Three attributes – travel time, traffic congestion, and road-side environment are adopted as factors driving people’s choice of routes, and three alternative routes between two typical locations in an Indian metropolitan city, Surat, are considered in the study. The approach to deal with multiple routes is shown by analyzing two-wheeler riders’ (e.g. motorcyclists’ and scooter drivers’) route choice behaviour during the peak-traffic time. Further, a Multinomial Logit (MNL) model is estimated, to enable a comparison of the two modelling approaches. The estimated Fuzzy Rule-Based Route Choice Model outperformed the conventional MNL model, accounting for the uncertain behaviour of travellers.

scholarly journals Commuter Train Mode Choice Modelling Using Binary Logit Model

2019 ◽  
Vol 6 (1) ◽  
pp. 1
Author(s):  
Ryan Septiady Nugraha
Keyword(s):  
Public Transportation ◽  
Choice Model ◽  
Mode Choice ◽  
Leisure Activity ◽  
Proper Solution ◽  
Choice Modelling ◽  
School Work ◽  
Trip Purpose ◽  
Public Transport System ◽  
Binary Logit

Car production in Malaysia increasing dramatically. This situation created serious impact such as pollution and congestion. The Malaysian government should find a proper solution to prevent the vehicles growth by controlling them and improve public transportation services. The only way to get people to switch to public transportation is by improving the public transport system becomes more efficient. To find out the solution, an understanding of traveler behavior by applying to mode choice model using binary logit approach is necessary. Stated preferences method was adopted in order to construct hypothetical choice in current and future situations. A total of 250 respondents were selected as the sample based on the research study. This research employed a discrete choice analysis to examine the relationship between the independent variables (travel time, fares, comfort and safety). With variation of trip purpose (school, work, leisure activity, and shopping), model has been developed and tested to check the validity. The result shows that the potential of new train services to compete with the current commuter (KTM) and private car user are quite competitive. This is no doubt due to the characteristics of the respondent to choose a good level of services especially a better comfortability and safety with an affordable price (fares). It can be concluded that scenario 2 has great potential to be implemented since forecasting demand reached above 90%.

Analyzing Intercity Modal Choice and Competition Between High Speed Rail (HSR) and Other Transport Modes in Indian Context

2016 ◽  
pp. 146-160
Author(s):  
Ashish Verma ◽  
Varun Raturi
Keyword(s):  
High Speed ◽  
Mode Choice ◽  
Transport Infrastructure ◽  
Infrastructure Investment ◽  
Theoretic Approach ◽  
Choice Modelling ◽  
Choice Behaviour ◽  
High Speed Rail ◽  
Game Theoretic ◽  
Game Theoretic Approach

In this study, a theoretical framework is developed in order to assess the viability of transport infrastructure investment in the form of High Speed Rail (HSR) by assessing, the mode choice behaviour of the passengers and the strategies of the operators, in the hypothetical scenario. Discrete choice modelling (DCM) integrated with a game theoretic approach is used to model this dynamic market scenario. DCM is incorporated to predict the mode choice behaviour of the passengers in the new scenario and the change in the existing market equilibrium and strategies of the operators due to the entry of the new mode is analysed using the game theoretic approach. The outcome of this market game will describe the strategies for operators corresponding to Nash equilibrium. In conclusion, the impact of introduction of HSR is assessed in terms of social welfare by analysing the mode choice behaviour and strategic decision making of the operators, thus reflecting on the economic viability of the transport infrastructure investment.

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.

Transferability of intercity disaggregate mode choice models in Canada

1991 ◽  
Vol 18 (1) ◽  
pp. 20-26 ◽  
Author(s):  
Walid M. Abdelwahab
Keyword(s):  
Travel Behavior ◽  
Travel Demand ◽  
Mode Choice ◽  
Model Development ◽  
Predictive Ability ◽  
Multinomial Logit ◽  
Choice Models ◽  
Data Sets ◽  
Policy Analysts ◽  
Transportation Studies

In many transportation studies, the time span of data collection, model development, and analysis is often too long to be responsive to the needs of policy analysts and decision makers. This problem is often exacerbated in situations with severely constrained analysis resources. Therefore, it is often useful to transfer a model from one area to another. Model transfer is defined as the application of a model developed in one area to describe the corresponding behavior in another area. This paper examines the transferability of a class of models used in intercity travel demand analysis. Specifically, disaggregate mode choice models of the multinomial logit type are developed for two regions in Canada, and some established measures of transferability are applied to assess the potential of calibrating these models in one region and applying them in the other. Comparison of mode choice models estimated on data sets from the two regions yielded inconclusive results regarding model transferability. In general, transferred models were found to be 18–23% less accurate than local models in predicting modal shares. Adjusting models' parameters to reflect observed modal shares in the application context improved the predictive ability of the models by about 10%. Key words: transferability, mode choice, disaggregate, travel behavior, multinomial logit, intercity.

scholarly journals Travel mode choice preferences of urban commuters in Kuching City, Malaysia based on stated preference data

2018 ◽  
Vol 181 ◽  
pp. 02007
Author(s):  
Resdiansyah
Keyword(s):  
Travel Time ◽  
Public Transport ◽  
Public Transportation ◽  
Stated Preference ◽  
Mode Choice ◽  
Travel Behaviour ◽  
Transportation Systems ◽  
Choice Modelling ◽  
Public Transport System ◽  
Bus Services

One aspect of Kuching City that has not progressed in tandem with the rest of the city is the public transport system, which is relatively old and almost non-existent. Transport and City planners seem to be at their wit’s end in coming up with satisfactory solutions to Kuching’s public transportation woes. In current situation, many proposals, but none have proven workable. As a result, representative buses remain a rare sight on Kuching city’s roads. To achieve a sustainable public transport industry, the old buses need to be regenerated and replaced with modern buses. The objectives of the intended study are to explore the consumer’s travel behaviour by employing mode choice modelling. Consequently, a study was conducted in Kuching City Area by using stated preference technique, analysed and compiled by using SPSS.17 multiple linear regressions analysis. In this context, discrete choice analysis was used to examine the relationship between independent variables (travel time, waiting time, fares and comfort) and dependent variables (choice of respondent whether to consume old bus or choose new bus services). A total of 2000 respondents were interviewed. The findings showed that for the trips purpose, fares and comfortability were the primary factors that reflected the decision or behaviour of the respondents asked. It was discovered that there is a significant relationship between the choice of the respondents and comfortability. It also appeared that longer travel time did not affect for the traveler’s choice at this stage. Hence, the study suggests that the local authority and the bus operators should establish a “quality partnership” and working together in order to come out with a much better and appropriate transport policy and schemes for the existing public transportation systems, especially bus services.

scholarly journals FUZZY LOGIC APPROACH IN MODE CHOICE MODELLING FOR EDUCATION TRIPS: A CASE STUDY OF INDIAN METROPOLITAN CITY

Transport ◽  
2015 ◽  
Vol 30 (3) ◽  
pp. 286-293 ◽  
Author(s):  
Ashu Shivkumar Kedia ◽  
Krishna Bhuneshwar Saw ◽  
Bhimaji Krishnaji Katti
Keyword(s):  
Fuzzy Logic ◽  
Choice Model ◽  
Mode Choice ◽  
Vital Role ◽  
Sustainable Transportation ◽  
Indian Society ◽  
Choice Modelling ◽  
Choice Behaviour ◽  
Public Transport System ◽  
Fuzzy Logic Approach

Urban population in India has increased significantly from 62 million in 1951 to 378 million in 2011 in six decades. It is estimated to reach 540 million by the year 2021. This reflects on likely pressure on urban transportation system. The situation necessarily calls plans for balanced personal and public transport system. Mandatory trips bear more importance in this regard owing to their higher share in urban trips. Mode share and their choice behaviour in estimation of such trips play vital role in analysing and boosting sustainable transportation. Logit modelling approach is the conventional method generally adopted for analysing mode choice behaviour, which is based on the principle of random utility maximization derived from econometric theory. However, such models cannot address uncertainity prevailing in the choice decisions. On the contrary, fuzzy logic bypasses the binary crisp derivations of the inputs and accepts multivalued inputs in linguistic expressions, which make possible to resemble the human behaviour closely. Therefore, the attempt here is to develop fuzzy logic based mode choice model for education trips, which constitutes a good share in mandatory trips by covering various income groups of Indian society.

scholarly journals Incorporating MNL Model into Random Forest for Travel Mode Detection

2021 ◽  
Vol 40 (3) ◽  
pp. 496-501
Author(s):  
Muhammad Awais Shafique ◽  
Eiji Hato
Keyword(s):  
Decision Making ◽  
Random Forest ◽  
Learning Algorithm ◽  
Choice Model ◽  
Mode Choice ◽  
Decision Making Process ◽  
Accelerometer Data ◽  
Choice Modelling ◽  
Travel Mode ◽  
Mode Choice Model

Mode choice models have been used widely to forecast the relative probabilities of using available travel modes. These depend on mode-related and traveler-related characteristics. On the other hand, smartphones are increasingly being used to collect sensors’ data relating to trips made after selection of a suitable mode. Such sensors’ data may be correlated with decision-making process of travelers regarding travel mode selection. Discrete Choice Modelling is used to simulate this decision-making process by computing utilities of various travel alternatives, and then calculating their respective probabilities of being selected. In this paper, multinomial logit (MNL) mode choice model is utilized to enhance the prediction capacity of supervised learning algorithm i.e. Weighted Random Forest. To make the procedure less energy-intensive, GPS data was used only to locate the origin and destination of any trip, to be incorporated in mode choice model. Afterwards only accelerometer data was utilized in feature selection for the learning algorithm. One tenth of the classified data was used to train the algorithm whereas rest was used to test it. Results suggested that with incorporation of MNL, the overall prediction accuracy of learning algorithm was increased from 93.75% to 99.08%.

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