Mode choice modelling for hailable rides: An investigation of the competition of Uber with other modes by using an integrated non-compensatory choice model with probabilistic choice set formation

2019 ◽  
Vol 129 ◽  
pp. 205-216 ◽  
Author(s):  
Khandker Nurul Habib
Keyword(s):  
Choice Model ◽  
Mode Choice ◽  
Choice Modelling ◽  
Probabilistic Choice ◽  
Choice Set Formation ◽  
Choice Set

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%.

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%.

Modelling commuting mode choice with explicit consideration of carpool in the choice set formation

2011 ◽  
Vol 38 (4) ◽  
pp. 587-604 ◽  
Author(s):  
Khandker M. Nurul Habib ◽  
Yuan Tian ◽  
Hamid Zaman
Keyword(s):  
Mode Choice ◽  
Choice Set Formation ◽  
Explicit Consideration ◽  
Commuting Mode ◽  
Choice Set

scholarly journals Commuter Train Mode Choice Modelling Using Binary Logit Model

2019 ◽  
Vol 10 (2) ◽  
pp. 112-126
Author(s):  
Muhammad 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 is increase 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 switch to pubic transportation is by improving the public transport system becomes more efficient. To find out the solution, an understanding of traveller behavior by apply 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%.

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