scholarly journals Exploring Influencing Factors of Intercity Mode Choice from View of Entire Travel Chain

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Xiaowei Li ◽  
Siyu Zhang ◽  
Yao Wu ◽  
Yuting Wang ◽  
Wenbo Wang
Keyword(s):  
Logit Model ◽  
Unobserved Heterogeneity ◽  
Mode Choice ◽  
Multinomial Logit Model ◽  
Multinomial Logit ◽  
Travel Mode ◽  
Intercity Travel ◽  
Travel Mode Choice ◽  
Mixed Multinomial Logit Model ◽  
Significant Factors

Exploring the influencing factors of intercity travel mode choice can reveal passengers’ travel decision mechanisms and help traffic departments to develop an effective demand management policy. To investigate these factors, a survey was conducted in Xi’an, China, to collect data about passengers’ travel chains, including airplane, high-speed railway (HSR), train, and express bus. A Bayesian mixed multinomial logit model is developed to identify significant factors and explicate unobserved heterogeneity across observations. The effect of significant factors on intercity travel mode choice is quantitatively assessed by the odds ratio (OR) technique. The results show that the Bayesian mixed multinomial logit model outperforms the traditional Bayesian multinomial logit model, indicating that accommodating the unobserved heterogeneity across observations can improve the model fit. The model estimation results show that ticket purchasing method, comfort, punctuality, and access time are random parameters that have heterogeneous effects on intercity travel mode choice.

scholarly journals A review of Machine Learning (ML) algorithms used for modeling travel mode choice

DYNA ◽  
2019 ◽  
Vol 86 (211) ◽  
pp. 32-41 ◽  
Author(s):  
Juan D. Pineda-Jaramillo
Keyword(s):  
Machine Learning ◽  
Choice Model ◽  
Mode Choice ◽  
Multinomial Logit Model ◽  
Support Vector ◽  
Travel Mode ◽  
Wide Range ◽  
Travel Mode Choice ◽  
And Cluster Analysis ◽  
Transportation Research

In recent decades, transportation planning researchers have used diverse types of machine learning (ML) algorithms to research a wide range of topics. This review paper starts with a brief explanation of some ML algorithms commonly used for transportation research, specifically Artificial Neural Networks (ANN), Decision Trees (DT), Support Vector Machines (SVM) and Cluster Analysis (CA). Then, these different methodologies used by researchers for modeling travel mode choice are collected and compared with the Multinomial Logit Model (MNL) which is the most commonly-used discrete choice model. Finally, the characterization of ML algorithms is discussed and Random Forest (RF), a variant of Decision Tree algorithms, is presented as the best methodology for modeling travel mode choice.

scholarly journals Influence of Weather Conditions on the Intercity Travel Mode Choice: A Case of Xi’an

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Xiaowei Li ◽  
Qiangqiang Ma ◽  
Wenbo Wang ◽  
Baojie Wang
Keyword(s):  
High Speed ◽  
Mode Choice ◽  
Mode Selection ◽  
Weather Conditions ◽  
Individual Characteristics ◽  
Activity Data ◽  
Travel Mode ◽  
Intercity Travel ◽  
Travel Mode Choice ◽  
Weather Characteristics

To explore the influence of weather conditions on the choice of the intercity travel mode of travelers, four modes of traveler transportation were studied in Xi'an, China, in March 2019: airplane, high-speed rail, conventional train, and express bus. The individual characteristics of travelers and intercity travel activity data were obtained, and they were matched with the weather characteristics at the departure time of the travelers. The Bayesian multinomial logit regression was employed to explore the relationship between the travel mode choice and weather characteristics. The results showed that temperature, relative humidity, rainfall, wind, air quality index, and visibility had significant effects on the travel mode selection of travelers, and the addition of these variables could improve the model’s predictive performance. The research results can provide a scientific decision basis for traveler flow transfer and the prediction of traffic modes choice due to the effects of climate change.

scholarly journals Older Adults’ Choice of Patterns of Outdoor Physical Activity Duration: A Mixed Multinomial Logit Model

2021 ◽  
Vol 18 (15) ◽  
pp. 8199
Author(s):  
Zhengying Liu ◽  
Wenli Huang ◽  
Yuan Lu ◽  
You Peng
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Logit Model ◽  
Multinomial Logit Model ◽  
Exercise Duration ◽  
Multinomial Logit ◽  
Activity Levels ◽  
Activity Duration ◽  
Mixed Multinomial Logit Model ◽  
Physical Activity Duration

Outdoor physical activity duration is a key component of outdoor physical activity behavior of older adults, and therefore, an important determinant of their total physical activity levels. In order to develop a successful outdoor physical activity program, it is important to identify any heterogeneity in preferences for outdoor physical activity duration patterns among older adults. In addition, more insight is needed in the influence of environmental characteristics on duration choice for creating supportive neighborhood environments matching individuals’ preferences. To this end, a mixed multinomial logit model is estimated based on one-week data collected among 336 respondents aged 60 or over in 2017 in Dalian, China. The present model formulation accounts for heterogeneity in individuals’ preferences and allows for the analysis of substitution and complementary relationships between the different patterns of outdoor physical activity duration. Results indicate that older adults vary significantly in their preferences for each outdoor physical activity duration pattern. Moreover, short walking duration, short exercise duration and medium exercise duration are substitutes for medium walking duration while short walking duration and short exercise duration are complements for medium exercise duration in terms of individuals’ outdoor physical activity duration preferences. In addition, we find that distance to the nearest park, footpath conditions and neighborhood aesthetics are associated with older adults’ outdoor physical activity duration choice.

A Mode Choice Model for a Public Transport Transfer Center in Istanbul

2011 ◽  
Vol 97-98 ◽  
pp. 606-610
Author(s):  
Huseyın Onur Tezcan ◽  
Fatih Yonar ◽  
Sabahat Topuz Kiremitci
Keyword(s):  
Public Transport ◽  
Logit Model ◽  
Choice Model ◽  
Mode Choice ◽  
Multinomial Logit Model ◽  
Multinomial Logit ◽  
Questionnaire Data ◽  
Mode Choice Model

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.

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