Optimization of the Road Capacity and the Public Transportation Frequency Which Are Based on Logit-Model of Travel Mode Choice

2014 ◽  
pp. 214-222 ◽  
Author(s):  
Mark Koryagin ◽  
Alexandra Dekina
Keyword(s):  
Public Transportation ◽  
Logit Model ◽  
Mode Choice ◽  
Travel Mode ◽  
The Public ◽  
The Road ◽  
Road Capacity ◽  
Travel Mode Choice

Values, attitudes and travel behavior: a hierarchical latent variable mixed logit model of travel mode choice

2013 ◽  
Vol 41 (4) ◽  
pp. 873-888 ◽  
Author(s):  
Marcel Paulssen ◽  
Dirk Temme ◽  
Akshay Vij ◽  
Joan L. Walker
Keyword(s):  
Travel Behavior ◽  
Logit Model ◽  
Latent Variable ◽  
Mode Choice ◽  
Mixed Logit ◽  
Mixed Logit Model ◽  
Travel Mode ◽  
Travel Mode Choice

scholarly journals A Bayesian Network Model on the Public Bicycle Choice Behavior of Residents: A Case Study of Xi’an

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Qiuping Wang ◽  
Hao Sun ◽  
Qi Zhang
Keyword(s):  
Bayesian Network ◽  
Network Model ◽  
Expert Knowledge ◽  
Choice Model ◽  
Mode Choice ◽  
Bayesian Network Model ◽  
Travel Mode ◽  
The Public ◽  
Proposed Model ◽  
Travel Mode Choice

In order to study the main factors affecting the behaviors that city residents make regarding public bicycle choice and to further study the public bicycle user’s personal characteristics and travel characteristics, a travel mode choice model based on a Bayesian network was established. Taking residents of Xi’an as the research object, a K2 algorithm combined with mutual information and expert knowledge was proposed for Bayesian network structure learning. The Bayesian estimation method was used to estimate the parameters of the network, and a Bayesian network model was established to reflect the interactions among the public bicycle choice behaviors along with other major factors. The K-fold cross-validation method was used to validate the model performance, and the hit rate of each travel mode was more than 80%, indicating the precision of the proposed model. Experimental results also present the higher classification accuracy of the proposed model. Therefore, it may be concluded that the resident travel mode choice may be accurately predicted according to the Bayesian network model proposed in our study. Additionally, this model may be employed to analyze and discuss changes in the resident public bicycle choice and to note that they may possibly be influenced by different travelers’ characteristics and trip characteristics.

Travel mode choice and impact of fuel tax in Beijing

2013 ◽  
Vol 19 (1) ◽  
pp. 92-110 ◽  
Author(s):  
Ping Qin ◽  
Xinye Zheng ◽  
Lanlan Wang
Keyword(s):  
Mode Choice ◽  
Rapid Development ◽  
Motor Vehicles ◽  
Vehicular Emissions ◽  
Travel Mode ◽  
Fuel Tax ◽  
The Road ◽  
Travel Mode Choice ◽  
On The Road ◽  
The Impact

AbstractAs an international metropolitan area undergoing rapid development, Beijing is facing a sharp rise in the volume of motor vehicles and mobility, which has become the major contributor to the air pollution in this city. This is evident in the recent ranking of Beijing as the most congested as well as the most polluted city in the world by the Millennium Cities Database. Local government has adopted a battery of policies to reduce these problems. In this study, we investigate the impact of increasing the fuel tax on travel mode choice based on a large sample of travel survey data. We estimate that if the price of gasoline increased to a moderate level, 11.53 RMB/liter, the total car volume on the road would be reduced by 7 per cent, which corresponds to a reduction in CO2 emissions of 786,002.4 tons, or about 8 per cent of vehicular emissions from private cars and company-owned cars in Beijing.

scholarly journals Quantifying Travel Physical Energy Expenditure for Urban Travellers – A Case Study of Beijing

2020 ◽  
Vol 32 (2) ◽  
pp. 219-228
Author(s):  
Xin Hong ◽  
Lingyun Meng ◽  
Jian An
Keyword(s):  
Energy Expenditure ◽  
Public Transportation ◽  
Choice Model ◽  
Mode Choice ◽  
Economic Cost ◽  
Multinomial Logit Model ◽  
Travel Mode ◽  
Physical Energy ◽  
Travel Mode Choice

Travel physical energy expenditure for travellers has impact on travel mode choice behaviour. However, quantitative study on travel physical energy expenditure is rare. In this paper, the concept of travel physical energy expenditure coefficient has been presented. A case study has been carried out of young travellers in Beijing to get the value of physical energy expenditure per unit time under three transport modes, walking, car and public transportation. A series of experiments have been designed and conducted, which consider influence factors including age, gender, travel mode, riding posture, luggage level and crowded level. By analysing the travel data of money, travel time and physical energy expenditure, we determined that the value of travel physical energy expenditure coefficient δ is 0.058 RMB/KJ, which means that travellers can pay 0.058 RMB to reduce 1 KJ physical energy expenditure. Next, a travel mode choice model has been proposed using a multinomial logit model (MNL), considering economic cost, time cost and physical energy cost. Finally, the case study based on OD from Xizhimen to Tiantongyuan in Beijing was conducted. It is verified that it will be in better agreement with the actual travel behaviour when we take the physical energy expenditure for different types of travellers into account.

scholarly journals Pro-Environmental Behaviour in Travel Mode Choice of Graduate Students: Case Study in Jakarta

2018 ◽  
Vol 65 ◽  
pp. 09001 ◽  
Author(s):  
Ankiet D. Lelono ◽  
Herdis Herdiansyah ◽  
Linda Darmajanti ◽  
Tri Edhi Budhi Soesilo ◽  
Hayati S. Hasibuan ◽  
...  
Keyword(s):  
Graduate Students ◽  
Public Transportation ◽  
Environmental Behavior ◽  
Mode Choice ◽  
Travel Mode ◽  
Political Activities ◽  
Emissions Mitigation ◽  
Travel Mode Choice ◽  
Socio Demographic Factors

Rapid urban growth requires an established and dynamic transportation system to connect places and facilitate economic, social, cultural and human political activities. The choice of public transportation is considered a pro-environmental behavior in regards to emissions mitigation, therefore leads to sustainability. This paper attempts to understand graduate students’ pro-environmental behavior in travel mode choice towards public transportation, and to observe correlation between socio-demographic factors and pro- environmental behavior. This research was conducted in University X in Jakarta with 82 respondents, analyzed in quantitative approach (SPSS) and mix method. Using Theory of Planned Behavior (TPB), this research concludes that attitude is the most dominant sub-variable of behavior, seen from correlation between attitude and subjective norm, intention, and respondents’ age. Subjective norms and intention has positive correlation, but no correlation to socio-demographics.

Public Transportation Travel Mode Choice Behavior Research

CICTP 2012 ◽  
2012 ◽  
Author(s):  
Huanhuan Yin ◽  
Juan Li ◽  
Hongzheng Zhao
Keyword(s):  
Public Transportation ◽  
Choice Behavior ◽  
Mode Choice ◽  
Travel Mode ◽  
Travel Mode Choice

scholarly journals OPTIMIZATION OF AN URBAN TRANSPORT SYSTEM ON THE CONDITION OF DIFFERENT GOALS OF MUNICIPAL AUTHORITIES, OPERATORS AND PASSENGERS

Transport ◽  
2016 ◽  
Vol 31 (1) ◽  
pp. 63-69 ◽  
Author(s):  
Mark Koryagin ◽  
Vladimir Katargin
Keyword(s):  
Control System ◽  
Travel Time ◽  
Public Transport ◽  
Mode Choice ◽  
Theoretic Approach ◽  
Passenger Transport ◽  
Travel Mode ◽  
Passenger Flow ◽  
Road Capacity ◽  
Travel Mode Choice

A control system of urban passenger transport is considered. The system participants are a passenger flow, a transport operator and municipal authorities. The participants’ strategies include a travel mode choice, a frequency of public transport service, and a road capacity. Objective functions are transport costs, public transport profit, road costs, and travel time. The passenger flow heterogeneity is based on the value of time that has an exponential distribution. The total costs of passenger flow depend on the probability of the travel mode choice. The dependence between travel time, roads capacity, and traffic is based on Greenshields model. The authorities’ objective consists of travel time and road costs, which can be changed by the road capacity. The game theoretic approach is applied to describe the control system. The existence of Nash equilibrium for coalition-free games for two (the passenger flow and the authorities and three (with addition of public transport) players is proved. The characteristics of urban passenger transport were studied based on a numerical example.

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.

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