scholarly journals Typical Combined Travel Mode Choice Utility Model in Multimodal Transportation Network

2019 ◽  
Vol 11 (2) ◽  
pp. 549 ◽  
Author(s):  
Yue Liu ◽  
Jun Chen ◽  
Weiguang Wu ◽  
Jiao Ye
Keyword(s):  
Short Distance ◽  
Stated Preference ◽  
Personal Information ◽  
Transportation Network ◽  
Mode Choice ◽  
Influential Factors ◽  
Long Distance ◽  
Travel Mode ◽  
Travel Mode Choice ◽  
Walking Time

The primary purpose of this paper is to explore the mechanism of combined travel mode choice in multimodal networks. To meet the objective, stated preference survey and revealed preference survey are designed under short, middle, and long travel distance scenarios. Data including travelers’ socio-economic/personal information, trip characteristics, and mode choice are collected and analyzed. To recognize the influential factors of mode choice, a nested logit model is established. A value of time estimation and sensitivity analysis are conducted to quantify the influencing degree. The results reveal that cost has a significant influence on the short-distance travel mode; waiting time is perceived as the most important factor in short-distance scenario, and transfer-walking time as the most significant in middle and long distance scenario. Moreover, the traveler is more sensitive to the decrease of the transfer walking time than increase. Regarding socio-economic/personal information, travelers aged 40–50 prefer to choose combined travel mode than other ages; female travelers have a greater acceptance of metro-based transfer travel than male; individuals with higher economic level have a positive image of metro than bus.

scholarly journals Exploring the Influence of Attitudes to Walking and Cycling on Commute Mode Choice Using a Hybrid Choice Model

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Chuan Ding ◽  
Yu Chen ◽  
Jinxiao Duan ◽  
Yingrong Lu ◽  
Jianxun Cui
Keyword(s):  
Travel Behavior ◽  
Traffic Congestion ◽  
Structural Equation ◽  
Choice Model ◽  
Mode Choice ◽  
Influential Factors ◽  
Travel Mode ◽  
Travel Mode Choice ◽  
The Impact ◽  
Hybrid Choice Model

Transport-related problems, such as automobile dependence, traffic congestion, and greenhouse emissions, lead to a great burden on the environment. In developing countries like China, in order to improve the air quality, promoting sustainable travel modes to reduce the automobile usage is gradually recognized as an emerging national concern. Though there are many studies related to the physically active modes (e.g., walking and cycling), the research on the influence of attitudes to active modes on travel behavior is limited, especially in China. To fill up this gap, this paper focuses on examining the impact of attitudes to walking and cycling on commute mode choice. Using the survey data collected in China cities, an integrated discrete choice model and the structural equation model are proposed. By applying the hybrid choice model, not only the role of the latent attitude played in travel mode choice, but also the indirect effects of social factors on travel mode choice are obtained. The comparison indicates that the hybrid choice model outperforms the traditional model. This study is expected to provide a better understanding for urban planners on the influential factors of green travel modes.

scholarly journals Optimization Scheme of Tradable Credits and Bus Departure Quantity for Travelers’ Travel Mode Choice Guidance

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Fang Zhou ◽  
Jianhui Wu ◽  
Yan Xu ◽  
Chi Yi
Keyword(s):  
Road Traffic ◽  
Choice Model ◽  
Transportation Network ◽  
Mode Choice ◽  
Optimization Scheme ◽  
Travel Mode ◽  
Travel Mode Choice ◽  
Total Travel Time ◽  
Tradable Credits ◽  
Car Travel

To analyze the influence of tradable credits and bus departure quantity on travelers' travel mode choice, this study investigated car travel and bus travel as research objects and established a two-mode day-to-day travel mode choice model based on tradable credits and bus departure quantity. To improve the guiding effect of tradable credits and bus departure quantity, an optimization scheme of tradable credits and bus departure quantity was developed with the goal of minimizing the system total travel time of car travel and the system total comprehensive cost of bus travel. Taking a test transportation network as an example, the influence of no tradable credits scheme, tradable credits scheme, and tradable credits and bus departure quantity scheme on the travelers’ travel mode choice behavior was analyzed. The results showed that the tradable credits and bus departure quantity scheme could reduce the saturation of road traffic and improve bus service quality.

scholarly journals Price Regulation Mechanism of Travelers’ Travel Mode Choice in the Driverless Transportation Network

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Jianhui Wu ◽  
Yuanfa Ji ◽  
Xiyan Sun ◽  
Yan Xu
Keyword(s):  
Transportation Network ◽  
Mode Choice ◽  
Price Regulation ◽  
Market Model ◽  
Regulation Mechanism ◽  
Optimal Price ◽  
Travel Mode ◽  
Travel Mode Choice ◽  
Calculation Process ◽  
Relationship Of

To study the guidance method of driverless travel mode choice from the perspective of traffic supply-demand, we assume that all vehicles are driverless and establish a multimodal travel market model to depict the supply-demand relationship of multimodal driverless transportation network. To regulate the disequilibrium multimodal travel market, an optimal price regulation law is proposed, which aims to minimize the supply-demand deviation and the amplitude of price regulation. Then, the existence, uniqueness, and stability of the optimal price regulation law are confirmed. In the calculation process of a numerical example, the travel prices of driverless car and driverless subway are realized by congestion fee and subway fare, respectively. The results indicate that the optimal price regulation law can reduce the supply-demand deviation of the multimodal travel market and guide travelers to choose a reasonable travel mode to travel in the driverless transportation network.

scholarly journals Incorporating Inertia in Mode Choice and Influential Factors of Car Stickiness: Implications for Shifts to Public Transit

2018 ◽  
Vol 30 (3) ◽  
pp. 293-303
Author(s):  
Kun Gao ◽  
Lijun Sun
Keyword(s):  
Public Transit ◽  
Stated Preference ◽  
Mode Choice ◽  
Influential Factors ◽  
Travel Time Reliability ◽  
Transit System ◽  
Travel Mode ◽  
And Gender ◽  
Demographic Attributes ◽  
Willingness To Use

To explore efficient strategies of adjusting travel mode structure and support scientific implements of public transit system, this paper investigated travelers’ mode choice behavior in a multimodal network incorporating inertia in utility specifications. Comprehensive stated preference surveys considering four modes and four key decisive variables were designed, and face-to-face investigations were conducted to collect reliable data in Shanghai. The discrete choice technique considering mode-specific inertias was employed for modeling. The influencing factors of car stickiness were particularly explored. The results show that there are significant and mode-specific inertias in travelers’ choices of travel mode. The inertia of car users shifting to other modes is considerably large compared to inertias of public transit users. Travel time reliability and crowdedness in public transit are identified to be crucial factors influencing car users’ willingness to use public transit. Demographic attributes (age, income, education level and gender), spatial context features (commuting duration) and the regime of flexible work time are found to be significant influential variables of car stickiness. Moreover, direct and cross elasticity analyses were executed to show practical implications of shifting car users to public transit. The results provide serviceable support for transport planning and strategy making.

scholarly journals Mode Choice Modelling Between Bus and Train Under the New Normal Condition

2021 ◽  
Vol 004 (01) ◽  
pp. 084-092
Author(s):  
Willy Kriswardhana ◽  
Akhmad Hasanuddin ◽  
Daud Muntsari
Keyword(s):  
Normal Condition ◽  
Large Scale ◽  
Choice Model ◽  
Stated Preference ◽  
Mode Choice ◽  
Travel Cost ◽  
Travel Mode ◽  
New Normal ◽  
Social Distancing ◽  
Travel Mode Choice

The passenger movements were limited by the government policies that made new system decisions, namely large-scale social distancing policies. However, over time several regions in Indonesia have begun to end large-scale social distancing called new normal. The new normal condition has undoubtedly changed the pattern of mode choice of the passenger. Little attention has been paid to the travel mode choice under the new normal condition. Therefore, this study aims to understand the travel mode choice model of train and bus, especially in the new normal era. The primary data was collected using the stated preference online-based survey. This study performed a Binomial-Logit-Difference model. From the modelling result, 89% of the passenger will choose the bus if the train's travel fare is IDR 160,000 higher. The probability value will be equal when the ticket fare of the bus is IDR 25,000 higher than train’s travel cost. It indicates that people choose the bus mode because of the travel cost factor. Directions for the future study are presented

Study of Travel Mode Choice Behavior Based on Nested Logit Model

2012 ◽  
Vol 253-255 ◽  
pp. 1345-1350
Author(s):  
Bin Shang ◽  
Xiao Ning Zhang
Keyword(s):  
Choice Behavior ◽  
Likelihood Function ◽  
Stated Preference ◽  
Mode Choice ◽  
Estimation Method ◽  
Simultaneous Estimation ◽  
Nested Logit ◽  
Travel Mode ◽  
Factors Affecting ◽  
Travel Mode Choice

Not only multinomial logit (ML) model is usually used in the analysis of travel mode split, but also nested logit (NL) with the method of phased estimation is used. NL model was developed in the paper which used the simultaneous estimation method to analyze travel mode choice behavior on the basis of the basic theory of disaggregate model and data of stated preference survey (SP). In the course of estimating the parameters, the multi-constrained optimization function in optimal tool of MATLAB was used to solve the maximum likelihood function. Using this method, the parameters of model could be calibrated at the same time. The hit ratios are also accurate. It is found that the NL model approach can consider more factors affecting the travel mode choice of residents, improve the prediction accuracy of model and practicality.

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