Dependence between travel distance,individual socioeconomic and health-related characteristics,and the choice of the travel mode: a cross-sectional study for Kaunas,Lithuania

The aim of this study was to analyse the associations between individual socioeconomic and health-related characteristics, travel distance, and the choice of different travel modes in urban population. A cross-sectional study included 932 adults of Kaunas city, Lithuania. The choice of the travel mode and individual characteristics were self-reported by the participants, and their travel routes were calculated using the geographic information system. Multivariate logistic regression was used to assess the most significant factors determining the choice of a car, cycling, walking, or public transport. In total, 529 participants reported using a car, of whom 65.8% had medium or high education levels. These participants were more likely to be younger, male, married, and employed. Among bicycle users, statistically significant differences between the employment status, body mass index, and travel distance were observed. Walkers were significantly more likely to be older, those with lower incomes, unemployed, and travelling the shortest distances. The analysis of the travel distance on the choice of the travel mode revealed that men travelled longer distances with a car compared to women. The employment status was significantly associated with travel distance by car or public transport. Employed individuals travelled longer distances by public transport or by car, compared to unemployed individuals. Among bicycle users, we found that people with higher levels of education and overweight individuals cycled the longest distances. Our study emphasizes the importance of considering different individual characteristics when analysing the choice of transport modes. It provides evidence that is relevant for all urban populations on the choice of the transport mode, particularly considering active versus passive transport.     

Joint estimation of mode and time of day choice accounting for arrival time flexibility,travel time reliability and crowding on public transport

This study develops joint choice models of mode and departure time for implementation in MetroScan, a new version of TRESIS (Hensher and Ton, 2002). Separate models are estimated for work and non-work purposes, testing all practical alternatives of model structure with a rich set of explanatory variables. The contributions of the current work to the existing TRESIS are twofold. First, travel demand for non-work purposes such as shopping, social and recreation are explicitly modelled in MetroScan as opposed to TRESIS that scales the demand for work purposes to obtain non-work travel demand. Second, choices of travel mode and departure time become more sensitive to situational factors such as the flexibility of arrival time, the reliability of travel time and crowding. Willingness to pay for various improvements to the level of service is derived. We describe and demonstrate how the proposed models are applied in the general modelling framework of MetroScan.     

An exploratory analysis of relationships between socioeconomic,land use,activity participation variables and travel patterns

This paper aims to find relations between the socioeconomic characteristics, activity participation, land use patterns and travel behavior of the residents in the São Paulo Metropolitan Area (SPMA) by using Exploratory Multivariate Data Analysis (EMDA) techniques. The variables influencing travel pattern choices are investigated using: (a) Cluster Analysis (CA), grouping and characterizing the Traffic Zones (TZ), proposing the independent variable called Origin Cluster and, (b) Decision Tree (DT) to find a priori unknown relations among socioeconomic characteristics, land use attributes of the origin TZ and destination choices. The analysis was based on the origin–destination home-interview survey carried out in SPMA in 1997. The DT application revealed the variables of greatest influence on the travel pattern choice. The most important independent variable considered by DT is car ownership, followed by the Use of Transportation “credits” for Transit tariff, and, finally, activity participation variables and Origin Cluster. With these results, it was possible to analyze the influence of a family income, car ownership, position of the individual in the family, use of transportation “credits” for transit tariff (mainly for travel mode sequence choice), activities participation (activity sequence choice) and Origin Cluster (destination/travel distance choice).     

Mitigating the impact of errors in travel time reporting on mode choice modelling

Travel time is a major component in understanding travel demand. However, the quantification of demand and forecasting hinges on understanding how travel time is perceived and reported. Travel time reporting is typically subject to errors and this paper focuses on the mitigation of their impact on choice models. The aim is to explain the origin of these errors by including elements of travel behaviour (e.g., activities during the trip), which have been shown to significantly affect mode choices and commuting satisfaction. Based on responses from a revealed preferences survey, we estimate a mode choice model that treats travel time as a latent variable and incorporates different sources of data along with information on travel activities. Employing these multiple – sometimes incongruent – sources of information in the choice model appears to be beneficial. Results from comparing a logit model assuming error-free inputs and the integrated hybrid model revealed significant impacts on the generated policy scenarios. The model results also contributed to identifying the main travel activity features that affect travel time reporting, providing indications that can assist in understanding and mitigating the impact of imprecise measurements.     

The end of travel time matrices: Individual travel times in integrated land use/transport models

To reduce inaccuracies due to insufficient spatial resolution of models, it has been suggested to use smaller raster cells instead of larger zones. Increasing the number of zones, however, increases the size of a matrix to store travel times, called skim tables in transport modeling. Those become difficult to create, to store and to read, while most of the origin-destination pairs are calculated and stored but never used. At the same time, such approaches do not solve inaccuracies due to lack of temporal resolution. This paper analyzes the use of personalized travel times at the finest spatial resolution possible (at x/y coordinates) and a detailed temporal resolution for synthetic agents. The approach is tested in the context of an existing integrated land use/transport model (ILUT) where travel times affect, among others, household relocation decisions. In this paper, person-level individual travel times are compared to traditional skim-based travel times to identify the extent of errors caused by spatial and temporal aggregation and how they affect relocation decisions in the model. It was shown that skim-based travel times fail to capture the spatial and temporal variations of travel times available at a microscopic scale of an agent-based ILUT model. Skims may provide acceptable averages for car travel times if a dense network and small zones are used. Transit travel times, however, suffer from temporal and spatial aggregation of skims. When analyzing travel-time-dependent relocation decisions in the land use model, transit captive households tend to react more sensitively to the transit level of service when individual travel times are used. The findings add to the existing literature a quantification of spatial biases in ILUT models and present a novel approach to overcome them. The presented methodology eliminates the impact of the chosen zone system on model results, and thereby, avoids biases caused by the modifiable spatial unit problem.     

Identification of determinants for rescheduling travel mode choice and transportation policies to reduce car use in urban areas

This paper presents a qualitative analysis about the determinants related to rescheduling travel mode decisions during the activity scheduling process. Notably, we were interested to study changes between intention and behavior. Data used came from an in-depth Computer Assisted Telephone Interview (CATI) follow up survey to habitual drivers carried out during the implementation of a panel survey. An interpretative qualitative method based on Analytic Induction was used to cope with the complex nature of rescheduling decisions and the characteristics of the data. The Theory of Planned Behavior has been used to gain a better understanding of the reasons associated with rescheduling travel mode decisions and to obtain a possible explanation of the phenomena studied. In our sample, 12 codes were identified as the main determinants of travel mode changing. Main reasons for rescheduling a travel mode are different considering gender, age, and the type of travel mode change. Main reasons for changing a nonprivate preplanned travel mode to a private travel mode are different considering the type of travel mode preplanned. New determinants of rescheduling decisions different from those associated with other activity scheduling decisions previously identified emerge when analyzing travel mode changes. A number of important sustainable transportation policies to reduce car use in urban areas are derived from the results of this study.     

A MILP model for planning the trips of dynamic positioned tankers with variable travel time

The transportation of the crude oil produced in offshore oilfields to onshore terminals is performed by vessels, known as shuttle tankers. Scheduling shuttle-tanker operations entails solving complex problems to ensure a timely offloading of the platforms, taking into account several logistics and inventory constraints. This work proposes a new MILP formulation that advances previous works by considering variable travel time between platforms and terminals. The combination of the MILP formulation with an optimization solver constitutes a decision-support tool to aid engineers reach optimal decisions for a planning horizon. To handle large-scale instances, rolling-horizon and relax-and-fix strategies are proposed.     

Gendered key events in the life course: effects on changes in travel mode choice over time

This paper studies changes in travel mode specific trip rates after life course (and accessibility) related key events from a gender perspective. It is theoretically informed by the mobility biographies approach, and by gender/travel studies. The data used is the German Mobility Panel (GMP) 1994 to 2010 in which households and their members are asked three times in three subsequent years to report the trips they made over a week. The changes reported are regressed to key events over the life course, cohort effects and period effects, while sociodemographics and spatial context attributes are controlled. A cluster–robust regression approach is used to account for the non-independent character of panel observations. Significant effects were found for some key events, including the birth of a child, entry into the labour market, and changes in spatial context, accessibility and mobility. Some effects differed distinctly between men and women, suggesting that men and women are differently affected by life course events. However, taken together the associations found, as well as their gender differences are rather limited. Hence, key events over the life course seem to be only loosely associated with travel mode specific trip rates.     

Walking down the habitual lane: analyzing path dependence effects of mode choice for social trips

In the field of transportation, several studies have researched commute mode choice and its dynamics in the short and in the long term. Relatively less is known about mode choice for discretionary and more flexible activities, such as social visits. These choices are dynamic and depend on personal habits and preferences, reflected to some extent in the history of similar choices. This study adopts the theory of path dependence to take life cycle dynamics and habitual preferences into account. Using a dataset collected in the Netherlands in 2011, a multinomial logit model of mode choice was developed. Results suggest that mode choices for social activities are path dependent, yet not entirely. There is also evidence of switching towards faster and more flexible modes after a life cycle event.     

The impact of metropolitan,county, and local land use on driving emissions in US metropolitan areas: Mediator effects of vehicle travel characteristics

Many municipalities in the U.S. pursue compact development to reduce greenhouse gas (GHG) emissions from driving. Despite the efforts, however, recent studies suggest that some land use strategies such as densification and mixed-use development may result in slower vehicle movements, and consequently generate more driving emissions. Since vehicle miles of travel (VMT) is only a proxy and not an exact measure of emissions, reduction in VMT may not lead to a proportional reduction in transportation GHG emissions. Aside from local land use efforts, regional factors also influence vehicle travel and associated emissions.This study investigates the relationship between land use, vehicle travel, and driving emissions in the selected U.S. metropolitan areas at multiple geographic levels. The study employed structural equation modeling (SEM) techniques to examine how land use influences vehicle travel characteristics and associated emissions. The main data sources for the analyses include the 2009 National Household Travel Survey (NHTS) add-on samples and the Smart Location Database (SLD) from the U.S. Environmental Protection Agency (EPA). The study results show that VMT reduction and the associated environmental benefit do not show a one-on-one relationship due to the emissions penalty of lowered vehicle operating speed. Vehicle travel and associated emissions are not only influenced by local urban form factors but also affected by the greater geographical context.     

The effect of travel cost on frequencies of shopping and recreational trips in Sweden

This article focus on how the cost of travel affects travel behavior. A trip frequency model for recreational and shopping trips is suggested and used to investigate this. The data that is used comes from a Swedish travel habit survey where the respondents’ trip frequencies of both types of trips on a certain day are recorded. This is likely to introduce a correlation structure, which is incorporated in the model. Special attention is paid to the effect of travel cost on trip frequencies for different regions and income groups. As a measure of the sensitivity of cost changes, elasticity of demand is calculated. The precision of the elasticities are evaluated with simulated p-values.     

The indirect effect of the built environment on travel mode choice: A focus on recent movers

Many studies have demonstrated that the built environment has a strong impact on people's travel mode choice. However, the built environment also influences elements such as travel distance and car ownership, which might be the true predictors of which travel modes are chosen. In this study, we analyse the effects of changes in residential neighbourhood on changes in travel mode (for commute trips and leisure trips), both directly and indirectly through changes in car ownership, travel distances and travel attitudes. This study applies a structural equation modelling approach using quasi-longitudinal data from 1650 recently relocated residents in the city of Ghent, Belgium. Results indicate that the built environment has strong direct effects on active leisure trips and car use. However, distance (for car use) and attitudes (for active travel) were found to be important mediating variables. In sum, the effect of the built environment on travel mode choice might be more complex than commonly assumed as it partly seems mediated by travel distance and travel attitudes.     

The path and time efficiency of residents' trips of different purposes with different travel modes: An empirical study in Guangzhou,China

Improving residents' travel efficiency and reducing carbon emissions from travel are the key issues for sustainable development of urban transportation. This study first employed a circuity index to measure the path efficiency of residents' trips based on 2015 survey data in Guangzhou and developed a generalized additive model (GAM) to investigate the relationship between the path efficiency and travel distance for different purposes of trip and different travel modes. On this basis, it further evaluated the time efficiency of different travel modes for each trip. The results showed that there is a complex and nonlinear relationship between the path efficiency and travel distance, which differs between different purposes of trips and different travel modes. In general, trips by non-motorized transport have a lower circuity index and higher path efficiency than those by cars or public transport. Moreover, non-motorized transport is the time-efficiency optimal mode for almost half of the trips, especially for daily shopping trips. However, people prefer to choose public transport on their trips even though public transport is not the time-efficiency optimal mode for these trips. Generally, only about half of the residents chose the time-efficiency optimal mode for their trips. Those who did not choose the time-efficiency optimal mode tended to choose the modes with higher carbon-intensity. The conclusions of this study indicate that for improving travel efficiency and reducing carbon emissions from transport, more efforts should be focused on the non-motorized travel environment and developing relevant policies to encourage more walking and cycling.     

Determinants of travel mode choice for seeking healthcare: A comparison between elderly and non-elderly patients

People's travel mode choices can vary significantly by age group due to different influencing factors, but relevant research on health-related travel is scarce. In this study, we explored and compared the determinants of travel mode choice for healthcare-seeking non-elderly and elderly patients in Beijing, China. A multinomial logit model was used to analyze data from a recent healthcare-seeking behavior survey. The results show that increased age discourages car use and slightly prompts non-motorized travel in the non-elderly, but has the opposite effect in the elderly group. Household income has a negative effect on non-motorized travel in the non-elderly, but a positive effect in elderly patients. Highly mixed land use, intensive urban development, and difficulty in parking discourage non-elderly patients from traveling by car, but none of these factors have a significant effect on the elderly. Our findings shed light on the unique transportation demands for different age cohorts and inform the creation of age-specific interventions to improve overall access to health.     

Influences of rural built environment on travel mode choice of rural residents: The case of rural Sichuan

China has entered a stage in which new rural construction and urbanization are rapidly developing. Considerable changes are occurring in rural China, and the built environment is different from that in the past; such difference directly influences the travel mode choice of rural residents. However, our knowledge on how the rural built environment influences the travel mode choice of rural residents in China remains limited. To fill this gap, this study combines on-site measurement methods, geographic information system (GIS) technology, and activity diary survey to obtain basic data regarding the built environment and the daily activities of rural residents. The multinomial logit (MNL) model is used to explore the relationship between the rural built environment and the travel mode choice of rural residents. Results show that building density significantly positively affects private car trips. This finding challenges earlier urban built environment research due to the considerable gap between rural and urban areas. An increase in road density increases the travel frequency of electric bicycles and motorcycles. Accessibility perception and preferences positively affect the probability of choosing to walk. Safety and neighborhood harmony perception positively affect the travel frequency of motorcycles and private cars. Rural residents who prefer a safe living environment are likely to choose walking for their daily travel. Despite the considerable achievements in the construction of rural roads, the frequency of public transportation remains low for rural residents. Therefore, additional attention should be given to the investment and construction of public transport facilities during rural urbanization.     

A model for time of day and mode choice using error components logit

The severity of road congestion not only depends on the relation between traffic volumes and network capacity, but also on the distribution of car traffic among different time periods during the day. A new error components logit model for the joint choice of time of day and mode is presented, estimated on stated preference data for car and train travellers in The Netherlands. The results indicate that time of day choice in The Netherlands is sensitive to changes in peak travel time and cost and that policies that increase these peak attributes will lead to peak spreading.     

Role of user's socio-economic and travel characteristics in mode choice between city bus and informal transit services: Lessons from household surveys in Visakhapatnam,India

Informally operated paratransit or Intermediate Public Transport (IPT) systems provide demand responsive transit in many developing countries, often competing with formal public transport systems. Literature on the relative user characteristics of the two modes and their choice behaviour between the systems is limited. This article addresses the gap by presenting a methodology to derive a comprehensive understanding of socio-economic and travel demand characteristics of all transit users in a city. The household survey based data collection and analysis framework is demonstrated for the case of Visakhapatnam, a medium sized Indian city. The variables impacting users' choice between the formal and informal modes were derived through binary logistic regression. It was observed that gender, income and travel time have a significant influence on users' choice between the modes, with waiting time having the maximum impact on mode choice. Therefore, the high frequency services offered by paratransit attract users making shorter trips.     

Built environment effects on leisure travel for children: Trip generation and travel mode

This study empirically analyzed the effects of built environment on leisure travel among children. Students of three elementary schools, namely Yangmingshan, Sanyu and Shilin, all located in the Shilin District of Taipei, were chosen to provide sample data. The negative binomial regression model and multinomial logit model were used to analyze trip generation and travel mode, respectively. This study reached the following empirical findings: (1) mixed land use, employment density, walkway quality, leisure facility supply and leisure travel distance encouraged generation of leisure trips for children; (2) intersection density, building density, employment density and walkway quality encouraged a child to use transit systems or non-motorized travel modes for leisure travel; and (3) vehicle density and leisure travel distance discouraged walking and biking but encouraged the use of transit systems for leisure travel involving children. Local government can use the empirical findings of this study to develop urban planning strategies to encourage children to perform leisure activities outside the home using transit systems or non-motorized travel modes.     

The influence of personality traits on airport public transport access mode choice: A hybrid latent class choice modeling approach

Many objective and subjective factors affect individual tendencies. Such subjective factors include personality traits, attitudes, identities, perceptions, and feelings. The choice of transportation mode is an individual tendency that is considered important in policy-making decisions, and it can affect sustainable transportation, particularly in metropolitan areas. The present study’s main aim is to determine the impact of the Big Five Personality Factors on individual preferences toward public transportation modes. We use data from a survey conducted in January and February of 2015 at Imam Khomeini International Airport (IKIA). Passengers were asked to indicate their preferred mode of transportation to access the IKIA and to respond to questions on the NEO Five-Factor Inventory. Based on 557 valid responses, hybrid discrete latent class modeling was conducted to understand the heterogeneity in the respondents’ individual preferences regarding the Big Five Personality Factors and their preferences toward public modes of transportation. The results indicated that individuals who display neuroticism were more likely than the others to be concerned about carrying heavy luggage and about inclement weather conditions when using public transportation. In addition, interesting results indicated that conscientious individuals likely paid more attention to travel cost than to any other attribute of public transportation, and the model of the conscientious latent personality trait was a better fit to the data. Finally, this paper examined the taste heterogeneity of each personality trait and the results indicate the usefulness of considering personality traits in mode choice models for richer insights toward sustainable transportation.