Modeling traveler mode choice behavior of a new high-speed rail corridor in China

This study examines mode choice behavior for intercity business and personal/recreational trips. It uses multinomial logit and nested logit methods to analyze revealed preference data provided by travelers along the Yong-Tai-Wen multimodal corridor in Zhejiang, China. Income levels are found to be positively correlated with mode share increases for high-speed rail (HSR), expressway-based bus, and auto modes, while travel time and trip costs are negatively correlated with modal shift. Longer distance trips trigger modal shifts to HSR services but prevent modal shift to expressway-based auto use due to escalation of fuel cost and toll charges. Travelers are less elastic in their travel time and cost for trips by nonexpressway-based auto use modes. The magnitude of elasticity for travel time is higher than trip costs for business trips and lower for personal/recreational trips. The study provides some policy suggestions for transportation planners and decision-makers.     

Understanding the development of business travel policies: Reducing business travel,motivations and barriers

Business travel accounted in the UK in 2010 for 3% of trips and 10% of the UK’s domestic distance travelled (Department for Transport, 2011, p. 4). However, it is an under researched area, even though in major cities, where transport networks are most congested, it forms a higher proportion of trips. The paper presents the findings of a study of changing business travel practices and policies affecting the briefcase traveller. The findings are drawn from semi-structured interviews with key actors in stakeholder and private sector organisations based predominately in London and a survey of 150 business travellers. The study was designed to understand the motivations and attitudes towards reducing business travel and the compromises that needed to be made to balance reducing carbon emissions and cost, whilst maintaining or improving productivity and meeting the requirements of the business.The main findings show the approaches and implications of these approaches to reduce carbon emissions and costs, improve productivity and the impact of ICT. The findings show the importance of external reporting through the Carbon Reduction Commitment, the Carbon Disclosure Project and corporate responsibility reports as a motivator to develop new policies. The paper goes on to outline how some factors can be both barriers and motivations for change, such as customers insisting on meeting their suppliers face-to-face, but also requiring information on carbon emissions as part of the Carbon Disclosure Project. Individuals can also be both a barrier and a motivator to change. The role of existing travel and meeting habits and the view of some that travelling is a perk linked to status symbols have proved to be a hard barriers to overcome. However, a technically literate younger generation used to communicating virtually have challenged these practices.     

Travel,transport and energy implications of university-related student travel: A case study approach

This study highlighted significant cultural differences and complexity in travel behaviour associated with travel to university across the UK and Ireland. This paper examines university travel behaviours and the implications for emissions, across the 2012–2013 academic year, based on responses from 1049 students across 17 universities in Ireland and the UK. Surveys were analysed to examine the trips of students both during term time and when accessing the universities each year. The data analysis in this paper examines three aspects of the transport implications of travel to and from university. Firstly the journey between university and term time address (or permanent address if the respondent does not have a separate term time address), secondly the journey between the university area and a separate permanent address where relevant; and thirdly implications for emissions resulting from university-related travel.The study found that student car users were more likely to be female, older students, or studying part time; male students were more likely to use active modes. The study indicated interesting differences between students living in different parts of the UK and Ireland. For example, it was found that there was a higher level of car dependence amongst Northern Irish students compared to other areas; and a greater variability in travel distances in Scotland and Northern Ireland. In England, car use was more pronounced when students travelled from their permanent address to term time address, and, as in Ireland, there was evidence of more car sharing on such trips. Public transport usage was more pronounced amongst Scottish students. The effect of these transport choices on emissions is significant and demonstrates the importance of education related trips to the development of a transport policy response. The analysis shows that annual emissions are highest for regular travel to and from university when a student has a permanent address rather than a separate term time and permanent address.     

Investigating travel utility elements in association with travel time and mode choice: the case of Seoul,South Korea

In this paper, travel utility is conceptualized into the elements of disutility, or derived utility, and positive utility, which includes synergistic and intrinsic utility, and then analyzed in terms of the effects of these elements on weekly travel time according to three travel modes – the automobile, public transit, and nonmotorized modes – and on the choice of the annually most used mode. Linear regressions on mode-specific travel time and a multinomial logistic regression on mode choice show that, compared to life situation and land-use characteristics, utility elements are among the strongest travel determinants. Specifically, while some utility elements contribute exclusively to shifting the mode of travel and others to increasing nonmotorized travel, modal shift is most strongly affected by a disutility element, trip timeliness, and the increase in nonmotorized travel by a positive utility element, amenities.     

Joint leisure travel optimization with user-generated data via perceived utility maximization

The lack of personalized solutions for managing the demand of joint leisure trips in cities in real time hinders the optimization of transportation system operations. Joint leisure activities can account for up to 60% of trips in cities and unlike fixed trips (i.e., trips to work where the arrival time and the trip destination are predefined), leisure activities offer more optimization flexibility since the activity destination and the arrival times of individuals can vary.To address this problem, a perceived utility model derived from non-traditional data such as smartphones/social media for representing users’ willingness to travel a certain distance for participating in leisure activities at different times of day is presented. Then, a stochastic annealing search method for addressing the exponential complexity optimization problem is introduced. The stochastic annealing method suggests the preferred location of a joint leisure activity and the arrival times of individuals based on the users’ preferences derived from the perceived utility model. Test-case implementations of the approach used 14-month social media data from London and showcased an increase of up to 3 times at individuals’ satisfaction while the computational complexity is reduced to almost linear time serving the real-time implementation requirements.     

Accommodating risk in the valuation of expected travel time savings

Valuation of travel time savings is a critical measure in transport infrastructure appraisal, traffic modelling and network performance. It has been recognised for some time that the travel times associated with repeated trips are subject to variation, and hence there is risk embedded in the treatment of expected travel time. In the context of the expected utility framework, we use a nonlinear probability weighting function to accommodate choice made under risk. Although the empirical findings suggest small differences between the value of expected travel time savings (VETTS) in the presence and absence of risk, the mean estimate does make a noticeable difference to time benefits when applied to real projects. By incorporating nonlinear probability weighting, our model reveals that the probabilities associated with specific travel times that are shown to respondents in the choice experiment are transformed, resulting in overweighting of outcomes with low probabilities and underweighting of outcomes with high probabilities. Copyright © 2011 John Wiley & Sons, Ltd.     

The influence of individuals’ environmental attitudes and urban design features on their travel patterns in sustainable neighborhoods in the UK

This paper explores the influence of individuals’ environmental attitudes and urban design features on travel behavior, including mode choice. It uses data from residents of 13 new neighborhood UK developments designed to support sustainable travel. It is found that almost all respondents were concerned about environmental issues, but their views did not necessarily ‘match’ their travel behavior. Individuals’ environmental concerns only had a strong relationship with walking within and near their neighborhood, but not with cycling or public transport use. Residents’ car availability reduced public transport trips, walking and cycling. The influence of urban design features on travel behaviors was mixed, higher incidences of walking in denser, mixed and more permeable developments were not found and nor did residents own fewer cars than the population as a whole. Residents did, however, make more sustainable commuting trips than the population in general. Sustainable modes of travel were related to urban design features including secured bike storage, high connectivity of the neighborhoods to the nearby area, natural surveillance, high quality public realm and traffic calming. Likewise the provision of facilities within and nearby the development encouraged high levels of walking.     

Women,travel and the idea of 'sustainable transport'

Women form an increasingly large proportion of both the populations of the US and of European countries. This, together with the changing role of women in modern society, has important potential implications for transport policy. Looked at from the micro level, women have different travel patterns from men, reflecting factors such as lower labour force participation, lower income levels, their traditional role in the family, the decision-making structure within households, the current age distribution and physical vulnerability. The situation is changing and this will have implications on transport demands. The female population is also, on average, getting older. Traditional travel modelling spends much time on modal attributes, such as speed and cost, but for many women this may not be the central issue. Security is often important. Standard traffic models only implicitly allow for gender (e.g. travel time is valued different from work and non-work trips). With the increased complexity of life styles and the growth in multi-purpose trips by women, the conventional approach to travel time valuation may need to be rethought. This paper looks at some of the emerging issues regarding women and travel and puts them in the context of the emerging ideas concerning sustainable transport.     

Estimating the trip generation impacts of autonomous vehicles on car travel in Victoria,Australia

Autonomous vehicles (AVs) potentially increase vehicle travel by reducing travel and parking costs and by providing improved mobility to those who are too young to drive or older people. The increase in vehicle travel could be generated by both trip diversion from other modes and entirely new trips. Existing studies however tend to overlook AVs’ impacts on entirely new trips. There is a need to develop a methodology for estimating possible impacts of AVs on entirely new trips across all age groups. This paper explores the impacts of AVs on car trips using a case study of Victoria, Australia. A new methodology for estimating entirely new trips associated with AVs is proposed by measuring gaps in travel need at different life stages. Results show that AVs would increase daily trips by 4.14% on average. The 76+ age group would have the largest increase of 18.5%, followed by the 18–24 age group and the 12–17 age group with 14.6 and 11.1% respectively. If car occupancy remains constant in AV scenarios, entirely new trips and trip diversions from public transport and active modes would lead to a 7.31% increase in car trips. However increases in car travel are substantially magnified by reduced car occupancy rates, a trend evidenced throughout the world. Car occupancy would need to increase by at least 5.3–7.3% to keep car trips unchanged in AV scenarios.     

A micro-analysis of land use and travel in five neighborhoods in the San Francisco Bay Area

This study examined the effects of land use and attitudinal characteristics on travel behavior for five diverse San Francisco Bay Area neighborhoods. First, socio-economic and neighborhood characteristics were regressed against number and proportion of trips by various modes. The best models for each measure of travel behavior confirmed that neighborhood characteristics add significant explanatory power when socio-economic differences are controlled for. Specifically, measures of residential density, public transit accessibility, mixed land use, and the presence of sidewalks are significantly associated with trip generation by mode and modal split. Second, 39 attitude statements relating to urban life were factor analyzed into eight factors: pro-environment, pro-transit, suburbanite, automotive mobility, time pressure, urban villager, TCM, and workaholic. Scores on these factors were introduced into the six best models discussed above. The relative contributions of the socio-economic, neighborhood, and attitudinal blocks of variables were assessed. While each block of variables offers some significant explanatory power to the models, the attitudinal variables explained the highest proportion of the variation in the data. The finding that attitudes are more strongly associated with travel than are land use characteristics suggests that land use policies promoting higher densities and mixtures may not alter travel demand materially unless residents' attitudes are also changed.     

GHG emissions in daily travel and long-distance travel in Germany – Social and spatial correlates

There is considerable research on the climate effects of daily travel, including research on the spatio-temporal and socioeconomic impact factors of daily travel and associated climate change effects. However, this is less true with respect to long-distance trips. This paper uses national transport survey data from Germany to point out differences in GHG emissions related to demographic, socioeconomic and spatial characteristics for daily and long-distance travel. Daily travel and long-distance travel are investigated simultaneously and separately using Logit and OLS regressions. The results show that transport-related GHG emissions from long-distance trips and daily trips are affected by sociodemographics in largely the same direction. In contrast, spatial attributes, like municipality size or density grade of the region, show a different picture. Per capita emissions in rural and suburban areas are higher for daily trips, but lower for long-distance trips than emissions caused by urban residents. While we cannot rule out the possibility of residential self-selection, our findings challenge the idea that compact urban development may help reduce CO₂ emissions once long-distance trips are taken into account.     

The impact of extreme weather conditions on long distance travel behaviour

This paper examines traveller attitudes and responses towards disruption from weather and natural events. An internet-based travel behaviour survey was conducted with more than 2000 respondents in London and Glasgow. Of these respondents, 740 reported information on over 1000 long distance trips affected by extreme weather and natural events over the previous three years. Results show respondents are generally cautious towards travelling during extreme weather events. For a slight majority in the case of air and public transport, and a greater one in the case of car, travellers did not considerably alter their travel plan following the disruption. This was explained not only by less disruptive weather conditions (with heavy snow and volcanic ash being the most disruptive) and impact, but also by the relative importance of their trips. Differences between transport modes were not substantial. Business trips sometimes appeared to give travellers more flexibility, some other times not. Origin and destination did have an impact on reaction, as well as the presence of children whilst travelling. Mixed results were obtained about socio-economic and attitudinal variables. Age in particular did not appear to have a significant effect. Whilst most respondents did acknowledge no external influence in their decision, results showed an important contribution of transport organisation staff, as well as home and mobile internet technology. A limited but still considerable number of respondents indicated their closest friends/relatives as the main influence of their decisions. The results will help planners deploy strategies to mitigate the negative effects of weather related disruptions.     

Multimodal travel groups and attitudes: A latent class cluster analysis of Dutch travelers

For developing sustainable travel policies, it may be helpful to identify multimodal travelers, that is, travelers who make use of more than one mode of transport within a given period of time. Of special interest is identifying car drivers who also use public transport and/or bicycle, as this group is more likely to respond to policies that stimulate the use of those modes. It is suggested in the literature that this group may have less biased perceptions and different attitudes towards those modes. This supposition is examined in this paper by conducting a latent class cluster analysis, which identifies (multi)modal travel groups based on the self-reported frequency of mode use. Simultaneously, a membership function is estimated to predict the probability of belonging to each of the five identified (multi)modal travel groups, as a function of attitudinal variables in addition to structural variables. The results indicate that the (near) solo car drivers indeed have more negative attitudes towards public transport and bicycle, while frequent car drivers who also use public transport have less negative public transport attitudes. Although the results suggest that in four of the five identified travel groups, attitudes are congruent with travel mode use, this is not the case for the group who uses public transport most often. This group has relatively favorable car attitudes, and given that many young, low-income travelers belong to this group, it may be expected that at least part of this group will start using car more often once they can afford it. Based on the results, challenges for sustainable policies are formulated for each of the identified (multi)modal travel groups.     

A model for integrated analysis of household location and travel choices

We develop a model for integrated analysis of household location and travel choices and investigate it from a theoretical point of view.Each household makes a joint choice of location (zone and house type) and a travel pattern that maximizes utility subject to budget and time constraints. Prices for housing are calculated so that demand equals supply in each submarket. The travel pattern consists of a set of expected trip frequencies to different destinations with different modes. The joint time and budget constraints ensure that time and cost sensitivities are consistent throughout the model. Choosing the entire travel pattern at once, as opposed to treating travel decisions as a series of isolated choices, allows the marginal utilities of trips to depend on which other trips are made.When choosing trip frequencies to destinations, households are assumed to prefer variation to an extent varying with the purpose of the trip. The travel pattern will tend to be more evenly distributed across trip ends the less similar destinations and individual preferences are. These heterogeneities of destinations and individual preferences, respectively, are expressed in terms of a set of parameters to be estimated.     

A comparative analysis of traditional four-step and activity-based travel demand modeling: a case study of Tampa,Florida

Activity-based travel demand modeling (ABTDM) has often been viewed as an advanced approach, due to its higher fidelity and better policy sensitivity. However, a review of the literature indicates that no study has been undertaken to investigate quantitatively the differences and accuracy between an ABTDM approach and a traditional four-step travel demand model. In this paper we provide a comparative analysis against each step – trip generation, trip distribution, mode split, and network assignment – between an ABTDM developed using travel diary data from the Tampa Bay Region in Florida and the Tampa Bay Regional Planning Model (TBRPM), an existing traditional four-step model for the same area. Results show salient differences between the TBRPM and the ABTDM, in terms of modeling performance and accuracy, in each of the four steps. For example, trip production rates calculated from the travel diary data are found to be either double or a quarter less than those used in the TBRPM. On the other hand, trip attraction rates computed from activity-based travel simulations are found to be either more than double or one tenth less than those used in the TBRPM. The trip distribution curves from the two models are similar, but both average and peak trip lengths of the two are significantly different. Mode split analyses show that the TBRPM may underestimate driving trips and fail to capture any usage of alternative modes, such as taxi and nonmotorized (e.g., walking and bicycling) modes. In addition, the ABTDMs are found to be less capable of reproducing observed traffic counts when compared to the TBRPM, most likely due to not considering external and through trips. The comparative results presented can help transportation engineers and planners better understand the strengths and weaknesses of the two types of model and this should assist decision-makers in choosing a better modeling tool for their planning initiatives.     

Identifying travel mode with GPS data

Travel mode identification is an essential step in travel information detection with global positioning system (GPS) survey data. This paper presents a hybrid procedure for mode identification using large-scale GPS survey data collected in Beijing in 2010. In a first step, subway trips were detected by applying a GPS/geographic information system (GIS) algorithm and a multinomial logit model. A comparison of the identification results reveals that the GPS/GIS method provides higher accuracy. Then, the modes of walking, bicycle, car and bus were determined using a nested logit model. The combined success rate of the hybrid procedure was 86%. These findings can be used to identify travel modes based on GPS survey data, which will significantly improve the efficiency and accuracy of travel surveys and data analysis. By providing crucial travel information, the results also contribute to modeling and analyzing travel behaviors and are readily applicable to a wide range of transportation practices.     

The impact of transit station areas on the travel behaviors of workers in Denver,Colorado

Transit development is one planning strategy that seeks to partially overcome limitations of low-density single use car oriented development styles. While many studies focus on how residential proximity to transit influences the travel behaviors of individuals, the effect of workplace proximity to transit is less understood. This paper asks, does working near a light rail transit station influence the travel behaviors of workers differently than workers living near a station? We begin by examining workers’ commute mode based on their residential and workplace proximity to transit station areas. Next, we analyze the ways in which personal travel behaviors differ between those who drive to work and those who do not. The data came from a 2009 travel behavior survey in the Denver, Colorado metropolitan area, which contains 8000 households, 16,000 individuals, and nearly 80,000 trips. We measure sustainable travel behaviors as reduced mileage, reduced number of trips, and increased use of non-car transportation. The results of this study indicate that living near a transit station area by itself does not increase the likelihood of using non-car modes for work commutes. But if the destination (work) is near a transit station area, persons are less likely to drive a car to work. People who both live and work in a transit station area are less likely to use a car and more likely to take non-car modes for both work and non-work (personal) trips. Especially for persons who work near a transit station area, the measures of personal trips and distances show a higher level of mobility for non-car commuters than car commuters – that is, more trips and more distant trips. The use of non-car modes for personal trips is most likely to occur by non-car commuters, regardless of their transit station area relationship.     

Active travel as a pro-environmental behaviour: An integrated framework

A travel mode may be chosen due to its emotional appeal (affective motive) or to express social status (symbolic motive). Previous studies have overlooked the role of such motives in active mode use as pro-environmental behaviour. This study aims to examine the role of symbolic and affective motives, together with other significant theoretical perspectives, to explain the share of active modes of transport in trips to the university. It adds to the previous literature by considering the share of active modes of transport in different seasons. We collected a total of 316 completely filled questionnaires (response rate = 75.4 percent) from a cross-sectional self-administered survey in February 2019 in Trondheim, Norway. Among the psychological variables related to active mode use, only affective motives were found significant in both summer and winter. Environmental self-identity predicted both types of motives. No evidence suggested that personal environmental norms and attitudes towards transportation significantly explained active mode share, although car-related subjective norms reached significance. Furthermore, there was no evidence that environmental attitudes towards transportation had a mediating effect between motives and active mode use. Cycling journey time between place of residence and campus was found significant in the share of active modes of transport in both seasons. The results have important ramifications for the provision of relevant regulations and raising positive support from society to enhance the share of active modes of travel to the university.     

A utility-theory travel demand model incorporating travel budgets

A model of traveler behavior is proposed which is consistent with the possibility that travelers expend average daily amounts of time and money on travel with stable regularities both among urban areas and over time in the same area. The model is founded on economic utility theory. It is designed to forecast: (1) the amount of total travel generated by types of households, (2) the division of travel among available modes, and (3) the relationship between the amounts of time and money allocated to travel expenditures. The qualitative properties of the model are shown to be consistent with economic principles. Specific theoretical results reveal that, in the simultaneous presence of constraints on both time and money, travel budgets are not strictly constant proportions of income and time available as they are in the cases of single constraints relevant to classes of travelers to whom time is scarce compared to money, or conversely. Constant expenditure proportions are shown to be linear approximations which are subject to empirical validation. The relevant economic principle is that expenditures can be considered fixed in the short run but become flexible in the long run when utility maximization is applied to the expenditures themselves and not just to their allocation. Empirical tests of the model using data from three urban areas are positive, but additional tests are called for. The most important output of the research is deemed to be the establishment of theoretical hypotheses which can be used in continuing tests of travel budgets.