Understanding Travel Time Expenditures Around the World: Exploring the Notion of a Travel Time Frontier

Travel behavior researchers have been intrigued by the amount of time that people allocate to travel in a day, i.e., the daily travel time expenditure, commonly referred to as a “travel time budget”. Explorations into the notion of a travel time budget have once again resurfaced in the context of activity-based and time use research in travel behavior modeling. This paper revisits the issue by developing the notion of a travel time frontier (TTF) that is distinct from the actual travel time expenditure or budget of an individual. The TTF is defined in this paper as an intrinsic maximum amount of time that people are willing to allocate for travel. It is treated as an unobserved frontier that influences the actual travel time expenditure measured in travel surveys. Using travel survey datasets from around the world (i.e., US, Switzerland and India), this paper sheds new light on daily travel time expenditures by modeling the unobserved TTF and comparing these frontiers across international contexts. The stochastic frontier modeling methodology is employed to model the unobserved TTF as a production frontier. Separate models are estimated for commuter and non-commuter samples to recognize the differing constraints between these market segments. Comparisons across the international contexts show considerable differences in average unobserved TTF values.     

A model of household time allocation taking into consideration of hiring domestic helpers

Household maintenance such as childcare not only induces activities and travel but also impose time constraints on individuals’ participation in other activities and travel. Instead of sharing household responsibilities, households may hire domestic helpers for household maintenance. Alternatively, they may get helps from members of the extended family such as parents of household heads. This paper develops a model to analyze households’ trade-offs between hiring domestic helpers for household maintenance and taking these responsibilities by household members. We will apply household economic theories to develop a time allocation model incorporating interactions among household members. We assume that households trade off the money they are willing to spend for hiring helpers with the time they may need to spend for household maintenance activities to maximize utilities, subject to time constraints. The model may be used to analyze the impacts of domestic helpers on household members’ time allocation to subsistence, maintenance and recreation activities. It may also be applied to analyze the impacts of government policies regarding the minimum salary of domestic helpers and the change of household members’ wage rates on households’ decision to hire helpers. The paper extends the current literature on intra-household activity–travel interactions by considering external helps from domestic helpers, which may contribute to the understanding of activity–travel patterns of household members.     

Shopping without travel or travel without shopping? an investigation of electronic home shopping

This study explores the growth of electronic home shopping in terms of likely transportation and communication interactions. Although opportunities exist to shop from home today, most consumers initiate travel trips to stores or markets. Widespread use of automobiles has facilitated the retailing configurations we know today but the development of new electronic networks could change this. This study establishes a baseline to explore shopping activities using two‐day travel activity data from a large U.S. metropolitan area. It is found that people who telework from home today spend more time engaged in shopping activities than other workers. Potentially, their saved work travel is converted into new trips. In the future, saved shopping travel might be converted into other types of travel, and modelling results show that for busy working women, there is a latent demand for maintenance‐related activities. The study results suggest that electronic home shopping will bring into play complex interactions between communications and transportation.     

TTB or not TTB, that is the question: a review and analysis of the empirical literature on travel time (and money) budgets

This paper summarizes and analyses findings from more than two dozen aggregate and disaggregate studies of travel time (and sometimes money) expenditures, exploring the question of the existence of a constant travel time budget. We conclude (with prior researchers) that travel time expenditures are not constant except, perhaps, at the most aggregate level. Nevertheless, individuals’ travel time expenditures do show patterns that can be partly explained by measurable characteristics. Travel time expenditure is strongly related to individual and household characteristics (e.g., income level, gender, employment status, and car ownership), attributes of activities at the destination (e.g., activity group and activity duration), and characteristics of residential areas (e.g., density, spatial structure, and level of service). To the extent that travel time expenditures are constant at the aggregate level, the underlying mechanisms explaining that regularity are not well understood. Consequently, further research into explaining travel time and money expenditure patterns is justified.     

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 reliability‐based traffic assignment model for multi‐modal transport network under demand uncertainty

In densely populated and congested urban areas, the travel times in congested multi‐modal transport networks are generally varied and stochastic in practice. These stochastic travel times may be raised from day‐to‐day demand fluctuations and would affect travelers' route and mode choice behaviors according to their different expectations of on‐time arrival. In view of these, this paper presents a reliability‐based user equilibrium traffic assignment model for congested multi‐modal transport networks under demand uncertainty. The stochastic bus frequency due to the unstable travel time of bus route is explicitly considered. By the proposed model, travelers' route and mode choice behaviors are intensively explored. In addition, a stochastic state‐augmented multi‐modal transport network is adopted in this paper to effectively model probable transfers and non‐linear fare structures. A numerical example is given to illustrate the merits of the proposed model. Copyright © 2012 John Wiley & Sons, Ltd.     

Modeling the evolutions of day‐to‐day route choice and year‐to‐year ATIS adoption with stochastic user equilibrium

Suppose that in an urban transportation network there is a specific advanced traveler information system (ATIS) which acts for reducing the drivers' travel time uncertainty through provision of pre‐trip route information. Because of the imperfect information provided, some travelers are not in compliance with the ATIS advice although equipped with the device. We thus divide all travelers into three groups, one group unequipped with ATIS, another group equipped and in compliance with ATIS advice and the third group equipped but without compliance with the advice. Each traveler makes route choice in a logit‐based manner and a stochastic user equilibrium with multiple user classes is reached for every day. In this paper, we propose a model to investigate the evolutions of daily path travel time, daily ATIS compliance rate and yearly ATIS adoption, in which the equilibrium for every day's route choice is kept. The stability of the evolution model is initially analyzed. Numerical results obtained from a test network are presented for demonstrating the model's ability in depicting the day‐to‐day and year‐to‐year evolutions.     

Modelling rain effects on risk‐taking behaviours of multi‐user classes in road networks with uncertainty

This paper proposes a new travel time reliability‐based traffic assignment model to investigate the rain effects on risk‐taking behaviours of different road users in networks with day‐to‐day demand fluctuations and variations in travel time. A generalized link travel time function is used to capture the rain effects on vehicle travel times and road conditions. This function is further incorporated into daily demand variations to investigate those travel time variations arising from demand uncertainty and rain condition. In view of these rain effects, road users' perception errors on travel times and risk‐taking behaviours on path choices are incorporated in the proposed model with the use of a logit‐based stochastic user equilibrium framework. This new model is formulated as a variational inequality problem in terms of path flows. A numerical example is used to illustrate the application of the proposed model for assessment of the rain effects on road networks with uncertainty.     

A model for the layout of bike stations in public bike‐sharing systems

The problem of designing a layout of bike stations for public bike‐sharing systems entails selecting a number of stations and then constructing them within a planning area having many bike traffic zones and candidate bike stations. In this paper, we proposed a mathematical model to formulate the layout of public bike stations with the objective of minimizing users' total travel time and investment budget constraints. The model can guarantee that the needs for picking up and dropping off bikes amidst all bike travel demands are satisfied. Using this model, the number and locations of bike stations and the number of bikes and parking lockers at each bike station can be simultaneously determined. A typical example solved by lingo solver is created to illustrate the proposed model. Copyright © 2015 John Wiley & Sons, Ltd.     

Variations in household transport expenditure within major Australian cities

A comparative analysis of intra‐urban variations in household transport expenditure in 1966–68 is undertaken for the two largest Australian cities, Sydney and Melbourne, and one of the smaller State capitals, Adelaide. Regional variations in transport expenditure are found to be greater the larger the city; however residents of small cities are more dependent upon the car for their motorised travel. In the larger cities car dependence is most evident among low‐to‐middle income groups at a relatively early stage in the life cycle, located in outer suburban areas. Consequently high levels of expenditure on transport typically coincide with relatively high levels of financial commitments to home purchase and/or operation. This has significant ramifications for the household budget, the most notable being deficit‐funding, and reduced outlays on other expenditure items such as recreation and education. The distribution of company vehicles and allowances is shown to be of relatively greater benefit to higher income groups, although is not confined to them. Although somewhat dated, the findings suggest that the social impacts of rising prices for energy will almost certainly be regressive.

Note: This paper was presented to the 7th PTRC Summer Annual Meeting held at the University of Warwick in July 1979. The authors gratefully acknowledge the contribution of the Australian Road Research Board in the preparation of the paper. Particular appreciation is expressed to Dr. M. R. Wigan, Mr. K. Sharp and Dr. M. G. Lay for their helpful comments.     

Stochastic frontier estimation of budgets for Kuhn–Tucker demand systems: Application to activity time-use analysis

We propose a stochastic frontier approach to estimate budgets for the multiple discrete–continuous extreme value (MDCEV) model. The approach is useful when the underlying time and/or money budgets driving a choice situation are unobserved, but the expenditures on the choice alternatives of interest are observed. Several MDCEV applications hitherto used the observed total expenditure on the choice alternatives as the budget to model expenditure allocation among choice alternatives. This does not allow for increases or decreases in the total expenditure due to changes in choice alternative-specific attributes, but only allows a reallocation of the observed total expenditure among different alternatives. The stochastic frontier approach helps address this issue by invoking the notion that consumers operate under latent budgets that can be conceived (and modeled) as the maximum possible expenditure they are willing to incur. The proposed method is applied to analyze the daily out-of-home activity participation and time-use patterns in a survey sample of non-working adults in Florida. First, a stochastic frontier regression is performed on the observed out-of-home activity time expenditure (OH-ATE) to estimate the unobserved out-of-home activity time frontier (OH-ATF). The estimated frontier is interpreted as a subjective limit or maximum possible time individuals can allocate to out-of-home activities and used as the time budget governing out-of-home time-use choices in an MDCEV model. The efficacy of this approach is compared with other approaches for estimating time budgets for the MDCEV model, including: (a) a log-linear regression on the total observed expenditure for out-of-home activities and (b) arbitrarily assumed, constant time budgets for all individuals in the sample. A comparison of predictive accuracy in time-use patterns suggests that the stochastic frontier and log-linear regression approaches perform better than arbitrary assumptions on time budgets. Between the stochastic frontier and log-linear regression approaches, the former results in slightly better predictions of activity participation rates while the latter results in slightly better predictions of activity durations. A comparison of policy simulations demonstrates that the stochastic frontier approach allows for the total out-of-home activity time expenditure to either expand or shrink due to changes in alternative-specific attributes. The log-linear regression approach allows for changes in total time expenditure due to changes in decision-maker attributes, but not due to changes in alternative-specific attributes.     

Finding time‐robust fuel‐efficient paths for a call‐taxi in a stochastic city road network

Intra‐city commuting is being revolutionized by call‐taxi services in many developing countries such as India. A customer requests a taxi via phone, and it arrives at the right time and at the right location for the pick‐up. This mode of intra‐city travel has become one of the most reliable and convenient modes of transportation for customers traveling for business and non‐business purposes. The increased number of vehicles on city roads and raising fuel costs has prompted a new type of transportation logistics problem of finding a fuel‐efficient and quickest path for a call‐taxi through a city road network, where the travel times are stochastic. The stochastic travel time of the road network is induced by obstacles such as the traffic signals and intersections. The delay and additional fuel consumption at each of these obstacles are calculated that are later imputed to the total travel time and fuel consumption of a path. A Monte‐Carlo simulation‐based approach is proposed to identify unique fuel‐efficient paths between two locations in a city road network where each obstacle has a delay distribution. A multi‐criteria score is then assigned to each unique path based on the probability that the path is fuel efficient, the average travel time of the path and the coefficient of variation of the travel times of the path. Copyright © 2016 John Wiley & Sons, Ltd.     

Simultaneous modeling of individuals’ duration and expenditure decisions in out-of-home leisure activities

In this paper, we propose an activity model under time and budget constraints to simultaneously predict the allocation of time and money to out-of-home leisure activities. The proposed framework considers the activity episode level, given that the activity is scheduled. Thus, the model considers the decision of the quantities for duration and expenditure spent during the activity. We use a flexible utility function and show how the simultaneous equations can be estimated by using structural equations model (SEM) estimation techniques to handle the endogeneity problem of time and expenditure. The estimation results are based on a large national leisure diary data set collected in 2008 in the Netherlands, which provides detailed information about time and money spent as well as timing and location attributes of the activities. The analysis reveals that socio-demographics, travel party, timing and location variables influence the duration and expenditure of activity episodes. It shows that various socio-demographic groups display different preferences in terms of the time and money spent on activities. The results also indicate substitution relationships between spending more time and money for various activity categories. Thus it is concluded that the analysis provides useful results for a better understanding of combined time and money allocation decisions for leisure activities.     

Tour-based mode choice of joint household travel patterns on weekend and weekday

Joint household travel, with or without joint participation in an activity, constitutes a fundamental aspect in modelling activity-based travel behaviour. This paper examines joint household travel arrangements and mode choices using a utility maximising approach. An individual tour-based mode choice model is formulated contingent on the choice of joint tour patterns where joint household activities and shared ride arrangements are recognised as part of the joint household decision-making that influences the travel modes of each household member. Two models, one for weekend and one for weekday, are estimated using empirical data from the Sydney Household Travel Survey. The results show that weekend travel is characterised by a high joint household activity participation rate while weekday travel is distinguished by more intra-household shared ride arrangements. The arrangements of joint household travel are highly associated with travel purpose, social and mobility constraints and household resources. On weekends, public transport is mainly used by captive users (i.e., no-car households and students) and its share is about half of that on weekdays. Also, the value of travel time savings (VOTs) are found to be higher on weekends than on weekdays, running entirely counter to the common belief that weekend VOTs are lower than weekday VOTs. This paper highlights the importance of studying joint household travel and using different transport management measures for alleviating traffic congestion on weekdays and weekends.     

Measuring the impact of efficient household travel decisions on potential travel time savings and accessibility gains

Using the conceptual framework of time–space geography, this paper incorporates both spatio-temporal constraints and household interaction effects into a meaningful measure of the potential of a household to interact with the built environment. Within this context, personal accessibility is described as a measure of the potential ability of individuals within a household not only to reach activity opportunities, but to do so with sufficient time available for participation in those activities, subject to the spatio-temporal constraints imposed by their daily obligations and transportation supply environment. The incorporation of activity-based concepts in the measurement of accessibility as a product of travel time savings not only explicitly acknowledges a temporal dimension in assessing the potential for spatial interaction but also expands the applicability of accessibility consideration to such real-world policy options as the promotion of ride-sharing and trip chaining behaviors. An empirical application of the model system provides an indication of the potential of activity-based modeling approaches to assess the bounds on achievable improvements in accessibility and travel time based on daily household activity patterns. It also provides an assessment of roles for trip chaining and ride-sharing as potentially effective methods to facilitate transportation policy objectives.     

I’ll have to drive there: How daily time constraints impact women’s car use differently than men’s

Transportation - Women, compared to men, spend more time on home-serving tasks. This might leave women with less time for other activities including daily travel, which can further limit their...     

Short‐term travel time forecasts for transport information system in hong kong

In this paper, a case study is carried out in Hong Kong for demonstration of the Transport Information System (TIS) prototype. A traffic flow simulator (TFS) is presented to forecast the short‐term travel times that can be served as a predicted travel time database for the TIS in Hong Kong. In the TFS, a stochastic deviation coefficient is incorporated to simulate the minute‐by‐minute fluctuation of traffic flows within the peak hour period. The purposes of the case study are: 1) to show the applicability of the TFS for larger‐scale road network; and 2) to illustrate the short‐term forecasting of path travel times in practice. The results of the case study show that the TFS can be applied to real network effectively. The predicted travel times are compared with the observed travel times on the selected paths for an OD pair. The results show that the observed path travel times fall in the 90% confidence interval of the predicted path travel times.     

A multi‐class mean‐excess traffic equilibrium model with elastic demand

Recent empirical studies have revealed that travel time variability plays an important role in travelers' route choice decisions. To simultaneously account for both reliability and unreliability aspects of travel time variability, the concept of mean‐excess travel time (METT) was recently proposed as a new risk‐averse route choice criterion. In this paper, we extend the mean‐excess traffic equilibrium model to include heterogeneous risk‐aversion attitudes and elastic demand. Specifically, this model explicitly considers (1) multiple user classes with different risk‐aversions toward travel time variability when making route choice decisions under uncertainty and (2) the elasticity of travel demand as a function of METT when making travel choice decisions under uncertainty. This model is thus capable of modeling travelers' heterogeneous risk‐averse behaviors with both travel choice and route choice considerations. The proposed model is formulated as a variational inequality problem and solved via a route‐based algorithm using the modified alternating direction method. Numerical analyses are also provided to illustrate the features of the proposed model and the applicability of the solution algorithm. Copyright © 2012 John Wiley & Sons, Ltd.     

Impact of interviewing by proxy in travel survey conducted by telephone

Telephone‐interview surveys are a very efficient way of conducting large‐scale travel surveys. Recent advancements in computer technology have made it possible to improve upon the quality of data collected by telephone surveys through computerization of the entire sample‐control process, and through the direct recording of the collected data into a computer. Notwithstanding these technological advancements, potential sources of bias still exist, including the reliance on an adult member of the household to report the travel information of other household members. Travel data collected in a recent telephone interview survey in the Toronto region is used to examine this issue. The statistical tool used in the research was the Analysis of Variance (ANOVA) technique as implemented within the general linear model framework in SAS. The study‐results indicate that reliance on informants to provide travel information for non‐informant members of their respective households led to the underreporting of some categories of trips. These underreported trip categories were primarily segments of home‐based discretionary trips, and non home‐based trips. Since these latter two categories of trips are made primarily outside the morning peak period, estimated factors to adjust for their underreporting were time‐period sensitive. Further, the number of vehicles available to the household, gender, and driver license status respectively were also found to be strongly associated with the underreporting of trips and thus were important considerations in the determination of adjustment factors. Work and school trips were found not to be underreported, a not surprising result giving the almost daily repetitiveness of trips made for these purposes and hence the ability of the informant to provide relatively more precise information on them.     

Activity settings and travel behaviour: A social contact perspective

Using time-use data from Canada, Norway, and Sweden, this study briefly outlines the essence of the activity setting approach and illustrates one aspect of its usefulness by exploring the impact of social contact on travel behaviour. The activity system approach views behaviour in context. Activity settings are generic components of the activity system and studying them using time-use diaries can provide major insights into travel behaviour. Focusing on social contact, this paper characterizes the social environment in terms of social circle (interaction partners) and social space (location). The analysis shows that there are clear differences in the levels of social interaction across various groups, including those who work at home. The 1992 Canadian data showed people working at the workplace spend relatively more time with others, about 50% of total time awake. Working at home reduced the time with others to a low of 15.7%. when people worked at home the family benefited, almost doubling the time spent with them compared to those working at the workplace. Persons working at home only spend the most time alone. There is a tendency for persons with low social interaction to travel more. It is argued that individual need, or want, social contact and if they cannot find it at the workplace they will seek it elsewhere thus generating travel. Whether this is the result of need or opportunity is of minor relevance, what it does suggest is that working in isolation at home will not necessarily diminish travel but rather may simply change its purpose. This revised version was published online in June 2006 with corrections to the Cover Date.