The Dutch mobility panel: Experiences and evaluation

The aim of this paper is to give an overview of the history and research experiences of the Dutch National Mobility Panel. Attention is given to the sampling strategy, the policy goals, and the representativity of the panel. It also tries to evaluate the research outcomes in terms of the original objectives and in view of more general research and policy goals. In sections one and two, a historic overview is given, starting from the first ideas to implement a longitudinal research instrument in transportation planning. In section three, some attention is devoted to longitudinal versus cross-sectional analyses. In section four, the sample design is treated in some detail. Next, various forms of bias are discussed that affect the representativity of the panel. In the sixth section, an overview is given of the research conducted with the data. Some conclusions are given in the final section.     

The implications of travel profiles for transportation investment: The Bronx Center Project

Investment in transportation infrastructure is generally regarded as an effective means for inducing economic growth and employment in a region. However, the ability of such investments to achieve these objectives, to a large extent, depends on the degree to which travel results from these investments support or conflict with present travel patterns and needs in this region. Using this view as a basis, this paper analyzes travel conditions and choices in the Bronx New York, where large scale transportation and other development projects (commonly called the Bronx Center Project) are presently taking place. Using a large data base, composed of census tract information on socio-economic and travel behavior, the paper first examines the travel profile of the Bronx population, by estimating travel choice elasticities. On the basis of these elasticities it then assesses the impact of the Bronx Center Project on travel patterns and trends.     

Multilevel analysis of daily time use and time allocation to activity types accounting for complex covariance structures using correlated random effects

In this paper multilevel analysis is used to study individual choices of time allocation to maintenance, subsistence, leisure, and travel time exploiting the nested data hierarchy of households, persons, and occasions of measurement. The multilevel models in this paper examine the joint and multivariate correlation structure of four dependent variables in a cross-sectional and longitudinal way. In this way, observed and unobserved heterogeneity are estimated using random effects at the household, person, and temporal levels. In addition, random coefficients associated with explanatory variables are also estimated and correlated with these random effects. Using the wide spectrum of options offered by multilevel models to account for individual and group heterogeneity, complex interdependencies among individuals within their households, within themselves over time, and within themselves but across different indicators of behavior, are analyzed. Findings in this analysis include large variance contribution by each level considered, clear evidence of non-linear dynamic behavior in time-allocation, different trajectories of change in time allocation for each of the four dependent variables used, and lack of symmetry in change over time characterized by different trajectories in the longitudinal evolution of each dependent variable. In addition, the multivariate correlation structure among the four dependent variables is different at each of the three levels of analysis.     

A tale of two cities

Land use and transportation mutually affect each other. Unfortunately, most transportation decision making procedures assume that public agencies cannot shape future land use patterns, and that past land use practices unswervingly determine future conditions. In A Tale of Two Cities, the author surveys the correlations between land use policies and travel behavior in two Oregon cities (Portland and Hillsboro).Building on successes the City of Portland has achieved in reducing reliance on the automobile, the author outlines a recent project by 1000 Friends of Oregon, titled Making the Land Use, Transportation, Air Quality Connection (LUTRAQ). According to the author, the purpose of LUTRAQ is to replicate Portland's approach in a more suburban context. Specifically, LUTRAQ is attempting to develop a realistic land use/transportation/demand management alternative to a proposed new bypass freeway and to accurately measure that alternative for its effects on travel demand, land use, air quality, climate change, and other indices. Although LUTRAQ is a project in progress, the author provides preliminary information that suggests the alternative successfully reduces demand for single occupancy automobile travel.     

An investigation of tour generation models combining two waves of household travel surveys through pooled models

This paper presents a study that examines two waves of travel survey data through a pooled model structure. The pooled model structure provides a means to take advantage of multiple data sources which will lead to a better estimate and understanding of travel behavior. In particular, it accounts for the difference in data variance and therefore allows for the comparison of the true impacts of the model parameters on travelers’ tour-making behavior. Larger variance is found in the 1998 data than in the 2010 data. Comparison between model parameters reveals significant behavioral changes among several socio-economic and demographic groups. In terms of common variables, the magnitude of the coefficient values has generally decreased, which conforms to the overall decreasing trend in traveling. Overall, the model equality tests indicate that the models developed based on the two data sources do not have equal taste parameters, thus the transferability hypothesis is rejected. The results of this study are expected to have implications for the application of models based on cross-sectional data, especially over long time periods.     

A dynamic analysis of person and household activity and travel patterns using data from the first two waves in the Puget Sound Transportation Panel

Daily activity participation and travel patterns are examined using data from the Puget Sound Transportation Panel (PSTP), which contains two-pairs of daily travel diary information (wave 1 in 1989 and wave 2 in 1990). Summary data of the travel diaries at the person and household levels are obtained using cluster analysis. At the person level, four clusters are found reasonable for both activity and travel. The four-cluster solutions indicate substantial day-to-day variation in activity participation and similarity in travel behavior over time. Temporal changes are analyzed using contingency table methods and log-linear models. The analysis reveals that activity participation and mobility present many regularities over time. Transitions within each wave show strong dependence between two days for both activity and travel, with higher dependency for the travel patterns than for the activity patterns. These are consistent when the analysis focuses on a longer period such as a year. Temporal dependencies appear to be stronger in the household-based than the person-based analysis. A hierarchical structure is also found in the relationship between activity and travel clusters. The link between activity and travel is much stronger within a day, weaker from one day to another, and the least strong from one year to the next. Important irregularities, however, are found and may be due to scheduling time-frames adopted by the respondents that are only partially captured in the data used.     

Analysis of consumer response to fuel price fluctuations applying sample selection model to GPS panel data: Dynamics in individuals’ car use

The effects of fuel price increases on people’s car use have been widely discussed during the last few decades in travel behavior research. It is well recognized that fuel price has significant effects on driving distance and driving efficiency. However, most of this research assumed that these effects are invariant across individuals and weather conditions. Moreover, intrinsic variability in people’s preferences has not been given much attention due to the difficulty of collecting the necessary data. In this paper, we collected detailed travel behavior data of 276 respondents in the Netherlands, spanning a time period between one week and three months using GPS logs. These GPS data were fused with weather data, allowing us to estimate both exogenous (such as weather and fuel price) and endogenous effects (inertia and activity plans) on individual’s car use behavior. To further understand the effects of fuel price on the environment, we estimated the effects of fuel price fluctuation on CO₂ emissions by car. The results show a significant degree of inertia in car use behavior in response to increased fuel prices. Weather and fuel price showed significant effects on individual’s car using behavior. Moreover, fuel price shows two-week lagged effects on individual’s travel duration by car.     

Regularity and irreversibility of weekly travel behavior

Dynamic characteristics of travel behavior are analyzed in this paper using weekly travel diaries from two waves of panel surveys conducted six months apart. An analysis of activity engagement indicates the presence of significant regularity in weekly activity participation between the two waves. The analysis also shows a general lack of association between regularity in activity participation and change in person and household attributes, suggesting the presence of behavioral inertia or response lags. It is further shown that observed trip rates do not exhibit patterns that would be observed if travel behavior had no response lag and no history dependence. The results point to the needs for models that are capable of representing these aspects of travel behavior.     

Strategies to achieve deep reductions in metropolitan transportation GHG emissions: the case of Philadelphia

ABSTRACT

This paper investigates strategies that could achieve an 80% reduction in transportation emissions from current levels by 2050 in the City of Philadelphia. The baseline daily lifecycle emissions generated by road transportation in the Greater Philadelphia Region in 2012 were quantified using trip information from the 2012 Household Travel Survey (HTS). Emissions were projected to the year 2050 accounting for population growth and trends in vehicle technology for both the Greater Philadelphia Region and the City of Philadelphia. The impacts of vehicle technology and shifts in travel modes on greenhouse gas (GHG) emissions in 2050 were quantified using a scenario approach. The analysis of 12 different scenarios suggests that 80% reduction in emissions is technically feasible through a combination of active transportation, cleaner fuels for public transit vehicles, and a significant market penetration of battery-electric vehicles. The additional electricity demand associated with greater use of electric vehicles could amount to 10.8 TWh/year. The use of plug-in hybrid electric vehicles (PHEV) shows promising results due to high reductions in GHG emissions at a potentially manageable cost.     

Asking the right questions about telecommuting: Avoiding pitfalls in surveying homebased work

In designing travel behavior surveys, the problem is to define “work,” “home,” and similar words that are commonly used in our language but which have acquired a plethora of associated meanings. The difficulty has not been resolved by the many new terms coined to describe non-traditional ways to work. Such words as “telecommuting,” “teleworking,” “at-home work,” “hoteling,” “homebased business,” “road warriors” and “mobile workers,” lack any agreed-upon definitions yet they are used in common parlance as if they did. These new workstyles are of interest to travel planners because they may involve trip reduction. To forecast just how much trip reduction will occur, behavior needs to be measured by objective criteria. To avoid definitional traps, we recommend phrasing questions in terms of measurable variables such as the place of work and the time in days and hours spent at each location. That approach leaves researchers the option of applying their own definitions that fit the context of their analyses. Thus, rather than ask “How many days a week do you telecommute?” the more precise question can be asked: “How many days last week did you work at home instead of going to your usual work location?” This approach has the advantage that information gathered over years can be used unambiguously in various contexts. Definitions can be applied at the point of analysis. This paper illustrates errors and confusion that can arise from casually worded surveys using examples from private and public surveys. The author proposes a set of core questions with four levels of priority for consideration in designing future surveys of travel behavior.     

The design of environmentally aware travel diaries

Any policy addressing the concerns and trends associated with the impact of travel on the environment should be based on a solid understanding of the activities giving rise to them. While the measurement of the total environment loads by air or noise measurement stations is essential, it needs to be matched by the observation of the human behaviours creating them. This is especially true in the transport sector, which has been rightly or wrongly identified as having the potential to make a substantial contribution to the reduction of air and noise pollution. While the contribution of freight transport is of growing concern and importance, this paper focuses on the measurement of passenger transport throughout.

In the past transport planners have largely relied on the travel diary as their prime instrument to measure traveller behaviour. The travel diary is a survey instrument designed to record all movements during the course of one or more days including their relevant details. It is complemented by spearate household and personal forms for recording general information. In the following paper the term travel diary implies all three elements (the diary, the person form and the household form).

The remainder of the paper discusses to what extent and how the travel diary can be used to capture data for the assessment of policies directed at reducing the impact of transport on the social and natural environment. The requirements of a travel diary and the potential uses of new technologies in realising such a travel diary are then presented. A brief outlook on the possibilities of reasling such a diary concludes the paper.     

The positive utility of the commute: modeling ideal commute time and relative desired commute amount

Two measures of commute time preferences – Ideal Commute Time and Relative Desired Commute amount (a variable indicating the desire to commute "much less" to "much more" than currently) – are modeled, using tobit and ordered probit, respectively. Ideal Commute Time was found to be positively related to Actual Commute Time and to a liking and utility for commuting, and negatively related to commute frequency and to a family/community-oriented lifestyle. Relative Desired Commute, on the other hand, was negatively related to amounts of actual commute and work-related travel, but positively related to travel liking and a measure of commute benefit. Overall, commute time is not unequivocally a source of disutility to be minimized, but rather offers some benefits (such as a transition between home and work). Most people have a non-zero optimum commute time, which can be violated in either direction – i.e. it is possible (although comparatively rare, occurring for only 7% of the sample) to commute too little. On the other hand, a large proportion of people (52% of the sample) are commuting longer than they would like, and hence would presumably be receptive to reducing (although usually not eliminating) that commute.     

How much disruption to activities could fuel shortages cause? – The British fuel crisis of September 2000

In September of 2000 the UK experienced a blockade of oil refineries in response to rising fuel prices. These protests resulted in severe fuel supply disruptions that intensified over the course of about one week. During the peak of the crisis, travel activity by car was curtailed. This paper analyzes survey data collected about two months after the crisis utilizing the recent memory of respondents as to how they would expect this sort of disruption to affect their participation in daily activities. Specifically, we focused on a variety of non-discretionary and discretionary activities and examined what factors are associated with respondents expecting disruption to those activities. Statistical models were developed to analyze how demographic factors, commute mode selection, vehicle characteristics, and various other factors can explain how individuals expect disruption to their activities. Results suggest that the majority of individuals do not expect major disruptions, although for more car-dependent individuals, disruption was expected to be substantial, especially for work-related trips. These results have implications for the potential success and benefits of an integrated transport policy.     

The impact of urban form on automobile travel: disentangling causation from correlation

A longstanding question within the field of transportation demand management is the strength of the relationship between urban form and mobility behavior. Although several studies have identified a strong correlation between these variables, there is as yet scant evidence to support policy interventions that target land use as a means of influencing travel. To the contrary, some of the more recent research has cast skepticism on the proposition that the relationship is causative, recognizing the possibility that households endogenously self-select themselves into communities that support their preferences for particular transportation modes. Focusing on individual automobile travel, the present study seeks to contribute to this line of inquiry by estimating econometric models on a panel of travel-diary data collected in Germany between 1996 and 2003. Specifically, we employ the two-part model (2PM)—a procedure involving probit and OLS estimators—to assess the determinants of the discrete decision to use the car and the continuous decision of distance traveled. Beyond modeling variables that capture the urban form features that are commonly suggested to influence mobility behavior, including mixed use and public transit, this study employs instrumental variables to control for potential endogeneity emerging from the simultaneity of residential and mode choices. Unlike much of the work to date, our results suggest that urban form has a causative impact on car use, a finding that is robust to alternative econometric specifications.

Reintroducing attitude theory in travel behavior research: The validity of an interactive interview procedure to predict car use

A methodological challenge is to develop methods which satisfy the need in transport planning of accurately forecasting travel behavior. Drawing on a review of the current state of attitude theory, it is argued that successfully forecasting travel behavior relies on a distinction between planned, habitual, and impulsive travel. Empirical illustrations are provided in the form of stated-response data from two experiments investigating the validity of an interactive interview procedure to predict household car use for different types of trips, either before or after participants were required to reduce use.     

The Influences of the Built Environment and Residential Self-Selection on Pedestrian Behavior: Evidence from Austin, TX

Pedestrian travel offers a wide range of benefits to both individuals and society. Planners and public health officials alike have been promoting policies that improve the quality of the built environment for pedestrians: mixed land uses, interconnected street networks, sidewalks and other facilities. Whether such policies will prove effective remains open to debate. Two issues in particular need further attention. First, the impact of the built environment on pedestrian behavior may depend on the purpose of the trip, whether for utilitarian or recreational purposes. Second, the connection between the built environment and pedestrian behavior may be more a matter of residential location choice than of travel choice. This study aims to provide new evidence on both questions. Using 1368 respondents to a 1995 survey conducted in six neighborhoods in Austin, TX, two separate negative binomial models were estimated for the frequencies of strolling trips and pedestrian shopping trips within neighborhoods. We found that although residential self-selection impacts both types of trips, it is the most important factor explaining walking to a destination (i.e. for shopping). After accounting for self-selection, neighborhood characteristics (especially perceptions of these characteristics) impact strolling frequency, while characteristics of local commercial areas are important in facilitating shopping trips.