Beyond the journey to work

This paper analyses the Nationwide Personal Transportation Study (NPTS) surveys of 1977 and 1983–1984 that reveal a remarkable increase in nonwork travel. This growth occurred among all city size classes but was stronger for suburban residents. Also interesting is that the rate of increase in nonwork trips was higher in the peaks (especially in the morning peak) than in the off-peak period. Some, but not all, of these trips may be price-elastic and might be diverted by congestion pricing strategies. The nonwork trip growth is concentrated in the “family and personal” and the “social and recreational” categories. Although higher-income households make more trips than low-income households, the increase in nonwork travel is common to all income groups. The growth in nonwork travel does not appear to be closely associated with the growth in female employment or trips related to the children of working women. The most convincing explanation of the growth in nonwork travel is that the trip cost savings (less time and distance) experienced because of more efficient spatial settlement patterns have provided an incentive to undertake more trips. Another implication is that urban economic models and urban transport policies have overemphasized the journey to work, especially to the central business district (CBD).     

Direct analysis of the perceived importance of attributes of reliability of travel modes in urban travel

Reliability of travel modes was found to be the most important characteristic of transportation systems in several attitudinal investigations of individual travel behavior. This paper represents the first part of a research effort aimed at gaining a better understanding of the characteristics of reliability of transportation modes in urban travel. In this research, reliability characteristics are identified; their importance relative to each other is assessed, and an insight into possible structure of an objective reliability index is discussed. The research is based on perceived values of reliability, which were identified through a large attitudinal survey conducted in the Chicago metropolitan area.     

The built environment and travel behavior in urban China: A literature review

Interests in studying of the built environment impacts on travel behavior have proliferated from North America to other parts of the world including China. Until very recently, there has been very little research into travel behavior in China. However, during the last decade, there has been a fast growing interest in studying the built environment and travel behavior in Chinese cities, perhaps motivated by China’s unprecedented urbanization and rapid urban transport development. Case studies from China provide new insights into the impacts of built environment on travel behavior that can help to enrich existing scholarship. However, currently there is a generally poor understanding of the role played by Chinese research and how it has enriched the international literature. This paper aims to fill this gap by reviewing studies in and outside China by both Chinese and non-Chinese scholars. The focus is on the contribution of these studies to the international literature. We identify four areas of contribution: how the built environment has been developed and its implications for travel behavior; the importance of housing sources in defining residential built environment and explaining travel behavior; the unique Danwei (or work unit) perspective on jobs-housing relationships and commuting behavior; and the importance of neighborhood types in explaining travel behavior in Chinese cities. The findings from this review should be relevant for researchers interested in developing future studies that will further advance geographic knowledge of the built environment and travel behavior, specifically in China and with broader global contexts.     

Pooling for the journey to work: The outlook in Great Britain

Pooling, or ride-sharing, is a term coined in the United States (U.S.) to describe various forms of collective travel organised for, and often by, specific groups of commuters with similar travel requirements. Its different forms include bus pooling (financially self-supporting works bus or commuter coach services), minibus pooling (van pooling in U.S. terminology) and car pooling. It has been claimed that these forms of collective travel offer a more personalised service than conventional stage carriage buses, and therefore have a greater chance of attracting solo car drivers and increasing vehicle occupancies. This, in turn, can lead to lower fuel consumption and reduced traffic congestion at peak times. Following the advent of oil shortages in the winter of 1973/74, considerable efforts were made in the U.S. to promote pooling initiatives. This gave rise to the publication of a substantial volume of literature that sometimes indicated significant resource-saving achievements. This paper considers the potential for bus, minibus and car pooling in Great Britain, drawing both on relevant theoretical and economic studies, and on practical operational experience. It concludes that under reasonable assumptions about the transport situation in the next decade or so, pooling could become increasingly useful for solving the travel problems of individual local groups, but that it is unlikely to become a major mode in terms of the numbers of trips carried. The effects of recent legislative changes are discussed, and the justification for further change assessed. Relevant comparisons are made with the U.S.Crown Copyright 1983. Extracts from the text may be reproduced, except for commercial purposes, provided the source is acknowledged.     

An examination of the determinants of day-to-day variability in individuals' urban travel behavior

Day-to-day variability in individuals' travel behavior (intrapersonal variability) has been recognized in conceptual discussions, yet the analysis and modeling of urban travel are typically based on a single day record of each individual's travel. This paper develops and examines hypotheses regarding the determinants of intrapersonal variability in urban travel behavior.Two general hypotheses are formulated to describe the effects of motivations for travel and related behavior and of travel and related constraints on intrapersonal variability in weekday urban travel behavior. Specific hypotheses concerning the effect of various sociodemographic characteristics on intrapersonal variability are derived from these general hypotheses. These specific hypotheses are tested empirically in the context of daily trip frequency using a five-day record of travel in Reading, England.The empirical result support the two general hypotheses. First, individuals who have fewer economic and role-related constraints have higher levels of intrapersonal variability in their daily trip frequency. Second, individuals who fulfil personal and household needs that do not require daily participation in out-of-home activities have higher levels of intrapersonal variability in their daily trip frequency.     

An examination of the determinants of day-to-day variability in individuals' urban travel behavior

Day-to-day variability in individuals' travel behavior (intrapersonal variability) has been recognized in conceptual discussions, yet the analysis and modeling of urban travel are typically based on a single day record of each individual's travel. This paper develops and examines hypotheses regarding the determinants of intrapersonal variability in urban travel behavior.Two general hypotheses are formulated to describe the effects of motivations for travel and related behavior and of travel and related constraints on intrapersonal variability in weekday urban travel behavior. Specific hypotheses concerning the effect of various sociodernographic characteristics on intrapersonal variability are derived from these general hypotheses. These specific hypotheses are tested empirically in the context of daily trip frequency using a five-day record of travel in Reading, England.The empirical results support the two general hypotheses. First, individuals who have fewer economic and role-related constraints have higher levels of intrapersonal variability in their daily trip frequency. Second, individuals who fulfil personal and household needs that do not require daily participation in out-of-home activities have higher levels of intrapersonal variability in their daily trip frequency.     

Methodologies for exploring the link between urban form and travel behavior

Communities are increasingly looking to urban design and the concept of the New Urbanism as an effective strategy for reducing automobile dependence in suburban areas. While the available empirical evidence suggests that automobile travel is lower in traditional-style neighborhoods, it provides limited insights as to how and why, largely because the research methodologies used have been insufficent for the task. Most of the studies addressing this question fall into three categories: simulation studies, aggregate analyses, and disaggregate analyses. Two other approaches offer greater promise for understanding the relationship between urban form and travel behavior: choice models and activity-based analyses. This paper reviews alternative approaches for exploring the link between urban form and travel behavior, outlines issues and complexities that this research must address, and, finally, suggests that the focus of this research should shift from the search for strategies to change behavior to a search for strategies to provide choices.     

Intrapersonal variability in daily urban travel behavior: Some additional evidence

Researchers have used multiday travel data sets recently to examine day-to-day variability in travel behavior. This work has shown that there is considerable day-to-day variation in individuals' urban travel behavior in terms of such indicators of behavior as trip frequency, trip chaining, departure time from home, and route choice. These previous studies have also shown that there are a number of important implications of the observed day-to-day variability in travel behavior. For example, it has been shown that it may be possible to improve model parameter estimation precision, without increasing the cost of data collection, by drawing a multiday sample (rather than a single day sample) of traveler behavior, if there is considerable day-to-day variability in the phenomenon being modeled. This paper examines day-to-day variability in urban travel using a three-day travel data set collected recently in Seattle, WA. This research replicates and extends previous work dealing with day-to-day variability in trip-making behavior that was conducted with data collected in Reading, England, in the early 1970s. The present research extends the earlier work by examining day-to-day variations in trip chaining and daily travel time in addition to the variation in trip generation rates. Further, the present paper examines day-to-day variations in travel across the members of two-person households. This paper finds considerable day-to-day variability in the trip frequency, trip chaining and daily travel time of the sample persons and concludes that, in terms of trip frequency, the level of day-to-day variability is very comparable to that observed previously with a data set collected almost 20 years earlier in Reading, England. The paper also finds that day-to-day variability in daily travel time is similar in magnitude to that in daily trip rates. The analysis shows that the level of day-to-day variability is about the same for home-based and non-homebased trips, thus indicating that day-to-day variability in total trip-making is attributable to variation in both home-based and non-home-based trips. Day-to-day variability in the travel behaviors of members of two-person households was also found to be substantial.     

Vehicle sharing for the journey to work by office employees

This paper outlines some spatial variations in the incidence of vehicle sharing for the journey to work amongst office workers at a number of locations in Britain. The contribution of occupation status and related factors to the variability in vehicle sharing is considered with reference to four case study offices and in relation to the use of private hire buses at one establishment. It is concluded that the original, local-specific, empirical evidence presented in the paper confirms the apparent lack of a universal pattern in vehicle sharing.     

Estimating the demand for urban bus travel

The disadvantages of conventional transportation study models, in particular their large data requirements and their weaknesses in dealing with changes in trip generation rates have led to a need for a simple model that can quickly and at low cost examine alternative public transport strategies.This paper investigates simple economic models of bus demand, examines alternative variables that can be used and discusses some alternative model forms. It demonstrates the results of a model using data from twelve urban bus operators in Britain and compares the results with those from other types of study. The model utilises fare and service quality elasticities to explain the decline in passengers on urban bus services, and derives an average elasticity with respect to fare changes of –0.31 and with respect to service quality changes of +0.62. It is estimated that fare rises accounted for 13% of the 43% decline in passengers over the last fifteen years, vehicle mileage reductions for 14.3% and that only 15.7% was due to such factors as rising car ownership which are often given as the cause of declining bus patronage.The results, by showing that passengers are far more sensitive to changes in service than they are to fare rises, are a useful guide to the broader public transport policy issues, and the paper concludes that the model does provide a useful method of forecasting public transport demand at a strategic level. Further work is needed, however, to establish more accurate forecasts for different types of passenger and studies are now being undertaken to establish these and to construct an operational forecasting model that can be applied with only limited data requirements     

Bus journey times in medium size urban areas

The predictive accuracy of the models based on the fundamental relation between journey time and passenger demand can be improved through data disaggregation or route segmentation. Primary reason for this is the improvement in the estimates of stopping delays and delays due to passenger boarding and/or alighting (dwell time). Both Poisson and Negative Binomial model estimates of stoppings for passenger boarding and alighting are shown to improve with disaggregation. These improvements, however, contribute little to the overall predictability of the fundamental models which are useful for gaining insight into the significance and variability of the stopping delays and dwell time, or testing sensitivity to changes in the long term. Site or route specific models of journey times which have better predictive capability exist, and may be used for short-run planning. However, the interchangeability and performance over time of the latter, have to be evaluated before making definitive conclusions.     

Intra-destination travel behavior of alpine tourists: a literature review on choice determinants and the survey work

Transportation - In the face of a continuous increase in the number of tourists in the Alps, the associated traffic volumes, and the resulting negative externalities, there is an urgent need to...     

Energy for travel: The influence of urban development patterns

Rising energy prices and supply shortfalls have underscored the need to improve the energy efficiency of urban travel. Long run solutions may involve rearranging development patterns in urban areas, or at least locating new growth in ways which reduce the need to travel. To test the degree to which altering development patterns may effect transport energy savings, relationships between gasoline consumption and urban development characteristics were investigated in 49 U.S. metropolitan areas. The results suggest that cities of medium size with clusters of high residential densities are associated with lower levels of per capita gasoline consumption. However, it is unlikely that changes in current development patterns during the next two decades would be substantial enough to cause a significant reduction in U.S. energy consumption.     

Classification issues in the analysis of complex travel behavior

Researchers have devoted considerable effort to identifying homogeneous travel-behavior groups, each of which also has distinctive sociodemographic characteristics. Interest in these efforts has been fueled by both theoretical and applied concerns. From a theoretical perspective, if such behaviorally and sociodemographically homogeneous groups cari be identified, we would have an improved understanding of the determinants of travel. From an applied perspective, because spatial choice models assume behavioral homogeneity within each sociodemographically defined subgroup, one would like to be able to identify groups that are homogeneous with respect to both behavior and sociodemographics. Most previous efforts to define such groups have classified individuals on the basis of one-day travel records. In this paper we review these efforts, note the problems inherent in using one-day travel records for identifying homogeneous travel-behavior groups, and use standard grouping procedures to classify individuals on the basis of behavior observed over a longer time period (five weeks). Using multi-day travel data means that the travel measures employed in classifying individuals are different from and more complex than those used with one-day data. We identify five travel-behavior groups, each of which has distinctive socio-demographic characteristics. Considerable intra-group variability remains, however, even though the groups are classified on the basis of longer-term behavior. The paper concludes with an examination of the implications of day-to-day variability in individual travel for classification procedures.     

Dynamic forecasting of urban shopping travel demand

A time-dependent model for commercial activity location and travel demand is developed based on the assumptions that instantaneous interzonal shopping travel demand can be described by a gravity formulation, whereas the incremental individual zonal retail space allocations are such that they maximize the aggregate, net resulting profit from retail sales. Over time, link travel costs are updated as a function of the current link volumes, whereas commercial space development costs are updated as a function of current zonal activity levels. Constraints on commercial space allocation are at the individual zonal level, as well as at the aggregate level of the overall area. The objective function for the corresponding mathematical program is then linearized, and the model programmed for implementation using a linear programming routine. The results of several simulations illustrate the dynamic impacts various urban development policies have on commercial activity location. In particular, periodic oscillations in zonal activity levels, as well as sudden changes in the spatial pattern of interzonal shopping travel, may appear for certain model parameter values. Several directions for future refinement of the model, including inclusion of economic variables and interaction with other urban activities, are discussed in conclusion.     

Estimation of the determinants of bicycle mode share for the journey to work using census data

A model is presented that relates the proportion of bicycle journeys to work for English and Welsh electoral wards to relevant socio-economic, transport and physical variables. A number of previous studies have exploited existing disaggregate data sets. This study uses UK 2001 census data, is based on a logistic regression model and provides complementary evidence based on aggregate data for the determinants of cycle choice. It suggests a saturation level for bicycle use of 43%. Smaller proportions cycle in wards with more females and higher car ownership. The physical condition of the highway, rainfall and temperature each have an effect on the proportion that cycles to work, but the most significant physical variable is hilliness. The proportion of bicycle route that is off-road is shown to be significant, although it displays a low elasticity (+0.049) and this contrasts with more significant changes usually forecast by models constructed from stated preference based data. Forecasting shows the trend in car ownership has a significant effect on cycle use and offsets the positive effect of the provision of off-road routes for cycle traffic but only in districts that are moderately hilly or hilly. The provision of infrastructure alone appears insufficient to engender higher levels of cycling.

The role of congestion of transportation networks in urban location and travel choices

Congestion of urban transportation systems results from an equilibrium of location and travel choices with generalized travel costs which increase with vehicle flows as well as other factors. The use of network equilibrium concepts in analyzing urban policies and evaluating alternative plans is examined. Issues arising in the use of network equilibrium models are described, and formulations of urban network prediction and design models are explored.