Traditional neighborhoods and commuting in the San Francisco Bay area

Neo-traditional designs, proponents argue, reduce dependency on the automobile and provide attractive environments for walking, bicycling, and transit riding. This paper explores the extent to which this proposition holds for seven traditional neighborhoods in the San Francisco Bay Area that evolved around early streetcar services. Matched-pair comparisons of modal shares and trip generation rates for work trips are made between these neighborhoods and newer auto-oriented suburbs, controlling for the effects of income and, to a lesser extent, existing bus service levels. Pedestrian/bicycle modal shares and trip rates tended to be considerably higher, in some cases five time as high, in transit-oriented than in the paired auto-oriented neighborhood. Transit neighborhoods also averaged around 70 more daily transit work trips per 1,000 households than auto-oriented neighborhoods, though trip rates varied considerably among neighborhood pairs. Higher residential densities were also found to have a proportionately greater impact on transit commuting in transit-oriented than in auto-oriented neighborhoods. The paper concludes that in order to yield significant transportation benefits, neo-traditional development must be coordinated with larger regional planning efforts and public policy initiatives to reduce automobile dependency.     

An Analysis of Weekend Work Activity Patterns in the San Francisco Bay Area

The purpose of this study is to examine the spatial and temporal characteristics of weekend work episodes. Specifically, we examine whether individuals work over the weekend and, if they work, whether they work at home or outside the home. We also model the time of day of weekend work. The empirical analysis in the paper is based on the 2000 San Francisco Bay Area Travel Survey. The results indicate the important effects of day of week/seasonal effects, individual demographics, work-related variables, household characteristics, and location variables on weekend work participation characteristics. The models estimated in the paper may be embedded within a larger weekend activity-travel pattern forecasting model system.     

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.     

Effect of land use on decisions of shopping tour generation: A case study of three traditional neighborhoods in WA

This study investigates the relationship between land use and shopping tour generation using an activity-based shopping model that captures the effects of land use patterns on household decisions of shopping tour frequency, tour scheduling and mode choice. The model was calibrated using travel data collected in three traditional neighborhoods located in the Puget Sound region, WA, and shopping travel patterns across seven common household structures were analyzed. The results reveal that land use patterns have virtually no impact on overall shopping tour frequency. However, land use does seem to be associated with decisions about the type of shopping tours undertaken. For example, households with poorer accessibility tend to make fewer one-stop shopping tours, and are more likely to combine shoppingtrips with other trips to form multi-stop shopping tours as a means of compensating for locational deficiencies. Finally, we also found that traditional neighborhood residents who live closer to the neighborhood commercial street, and thus, have greater accessibility, are more inclined to use non-auto modes for one-stop shopping tours.     

Impacts of automated vehicles on travel behaviour and land use: an international review of modelling studies

ABSTRACT

Automated vehicles (AVs) could completely change mobility in the coming years and decades. As AVs are still under development and gathering empirical data for further analysis is not yet possible, existing studies mainly applied models and simulations to assess their impact. This paper provides a comprehensive review of modelling studies investigating the impacts of AVs on travel behaviour and land use. It shows that AVs are mostly found to increase vehicle miles travelled and reduce public transport and slow modes share. This particularly applies to private AVs, which are also leading to a more dispersed urban growth pattern. Shared automated vehicle fleets, conversely, could have positive impacts, including reducing the overall number of vehicles and parking spaces. Moreover, if it is assumed that automation would make the public transport system more efficient, AVs could lead to a favouring of urbanisation processes. However, results are very sensitive to model assumptions which are still very uncertain (e.g. the perception of time in AVs) and more research to gain further insight should have priority in future research as well as the development of the models and their further adaptation to AVs.     

A parameterized consideration set model for airport choice: an application to the San Francisco Bay Area

Airport choice is an important air travel-related decision in multiple airport regions. This paper proposes the use of a probabilistic choice set multinomial logit (PCMNL) model for airport choice that generalizes the multinomial logit model used in all earlier airport choice studies. The paper discusses the properties of the PCMNL model, and applies it to examine airport choice of business travelers residing in the San Francisco Bay Area. Substantive policy implications of the results are discussed. Overall, the results indicate that it is important to analyze the choice (consideration) set formation of travelers. Failure to recognize consideration effects of air travelers can lead to biased model parameters, misleading evaluation of the effects of policy action, and a diminished data fit.     

Spatiotemporal influence of land use and household properties on automobile travel demand

Understanding the patterns of automobile travel demand can help formulate policies to alleviate congestion and pollution. This study focuses on the influence of land use and household properties on automobile travel demand. Car license plate recognition (CLPR) data, point-of-interest (POI) data, and housing information data were utilized to obtain automobile travel demand along with the land use and household properties. A geographically and temporally weighted regression (GTWR) model was adopted to deal with both the spatial and temporal heterogeneity of travel demand. The spatial-temporal patterns of GTWR coefficients were analyzed. Also, comparative analyses were carried out between automobile and total person travel demand, and among travel demand of taxis, heavily-used private cars, and total automobiles. The results show that: (I) The GTWR model has significantly higher accuracy compared with the Ordinary Least Square (OLS) model and the Geographically Weighted Regression (GWR) model, which means the GTWR model can measure both the spatial and temporal heterogeneity with high precision; (II) The influence of built environment and household properties on automobile travel demand varies with space and time. In particular, the temporal distribution of regression coefficients shows significant peak phenomenon; and (III) Comparative analyses indicate that residents’ preference for automobiles over other travel modes varies with their travel purpose and destination. The above findings indicate that the proposed method can not only model spatial-temporal heterogeneous travel demand, but also provide a way to analyze the patterns of automobile travel demand.     

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.     

Coordinating buses and rapid rail in the San Francisco Bay Area: The case of Bay Area Rapid Transit

This paper examines attempts by planners and policy makers to analyze and bring about the coordination of rail and bus transit in the San Francisco Bay Area. Drawing on studies and plans before and after the creation of the rapid rail system BART (Bay Area Rapid Transit), the author points to technical, analytical and political problems in attempts to link BART and buses. Some options and cautions are presented for planners considering route coordination, feeder buses, transfers and institutional arrangements to manage bus and rail services.     

Sensitivity of prices to demand shocks: A natural experiment in the San Francisco Bay Area

We analyze the impact of a freeway interchange collapse in the San Francisco Bay Area on the difference in airfare quotes for travel into the area’s main airports. The incident temporarily made Oakland airport a less attractive choice for traveling to San Francisco, so we hypothesize that fares for travel into Oakland will be relatively lower while the freeway interchange was out of service. We test our contention using a sample of fare quotes collected on-line, and find the expected effect of a magnitude of 6–7%. Our results imply the following important conclusions. First, the demand-side shock was well absorbed by the supply side. Second, adjustment of prices and return to the status quo once the shock vanished was swift.     

Integrating a traffic router and microsimulator into a land use and travel demand model

Abstract

This paper describes one of the first known attempts at integrating a dynamic and disaggregated land-use model with a traffic microsimulator and compares its predictions of land use to those from an integration of the same land-use model with a more traditional four-step travel demand model. For our study area of Chittenden County, Vermont, we used a 40-year simulation beginning in 1990. Predicted differences in residential units between models for 2030 broken down by town correlated significantly with predicted differences in accessibility. The two towns with the greatest predicted differences in land use and accessibility are also the towns that currently have the most severe traffic bottlenecks and poorest route redundancy. Our results suggest that this particular integration of a microsimulator with a disaggregated land-use model is technically feasible, but that in the context of an isolated, small metropolitan area, the differences in predicted land use are small.     

A GPS-aided survey for assessing trip reporting accuracy and travel of students without telephone land lines

A geo-positioning satellite (GPS)-based survey, using a web-based prompted recall tool, was conducted on a sample of 94 students at the University of Toronto from November 2008 to April 2009. The sample included students with and without telephone land lines, allowing for a statistical comparison of demographic and travel behaviour attributes. The same subjects simultaneously completed a traditional trip reporting survey, modelled on the household travel survey in Toronto, allowing for a comparison between the travel behaviour information obtained from the GPS and that reported by the participants in the traditional survey. Students with a land line are more likely to live in houses, with parents, and to live in suburban areas than students without a land line. They also make fewer trips in total, fewer discretionary trips, more transit and auto trips and fewer active trips than students without a land line. By comparing questionnaire-based data and GPS data, we found that most participants reported in the questionnaire either the same number of GPS-based trips or fewer. On average, the GPS survey captured 1.29 more daily trips per participant than the corresponding trips reported in the questionnaire.     

A structural equations analysis of commuters' activity and travel patterns

An exploratory analysis of commuters' activity and travel patterns was carried out using activity-based travel survey data collected in the Washington, DC metropolitan area to investigate and estimate relationships among socio-demographics, activity participation, and travel behavior. Structural equations modeling methodology was adopted to determine the structural relationships among commuters' demographics, activity patterns, trip generation, and trip chaining information. Three types of structural equations model systems were estimated: one that models relationships between travel and activity participation, another that captures trade-offs between in-home and out-of-home activity durations, and a third that models the generation of complex work trip chains. The model estimation results show that strong relationships do exist among commuters' socio-demographic characteristics, activity engagement information, and travel behavior. The finding that significant trade-offs exist between in-home and out-of-home activity participation is noteworthy in the context of in-home vs. out-of-home substitution effects. Virtually all of the results obtained in this paper corroborate earlier findings reported in the literature regarding relationships among time use, activity participation, and travel. This revised version was published online in June 2006 with corrections to the Cover Date.     

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.     

How big should transit be? Evidence on the benefits of reorganization from the San Francisco Bay Area

This paper studies whether the many public urban transit providers in the San Francisco Bay Area could realize cost economies by consolidating into larger systems. In this discussion, any benefits of rationalization are excluded, since these could be achieved without organizational changes.The results support the formation of larger multi-modal systems in the Bay Area. But care must be taken in selecting the candidates for reorganization, and a broad-brush approach could result in important lost opportunities for cost reduction. But if these economies are taken into account, and transit grows in the right directions, the benefits could be substantial.     

Optimization of tunnel tolls in land use and transport planning

The task of transport planning is to determine cost-effective methods of providing and improving mobility, which can include minimizing traffic congestion. A cost-effective solution to transport problems should consist of a land use pattern, a transport system an a set of road pricing policies that together bring demand and supply into balance in an efficient and equitable way. The conventional approach aimed to produce comprehensive, long-term plans for land use and transport in considerable detail, but tended to ignore the role of road pricing policy, thus ending up with solutions that might not be efficient or economical. This feature of sub-optimal road pricing policy is accentuated by the overall growth in car use, which has generated problems with the efficient use of road space. This paper presents a computer analysis system (or model) which will enable the analysis of coordinated tunnel toll pricing policies by optimising an “objective function” while satisfying the associated and other constraints. The possibility of integrating the optimal road pricing policies in the land use and transport planning are discussed. A case study based on Hong Kong data demonstrates the efficiency of optimizing tolls on two of the three harbour crossing tunnels in Hong Kong.     

The relationship between land use and automobile travel utility: A Multiple Indicators Multiple Causes approach

The relationship between land use and the utility of automobile travel is examined by refining the utility concept, particularly by combining the microeconomic utility theory, which is concerned with the disutility of travel, and the perspective on the positive utility. A conceptual model is accordingly developed and then adjusted considering different purposes of travel. The purpose-specific models are tested through a Multiple Indicators Multiple Causes approach in Seoul, Korea, using datasets from a sample survey and geographic information systems. The major finding is that land use affects the utility mainly by changing synergy and affective utility rather than instrumental utility, which encompasses disutility variables. Among land use variables, the utility is found to be the most sensitive to the number of transit facilities for commuting and shopping travel and land use balance for leisure travel.     

Linking land use and transportation in a rapidly urbanizing context: A study in Delhi,India

Cities in developing countries like India are facing some of the same concerns that North American cities are: congestion and urban growth. However, there is a sense of urgency in cities like Delhi, India in that this growth is far more rapid as both urbanization and motorization are ongoing processes that have not yet peaked. In this paper, we examine land use change and its relationship with transportation infrastructure and other planning related variables in a spatial context. We estimate land use change models at two different scales from separate data. Cellular automation and Markov models were used to understand change at the regional scale and discrete choice models to predict change at the local level. The results suggest that land use in the Delhi metropolitan area is rapidly intensifying while losing variety. These changes are affected by industrial, commercial and infrastructure location and planners and policy-makers need to better understand the implications of location decisions. We also examine these results in the context of a policy framework for data-based planning that links land use and transportation models for Delhi.     

A land use and transportation integration method for land use allocation and transportation strategies in China

In this paper, we will first review literature of the land use and transportation interaction and then develop a new land use allocation methodology called Three Stages-Two-Feedback Method (Integration Method) for both land use allocation and the transportation policy options with a practical implementation. Then we apply this method in an urban general planning project in China with more than 1.2 million populations. In this project, we evaluated three land use allocation strategies and three transportation policy options using two application tools (with and without feedbacks) using this method implemented in a land use planning system UPlan and a transportation planning system Emme. The results show that the use of the feedback method (Application Two) results in a vehicle distance reduction and the increase in the service coverage area of transit bus stops at the same time. Due to the use of transportation accessibility and the congestion measures with a MSA implementation, the accessibility measure shows a convergent process over iterations. This nice feature can be used for alternative comparisons. Future research subjects are also discussed.