Kenneth Dueker

The new 'burbs: the exurbs and their implications for planning policy

Abstract The exurbs are currently home to sixty million Americans, and may be home to more people than urban, suburban, or rural areas are by early in the next century. Planners may be unprepared to address the special needs and challenges presented by the exurbs, because the tools that planners use to manage cities, suburbs, and rural areas may be inappropriate. Before planners can respond adequately to the challenge of exurban development, they must first understand who lives there and why. Using a case study of the Portland, Oregon area, we find that although ex-urbanites have many socio-economic characteristics in common with suburbanites, they prefer a different lifestyle. This lifestyle includes rural amenities, large house lots, and longer drives to work. We also find substantial differences between exurbanites living in small towns and those living in rural areas.

Effects of household structure and selected travel characteristics on trip chaining

This paper analyzes trip chaining, focusing on how households organize non-work travel. A trip chaining typology is developed using household survey data from Portland, Oregon. Households are organized according to demographic structure, allowing analysis of trip chaining differences among household types. A logit model of the propensity to link non-work trips to the work commute is estimated. A more general model of household allocation of non-work travel among three alternative chain types — work commutes, multi-stop non-work journeys, and unlinked trips — is also developed and estimated. Empirical results indicate that the likelihood of linking work and non-work travel, and the more general organization of non-work travel, varies with respect to household structure and other factors which previous studies have found to be important. The effects of two congestion indicators on trip chaining were mixed: workers who commuted in peak periods were found to have lower propensity to form work/non-work chains, while a more general congestion indicator had no effect on the allocation of non-work trips among alternative chains.

DETERMINANTS OF BUS DWELL TIME

Bus dwell time data collection typically involves labor intensive ride checks. This paper reports an analysis of bus dwell times that use archived automatic vehicle location (AVL)/automatic passenger counter (APC) data reported at the level of individual bus stops. The archived data provide a large number of observations that serve to better understand the determinants of dwells, including analysis of rare events, such as lift operations. The analysis of bus dwell times at bus stops is applicable to TriMet, the transit provider for the Portland, Oregon metropolitan area, and transit agencies in general. The determinants of dwell time include passenger activity, lift operations, and other effects, such as low floor bus, time of day, and route type.

The Exurbanization of America and Its Planning Policy Implications

There is considerable evidence of continued population deconcentra tion in the continental United States. It has created, among other things, a new form of development, which we call exurbanization. In this paper we suggest the magnitude of exur banization in both spatial and popu lation terms, identify many of the reasons for the locational behavior of exurban households, and present some notable planning policy impli cations. We ask our planning col leagues to comprehensively investi gate this new form of urban development. The risks to ignoring the nature, causes, consequences, and policy implications of exurbani zation are great.

EVALUATION OF TRANSIT OPERATIONS: DATA APPLICATIONS OF TRI-MET'S AUTOMATED BUS DISPATCHING SYSTEM

In this paper, archived Automatic Vehicle Location and Automatic Passenger Counter data are used to evaluate actual bus running time variation in relation to scheduled service for Tri-Met, the transit provider for the Portland, Oregon metropolitan area. Given observed variation in running times, scheduled recovery times are found to be generally (though not universally) excessive. This results in an under-investment of resources in revenue service relative to non-revenue service. Analysis of trip level data reveals that bus operators are an important source of running time variation after controlling for such factors as route design, time of day and direction of service, and passenger activity.

AUTOMATED BUS DISPATCHING, OPERATIONS CONTROL, AND SERVICE RELIABILITY: BASELINE ANALYSIS

Tri-Met, the transit provider in Portland, Oregon, is implementing a new computer-aided bus dispatching system that uses a satellite-based global positioning system to track vehicle location. It is expected that the new system will produce improvements in service reliability. Presented is a baseline analysis of service reliability on selected routes, focusing on running times, headways, and on-time performance. Reliability is found to vary according to route characteristics, direction, and time of day.

Geographic Information Systems and Computer-Aided Mapping

Abstract The paper distinguishes computer-aided mapping from geographic information systems. Mapping systems are display oriented, and they produce plots of selected layers of point and line data. Geographic information systems, on the other hand, are analysis oriented; they analyze relationships among point, line, and area data that describe such geographic features as streets, rivers, buildings, and counties. A link between mapping and information systems is emerging in the form of a data model that relates locational data on features and descriptive data for those features. Planners are cautioned about acquiring computer-aided mapping systems that lack the geographic information systems data models that most spatial analysis requires.

Light-Rail-Transit Impacts in Portland: The First Ten Years

The ways in which the first decade of light-rail transit (LRT) in the Portland region have affected auto ownership, mode share, density, and property values are examined. Empirical analysis provides evidence that light rail has had some positive effects on single-family property values, transit use, and slower growth of two-plus car households in the outer part of the LRT corridor as compared with an outer part of a parallel bus corridor. These effects might be the result of households self-selecting to locate near LRT rather than the result of current households changing their mode. This assessment of the evidence indicates the extent to which consumer preferences have responded to LRT investments. This kind of assessment is needed to provide the basis for estimating travel-mode shares and market shares for dispersed and concentrated development forms. Examination of data suggests that it might be advisable for planners to entertain more modest expectations of LRT.

A geographic information system framework for transportation data sharing

Abstract This paper develops a framework and principles for sharing transportation data. The framework is intended to clarify roles among participants, data producers, data integrators, and data users. The principles are intended to provide guidance for the participants. Both the framework and the principles are based on an enterprise geographic information systems-transportation (GIS-T) data model that defines relations among transportation data elements. The data model guards against ambiguities and provides a basis for the development of the framework and principles for sharing transportation data. There are two central principles. First is the uncoupling of graphics, topology, position, and characteristics. Second is the establishment of a schema for transportation features and their identifiers. An underlying principle is the need for a common data model that holds transportation features, not their graphical representations, as the objects of interest. Attributes of transportation features are represented as linear and point events. These are located along the feature using linear referencing. Sharing of transportation data involves exchange of relevant transportation features and events, not links and nodes of application-specific databases. Strategies for sharing transportation features follow from this approach. The key strategy is to identify features in the database to facilitate a transactional update system, one that does not require rebuilding the entire database anew. This feature-oriented enterprise GIS-T database becomes the basis for building separate application-specific network databases.

MEASURING THE IMPACT OF LIGHT RAIL SYSTEMS ON SINGLE-FAMILY HOME VALUES: A HEDONIC APPROACH WITH GEOGRAPHIC INFORMATION SYSTEM APPLICATION

In theory, proximity to light rail transit (LRT) may have two different effects on residential property values. On the one hand, accessibility (proximity to LRT stations) may increase property values. On the other hand, nuisance effects (proximity to the LRT line and stations) may decrease property values. Existing empirical studies are inconclusive, and failure to separate the effects of accessibility from the nuisance effects may explain some of the ambiguity. An examination is presented of the impact of the light rail system (MAX) in Portland, Oregon, on single-family home values using distance to rail stations as a proxy for accessibility and distance to the line itself as a proxy for nuisance effects. Geographic information system techniques are employed to create spatial-related variables and merge data from various sources. The study results confirm the hypothesis that the light rail has both a positive effect (accessibility effect) and a negative effect (nuisance effect) on single-family home values. The positive effect dominates the negative effect, which implies a declining price gradient as one moves away from LRT stations for several hundred meters. Without controlling for the nuisance effect of the distance to the rail line, the estimated coefficients on distance from stations appear to be biased and would underestimate the accessibility effect. The finding of an independent nuisance effect suggests that previous hedonic models may have reached contradictory results because the nuisance effect differs with different types of rail or other local characteristics.