Derivation and use of automobile availability as a variable for estimating travel demand /

Jan. 1979.

Sustainable Australia : containing travel in master planned estates

Low density suburban development and excessive use of automobiles are associated with serious urban and environmental problems. These problems include traffic congestion, longer commuting times, high automobile dependency, air and water pollution, and increased depletion of natural resources. Master planned development suggests itself as a possible palliative for the ills of low density and high travel. The following study examines the patterns and dynamics of movement in a selection of master planned estates in Australia. The study develops new approaches for assessing the containment of travel within planned development. Its key aim is to clarify and map the relationships between trip generation and urban form and structure. The initial conceptual framework of the paper is developed in a review of literature related to urban form and travel behaviour. These concepts are tested empirically in a pilot study of suburban travel activity in master planned estates. A geographical information systems methodology is used to determine regional journey-to-work patterns and travel containment rates. Factors that influence selfcontainment patterns are estimated with a regression model. This research is a useful preliminary examination of travel self-containment in Australian master planned estates.

Research Monograph : Sustainable Australia : Containing travel in master planned estates

Low density suburban development and excessive use of automobiles are associated with serious urban and environmental problems. These problems include traffic congestion, longer commuting times, high automobile dependency, air and water pollution, and increased depletion of natural resources. Master planned development suggests itself as a possible palliative for the ills of low density and high travel. The following study examines the patterns and dynamics of movement in a selection of master planned estates in Australia. The study develops new approaches for assessing the containment of travel within planned development. Its key aim is to clarify and map the relationships between trip generation and urban form and structure. The initial conceptual framework of the report is developed in a review of literature related to urban form and travel behaviour. These concepts are tested empirically in a pilot study of suburban travel activity in master planned estates. A geographical information systems (GIS) methodology is used to determine regional journey-to-work patterns and travel containment rates. Factors that influence self-containment patterns are estimated with a regression model. The key research findings of the pilot study are: - There is a strong relation between urban structural form and patterns of trip generation; - The travel self-containment of Australian master planned estates is lower than the scholarly literature implies would occur if appropriate planning principles to achieve sustainable urban travel were followed; - Proximity to the central business district, income level and education status are positively correlated with travel containment; - Master planned estates depend more on local and regional centres for employment than on the central business district; - The service sector is the major employer in and around master planned estates. It tends to provide part-time and casual employment rather than full-time employment; - Travel self-containment is negative correlated with car dependency. Master planned estates with less car dependent residents, and with good access to public transport, appear to be more self-contained and, consequently, more sustainable than the norm. This research is a useful preliminary examination of travel self-containment in Australian master planned estates. It by no means exhausts the subject. In future research we hope to further assess sustainable travel patterns with more detailed spatial analysis.

Modelling the Impact of Built Environment, Geographical Scales and Latent Constructs On Individual Travel Behaviour

La relación entre la estructura urbana y la movilidad ha sido estudiada desde hace más de 70 años. El entorno urbano incluye múltiples dimensiones como por ejemplo: la estructura urbana, los usos de suelo, la distribución de instalaciones diversas (comercios, escuelas y zonas de restauración, parking, etc.). Al realizar una revisión de la literatura existente en este contexto, se encuentran distintos análisis, metodologías, escalas geográficas y dimensiones, tanto de la movilidad como de la estructura urbana. En este sentido, se trata de una relación muy estudiada pero muy compleja, sobre la que no existe hasta el momento un consenso sobre qué dimensión del entorno urbano influye sobre qué dimensión de la movilidad, y cuál es la manera apropiada de representar esta relación. Con el propósito de contestar estas preguntas investigación, la presente tesis tiene los siguientes objetivos generales: (1) Contribuir al mejor entendimiento de la compleja relación estructura urbana y movilidad. y (2) Entender el rol de los atributos latentes en la relación entorno urbano y movilidad. El objetivo específico de la tesis es analizar la influencia del entorno urbano sobre dos dimensiones de la movilidad: número de viajes y tipo de tour. Vista la complejidad de la relación entorno urbano y movilidad, se pretende contribuir al mejor entendimiento de la relación a través de la utilización de 3 escalas geográficas de las variables y del análisis de la influencia de efectos inobservados en la movilidad. Para el análisis se utiliza una base de datos conformada por tres tipos de datos: (1) Una encuesta de movilidad realizada durante los años 2006 y 2007. Se obtuvo un total de 943 encuestas, en 3 barrios de Madrid: Chamberí, Pozuelo y Algete. (2) Información municipal del Instituto Nacional de Estadística: dicha información se encuentra enlazada con los orígenes y destinos de los viajes recogidos en la encuesta. Y (3) Información georeferenciada en Arc-GIS de los hogares participantes en la encuesta: la base de datos contiene información respecto a la estructura de las calles, localización de escuelas, parking, centros médicos y lugares de restauración. Se analizó la correlación entre e intra-grupos y se modelizaron 4 casos de atributos bajo la estructura ordinal logit. Posteriormente se evalúa la auto-selección a través de la estimación conjunta de las elecciones de tipo de barrio y número de viajes. La elección del tipo de barrio consta de 3 alternativas: CBD, Urban y Suburban, según la zona de residencia recogida en las encuestas. Mientras que la elección del número de viajes consta de 4 categorías ordinales: 0 viajes, 1-2 viajes, 3-4 viajes y 5 o más viajes. A partir de la mejor especificación del modelo ordinal logit. Se desarrolló un modelo joint mixed-ordinal conjunto. Los resultados indican que las variables exógenas requieren un análisis exhaustivo de correlaciones con el fin de evitar resultados sesgados. ha determinado que es importante medir los atributos del BE donde se realiza el viaje, pero también la información municipal es muy explicativa de la movilidad individual. Por tanto, la percepción de las zonas de destino a nivel municipal es considerada importante. En el contexto de la Auto-selección (self-selection) es importante modelizar conjuntamente las decisiones. La Auto-selección existe, puesto que los parámetros estimados conjuntamente son significativos. Sin embargo, sólo ciertos atributos del entorno urbano son igualmente importantes sobre la elección de la zona de residencia y frecuencia de viajes. Para analizar la Propensión al Viaje, se desarrolló un modelo híbrido, formado por: una variable latente, un indicador y un modelo de elección discreta. La variable latente se denomina “Propensión al Viaje”, cuyo indicador en ecuación de medida es el número de viajes; la elección discreta es el tipo de tour. El modelo de elección consiste en 5 alternativas, según la jerarquía de actividades establecida en la tesis: HOME, no realiza viajes durante el día de estudio, HWH tour cuya actividad principal es el trabajo o estudios, y no se realizan paradas intermedias; HWHs tour si el individuo reaiza paradas intermedias; HOH tour cuya actividad principal es distinta a trabajo y estudios, y no se realizan paradas intermedias; HOHs donde se realizan paradas intermedias. Para llegar a la mejor especificación del modelo, se realizó un trabajo importante considerando diferentes estructuras de modelos y tres tipos de estimaciones. De tal manera, se obtuvieron parámetros consistentes y eficientes. Los resultados muestran que la modelización de los tours, representa una ventaja sobre la modelización de los viajes, puesto que supera las limitaciones de espacio y tiempo, enlazando los viajes realizados por la misma persona en el día de estudio. La propensión al viaje (PT) existe y es específica para cada tipo de tour. Los parámetros estimados en el modelo híbrido resultaron significativos y distintos para cada alternativa de tipo de tour. Por último, en la tesis se verifica que los modelos híbridos representan una mejora sobre los modelos tradicionales de elección discreta, dando como resultado parámetros consistentes y más robustos. En cuanto a políticas de transporte, se ha demostrado que los atributos del entorno urbano son más importantes que los LOS (Level of Service) en la generación de tours multi-etapas. la presente tesis representa el primer análisis empírico de la relación entre los tipos de tours y la propensión al viaje. El concepto Propensity to Travel ha sido desarrollado exclusivamente para la tesis. Igualmente, el desarrollo de un modelo conjunto RC-Number of trips basado en tres escalas de medida representa innovación en cuanto a la comparación de las escalas geográficas, que no había sido hecha en la modelización de la self-selection. The relationship between built environment (BE) and travel behaviour (TB) has been studied in a number of cases, using several methods - aggregate and disaggregate approaches - and different focuses – trip frequency, automobile use, and vehicle miles travelled and so on. Definitely, travel is generated by the need to undertake activities and obtain services, and there is a general consensus that urban components affect TB. However researches are still needed to better understand which components of the travel behaviour are affected most and by which of the urban components. In order to fill the gap in the research, the present dissertation faced two main objectives: (1) To contribute to the better understanding of the relationship between travel demand and urban environment. And (2) To develop an econometric model for estimating travel demand with urban environment attributes. With this purpose, the present thesis faced an exhaustive research and computation of land-use variables in order to find the best representation of BE for modelling trip frequency. In particular two empirical analyses are carried out: 1. Estimation of three dimensions of travel demand using dimensions of urban environment. We compare different travel dimensions and geographical scales, and we measure self-selection contribution following the joint models. 2. Develop a hybrid model, integrated latent variable and discrete choice model. The implementation of hybrid models is new in the analysis of land-use and travel behaviour. BE and TB explicitly interact and allow richness information about a specific individual decision process For all empirical analysis is used a data-base from a survey conducted in 2006 and 2007 in Madrid. Spatial attributes describing neighbourhood environment are derived from different data sources: National Institute of Statistics-INE (Administrative: municipality and district) and GIS (circular units). INE provides raw data for such spatial units as: municipality and district. The construction of census units is trivial as the census bureau provides tables that readily define districts and municipalities. The construction of circular units requires us to determine the radius and associate the spatial information to our households. The first empirical part analyzes trip frequency by applying an ordered logit model. In this part is studied the effect of socio-economic, transport and land use characteristics on two travel dimensions: trip frequency and type of tour. In particular the land use is defined in terms of type of neighbourhoods and types of dwellers. Three neighbourhood representations are explored, and described three for constructing neighbourhood attributes. In particular administrative units are examined to represent neighbourhood and circular – unit representation. Ordered logit models are applied, while ordinal logit models are well-known, an intensive work for constructing a spatial attributes was carried out. On the other hand, the second empirical analysis consists of the development of an innovative econometric model that considers a latent variable called “propensity to travel”, and choice model is the choice of type of tour. The first two specifications of ordinal models help to estimate this latent variable. The latent variable is unobserved but the manifestation is called “indicators”, then the probability of choosing an alternative of tour is conditional to the probability of latent variable and type of tour. Since latent variable is unknown we fit the integral over its distribution. Four “sets of best variables” are specified, following the specification obtained from the correlation analysis. The results evidence that the relative importance of SE variables versus BE variables depends on how BE variables are measured. We found that each of these three spatial scales has its intangible qualities and drawbacks. Spatial scales play an important role on predicting travel demand due to the variability in measures at trip origin/destinations within the same administrative unit (municipality, district and so on). Larger units will produce less variation in data; but it does not affect certain variables, such as public transport supply, that are more significant at municipality level. By contrast, land-use measures are more efficient at district level. Self-selection in this context, is weak. Thus, the influence of BE attributes is true. The results of the hybrid model show that unobserved factors affect the choice of tour complexity. The latent variable used in this model is propensity to travel that is explained by socioeconomic aspects and neighbourhood attributes. The results show that neighbourhood attributes have indeed a significant impact on the choice of the type of tours either directly and through the propensity to travel. The propensity to travel has a different impact depending on the structure of each tour and increases the probability of choosing more complex tours, such as tours with many intermediate stops. The integration of choice and latent variable model shows that omitting important perception and attitudes leads to inconsistent estimates. The results also indicate that goodness of fit improves by adding the latent variable in both sequential and simultaneous estimation. There are significant differences in the sensitivity to the latent variable across alternatives. In general, as expected, the hybrid models show a major improvement into the goodness of fit of the model, compared to a classical discrete choice model that does not incorporate latent effects. The integrated model leads to a more detailed analysis of the behavioural process. Summarizing, the effect that built environment characteristics on trip frequency studied is deeply analyzed. In particular we tried to better understand how land use characteristics can be defined and measured and which of these measures do have really an impact on trip frequency. We also tried to test the superiority of HCM on this field. We can concluded that HCM shows a major improvement into the goodness of fit of the model, compared to classical discrete choice model that does not incorporate latent effects. And consequently, the application of HCM shows the importance of LV on the decision of tour complexity. People are more elastic to built environment attributes than level of services. Thus, policy implications must take place to develop more mixed areas, work-places in combination with commercial retails.

The Impact of Transit Oriented Development on the Travel Behaviors of Workers in Denver, Colorado

To combat unsustainable transportation systems characterized by reliance on petroleum, polluting emissions, traffic congestion and suburban sprawl, planners encourage mixed use, densely populated areas that provide individuals with opportunities to live, work, eat and shop without necessarily having to drive private automobiles to accommodate their needs. Despite these attempts, the frequency and duration of automobile trips has consistently increased in the United States throughout past decades. While many studies have focused on how residential proximity to transit influences travel behavior, the effect of workplace location has largely been ignored. This paper asks, does working near a TOD influence the travel behaviors of workers differently than workers living near a TOD? We examine the non-work travel behaviors of workers based upon their commuting mode and proximity to TODs. The data came from a 2009 travel behavior survey by the Denver Regional Council of Governments, which contains 8,000 households, 16,000 individuals, and nearly 80,000 trips. We measure sustainable travel behaviors as reduced mileage, reduced number of trips, and increased use of non-automobile transportation. The results of this study indicate that closer proximity of both households and workplaces to TODs decrease levels of car commuting and that non-car commuting leads to more sustainable personal travel behaviors characterized by more trips made with alternative modes.

An analysis of the automobile market: modeling of the long-run determinants of the demand for automobiles. Volume III: appendices to the Wharton E.F.A. Automobile Demand Model. Final report.

Transportation Department, Washington, D.C.

Revisions to the Wharton EFA Automobile Demand Model (Mark I). Final report.

National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.

An analysis of the automobile market: modeling of the long-run determinants of the demand for automobiles. Volume II: simulation analysis using the Wharton E.F.A. Automobile Demand Model. Final report.

Transportation Department, Washington, D.C.

Accident and near accident causation: the contribution of automobile design characteristics. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

An analysis of the automobile market: modeling of the long-run determinants of the demand for automobiles. Volume I: the Wharton E.F.A. Automobile Demand Model. Final report.

Transportation Department, Washington, D.C.

Purposes of vehicle trips and travel: report 3, 1977 - NPTS. Final report.

Mode of access: Internet.

Survey of suspension systems on vehicles towing travel trailers II. Volume 15. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Nationwide Personal Transportation Survey : summary of travel trends /

Includes glossary.

THE INFLUENCE OF URBAN FORM AT DIFFERENT GEOGRAPHICAL SCALES ON TRAVEL BEHAVIOR; EVIDENCE FROM U.S. CITIES

Suburban lifestyle is popular among American families, although it has been criticized for encouraging automobile use through longer commutes, causing heavy traffic congestion, and destroying open spaces (Handy, 2005). It is a serious concern that people living in low-density suburban areas suffer from high automobile dependency and lower rates of daily physical activity, both of which result in social, environmental and health-related costs. In response to such concerns, researchers have investigated the inter-relationships between urban land-use pattern and travel behavior within the last few decades and suggested that land-use planning can play a significant role in changing travel behavior in the long-term. However, debates regarding the magnitude and efficiency of the effects of land-use on travel patterns have been contentious over the years. Changes in built-environment patterns is potentially considered a long-term panacea for automobile dependency and traffic congestion, despite some researchers arguing that the effects of land-use on travel behavior are minor, if any. It is still not clear why the estimated impact is different in urban areas and how effective a proposed land-use change/policy is in changing certain travel behavior. This knowledge gap has made it difficult for decision-makers to evaluate land-use plans and policies. In addition, little is known about the influence of the large-scale built environment. In the present dissertation, advanced spatial-statistical tools have been employed to better understand and analyze these impacts at different scales, along with analyzing transit-oriented development policy at both small and large scales. The objective of this research is to: (1) develop scalable and consistent measures of the overall physical form of metropolitan areas; (2) re-examine the effects of built-environment factors at different hierarchical scales on travel behavior, and, in particular, on vehicle miles traveled (VMT) and car ownership; and (3) investigate the effects of transit-oriented development on travel behavior. The findings show that changes in built-environment at both local and regional levels could be very influential in changing travel behavior. Specifically, the promotion of compact, mixed-use built environment with well-connected street networks reduces VMT and car ownership, resulting in less traffic congestion, air pollution, and energy consumption.

Chi viaggia ha delle storie da raccontare : those who travel have stories to tell

This review article uses the work of Italian scholar Milly Buonanno to review the state and future of television scholarship, given that the ‘age of television’ has been overtaken by the age of computer-based media. In particular, it discusses the role of open-ended narrative through which we collectively explore the human condition.