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Abstract: Integrated land use transportation models simulate the behavior of the spatial economic system and the interactions between the transportation system and the rest of the economic system. The essential elements of these models are explicit treatment of space in economic production and consumption behavior, both the space that is the physical areas that contain production processes and the space that separates different production locations and gives rise to the demand for travel and transport. They put travel within an economic context, and thus facilitate simulation of the impacts of transportation policy and planning actions and transportation conditions on the wider economic system. As such, integrated models can be used address complex policy questions that more limited transportation models cannot address, or cannot address well.

This seminar will set out the basic scope and form of integrated models and discusses several of the key advantages they provide for planning. Experiences gained in the practical applications of the Oregon SWIM and Sacramento MEPLAN and PECAS integrated models will be described. These experiences will be used to illustrate the added benefits arising with such models in terms of more efficient land use forecasting, more complete analysis of cumulative and indirect impacts and more holistic consideration of policy in general, more...

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The proliferation of information technology in the transportation field has opened up opportunities for communication and analysis of the performance of transportation facilities. The Highway Capacity Manual relies on rules of thumb and small data samples to generate levels of service to assess performance, but modern detection technology gives us the opportunity to better capture the dynamism of these systems and examine their performance from many perspectives. Travelers, operations staff, and researchers can benefit from measurements that provide information such as travel time, effectiveness of signal coordination, and traffic density. In particular, inductive loop detectors show promise as a tool to collect the data necessary to generate such information. But while their use for this purpose on restricted‐access facilities is well understood, a great many challenges remain in using loop detectors to measure the performance of surface streets.

This thesis proposes 6 methods for estimating arterial travel time. Estimates are compared to simulated data visually, with input/output diagrams; and statistically, with travel times. Methods for estimating travel time are applied to aggregated data and to varying detector densities and evaluated as above. Conclusions are drawn about which method provides the best estimates, what levels of data aggregation can still provide useful information, and what the effects of detector density are on the quality of estimates....

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Summary: A growing concern related to large-truck crashes has increased in the State of Texas in recent years due to the potential economic impacts and level of injury severity that can be sustained. Yet, studies on large truck involved crashes highlighting the contributing factors leading to injury severity have not been conducted in detail in the State of Texas especially for its interstate system.  In this study, we analyze the contributing factors related to injury severity by utilizing Texas crash data based on a discrete outcome based model which accounts for possible unobserved heterogeneity related to human, vehicle and road-environment. We estimate a random parameter logit model (i.e., mixed logit) to predict the likelihood of five standard injury severity scales commonly used in Crash Records Information System (CRIS) in Texas – fatal, incapacitating, non-incapacitating, possible, and no injury (property damage only). Estimation findings indicate that the level of injury severity outcomes is highly influenced by a number of complex interactions between factors and the effects of the some factors can vary across observations. The contributing factors include drivers’ demographics, traffic flow condition, roadway geometrics, land use and temporal...

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The video begins at 0:16.

Abstract: This seminar will introduce travel models to non-modelers. It will build off the previous seminar, which introduced models in general, and discuss two primary approaches to travel modeling – four-step aggregate models and activity-based disaggregate models. The inputs, basic model methodology, and outputs of each approach will be discussed. An example of each approach will be discussed as well. The goal of the seminar is to introduce key concepts, basic differences between the two approaches, and discuss the benefits and shortcomings of each approach, with a focus on application.

Speaker Bio: Ben Stabler is a supervising planner with Parsons Brinckerhoff who specializes in planning modeling systems development. Ben has worked locally, as well as internationally, on numerous four-step and activity-based travel demand and land use modeling systems and has presented at various conferences, including TRB, the TRB Planning Applications Conference, and the Innovations in Travel Modeling conference. He is a certified GIS Professional and has worked in travel forecasting for Oregon DOT as well as PTV – the makers of VISUM and VISSIM. Ben is a member of the TRB Urban Transportation Data and Information Systems Committee (ABJ30) and is an active member of the Oregon Modeling Users Group.

The video begins at 0:27.

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Summary: The Transportation Planning Analysis Unit (TPAU) at ODOT helps to provide information to a large variety of transportation plans, projects, and policy questions.  This allows customers to make better informed decisions and to maximize limited resources.  In order to fill this role TPAU and the Oregon modeling community have a fairly large "toolbox" of models and analysis tools and procedures.  This transportation seminar will give an overview of the role and services that TPAU provides and the different tools and processes used to fulfill that role.

The video begins at 3:30.

Abstract: We all use abstractions of reality to help understand the world around us, synthesize knowledge, and to predict the consequences of our actions. These range from ad hoc mental models to highly complex mathematical creations. In this discussion we'll examine the motivations for building formal models, with particular focus on the types of models that will be explored in this course. Several different modeling approaches will be compared, along with the strengths and limitations of each. Some important questions that builders and consumers of models should ask will be covered, as well as ideas for building more useful and informative models. A discussion on how to judge the validity of a model will round out the discussion.

Speaker Bio: Rick Donnelly has over 25 years of experience in the modeling and simulation of transportation systems, from the urban to national level. His current interests include agent-based modeling of freight and logistics, integrated land use-transportation models, and dynamic network modeling. Rick leads the travel modeling and simulation practice at Parsons Brinckerhoff, an international civil and transportation engineering consultancy. He is also a senior fellow at the University of Melbourne, where he earned his doctorate in engineering, and a visiting scholar at Los Alamos National Laboratory.

Transportation mode choice is often expressed in terms of models which assume rational choice; psychological case studies of mode adoption are comparatively rare. We present findings from a study of the psychology of adoption for sustainable transportation modes such as bicycles, car sharing, and mass transit. Case studies were conducted with current and former participants in PSU’s ‘Passport Plus’ transit pass program, as well as a longitudinal cohort study of first-time winter bicycle commuters. Composite sequence analysis was used to construct a theory of the adoption process for these modes. Our findings suggest that mode evaluation is cognitively distinct from mode selection and has different information requirements. We conclude that public and private organizations could improve the adoption rate for these modes by tailoring their communication strategies to match the commuter’s stage of adoption.

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Steven Gehrke, Ph.D. Candidate, Portland State University

Topic: An Activity-related Land Use Mix Construct and Its Connection to Pedestrian Travel

Land use mix is a central smart growth principle connected to active transportation. This presentation describes the indicators of local land use mixing and their association with pedestrian travel in Oregon’s Willamette River Valley. It argues that land use mix is a multidimensional construct reflected by the complementarity, composition, and configuration of land use types, which is positively linked to walk mode choice and home-based trip frequency. Findings from this study underline the conceptual and empirical benefit of analyzing this transportation-land use interaction with a landscape pattern measure of activity-related composition and spatial configuration.

Steven Gehrke is a Ph.D. candidate in Civil and Environmental Engineering at Portland State University. His research examines the transportation-land use interaction,...

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