A Conceptual Framework for Understanding Latent Demand: Accounting for Unrealized Activities and Travel

Friday, April 21, 2017, 12:00pm to 1:00pm PDT

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Latent demand—the activities and travel that are desired but unrealized because of constraints—have been historically examined from the standpoint of understanding the impacts of proposed capacity or service improvements on travel demand.

Drawing on work from a variety of theoretical perspectives, this paper presents a broader conceptual view of latent demand that provides a useful framework for researching and understanding these unmet needs. This is important from an equity standpoint, as it provides insights into to questions of transport disadvantage, social exclusion and poverty.

The framework presented here is theoretical in nature and untested empirically. This study aims to promote discussion and ultimately a more developed theory that can inform transportation planning and forecasting. A better definition and quantification of latent (or induced) demand can aid transportation planners to better predict the impacts of future...

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Getting to Know the Data: Understanding assumptions, sensitivities, uncertainty, and being "conservative" while using ITE's Trip Generation Data in the Land Development Process

Friday, April 14, 2017, 12:00pm to 1:00pm PDT

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Many agencies rely on trip generation estimates to evaluate the transportation impacts of land development in urban and suburban areas alike. Over the past decade, substantial attention has been paid to one national set of guidelines—the Institute of Transportation Engineers (ITE) Trip Generation Handbook (2014) and corresponding Manual (2012)—focusing in particular to improve the use of these data and supplementary methods for urban contexts. 

The purpose of this study is to explore the typical data provided in the Handbook, within the context of these new improved state-of-the-art methods. As ITE’s describes, “an example of poor professional judgment is to rely on rules of thumb without understanding or considering their derivation or initial context” (Institute of Transportation Engineers, 2014, p. 3). This research aims to improve the understanding of these data—still ubiquitously used across the US—to encourage increased engagement with their meaning, and following, to provide the users (e.g., engineering, planners, agencies, and...

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Urbanism Next: How technology is changing our city

Friday, April 7, 2017, 12:00pm to 1:00pm PDT

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Advances in technology such as the advent of autonomous vehicles (AV’s), the rise of E-commerce, and the proliferation of the sharing economy are having profound effects not only on how we live, move, and spend our time in cities, but also increasingly on urban form and development itself. These new technologies are changing the ease of transport, the role of transit, and the places we spend our time. These changes will have profound effects on cities including large shifts in land use, changes in street design, a potential reduction on the need for parking, a shift on where we choose to live, and challenges for urban density, the extent of sprawl, and the vitality of urban areas.

While there has been a focused effort of research on the technological aspects of autonomous vehicles and systems themselves, there has been a shortage of systematic exploration on their secondary effects on city development, form, and design, with implications for sustainability, resiliency, equity, cost...

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Webinar: Bang for the Buck? Following the Money from Transportation Decisions to Outcomes

Tuesday, March 21, 2017, 10:00am to 11:00am PDT

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Federal, state and local governments spend roughly 5 percent of their total expenditures on transportation: roads, bridges, tunnels, public transit, ports, etc. Such projects and programs are intended to support the efficient movement of people, goods and services, but also impact livability and other societal goals. The 2012 federal transportation reauthorization, MAP-21, is calling for more performance-based decision-making.

A recent research project examines transportation decision-making in six innovative states: California, Massachusetts, Minnesota, Tennessee, Utah, and Virginia.

This webinar will offer examples of current decision-making practices, note strengths and weaknesses, and highlight significant gaps in linking transportation investment decisions to outcomes.

Key takeaways include a suggested comprehensive framework for performance-based transportation decision-making and ideas for going beyond MAP-21.

...

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Dynamic Assignment Models and their Application in the Portland Metro Region

Friday, March 17, 2017, 12:00pm to 1:00pm PDT

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Metro's Research and Modeling Services Program is responsible for the development, maintenance, and application of travel demand models for application in long-range planning efforts in the Portland metropolitan region.

Representation of traffic—both vehicular and transit—plays an integral role in the travel demand modeling process. Complex software is required to assign vehicles and transit users to transportation networks to determine viable options available to travelers, costs associated with those options, and sets of routes by which travelers might navigate their trips. 

Metro's current static assignment model has traditionally sufficed for use with Metro's four-step travel demand model. However, static assignments have well-documented limitations that preclude the ability of the analyst to answer complex policy questions, especially those related to greenhouse...

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Addressing Data Challenges for Bicycle Crash Analysis

Friday, March 10, 2017, 12:00pm to 1:00pm PST

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Although an increasing number of separated bicycle facilities have been appearing across the US over the last few years, the majority of bicyclists are still traveling on roadways shared with motorized vehicles.

As a result, bicycles are essentially double exposed to safety risk, due to their interactions with both motorized vehicles and other bicycles. In addition to this double exposure, data challenges–such as a lack of continuous counts and bicycle crash data—complicate the assessment of bicycle safety further.

This research presents a bicycle crash analysis framework for estimating bicycle crash rates accounting for both bicycle and motorized vehicle exposure as well as overcoming the lack of bicycle count data.

First, a novel seasonal bicycle demand model is presented that is capable of estimating monthly average daily bicyclists (MADB) and annual average daily bicyclists (AADB) using an area-specific calibration factor. This factor can...

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Big data and the future of travel modeling

Friday, March 3, 2017, 12:00pm to 1:00pm PST

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New technologies such as smart phones and web applications constantly collect data on individuals' trip-making and travel patterns. Efforts at using these "Big data" products, to date, have focused on using them to expand or inform traditional travel demand modeling frameworks; however, it is worth considering if a new framework built to maximize the strengths of big data would be more useful to policy makers and planners.

In this presentation Greg Macfarlane will present a discussion on elements of travel models that could quickly benefit from big data and concurrent machine learning techniques, and results from a preliminary application of a prototype framework in Asheville, North Carolina.

Dr. Macfarlane is an analyst in the Systems Analysis Group of WSP | Parsons Brinckerhoff, developing and applying advanced travel demand models. His research and expertise includes trip-based models, activity-based models, integrated land-use/transport models, and micro-simulation of both travel...

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Student Presentations from TRB, Week 3: Positive Utility of Travel & Impact of Bike Facilities

Friday, February 24, 2017, 12:00pm to 1:00pm PST

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Exploring the Positive Utility of Travel and Mode Choice

Civil & Environmental Engineering: Patrick Singleton

Why do people travel? We traditionally assume traveling is a means to an end, travel demand is derived (from the demand for activities), and travel time is to be minimized. Recently, scholars have questioned these axioms, noting that some people may like to travel, use travel time productively, enjoy the experience of traveling, or travel for non-utilitarian reasons. The idea that travel can provide benefits and may be motivated by factors beyond reaching activity destinations is known as...

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Webinar: Integrating explicit and implicit methods in travel behavior research: A study of driver attitudes and bias

Tuesday, February 21, 2017, 10:00am to 11:00am PST

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Car crashes are still a leading cause of death in the United States, with vulnerable road users like bicyclists and pedestrians being injured or killed at rates that outpace their mode share.

Planners, engineers, and advocates are increasingly adopting Vision Zero and Tactical Urbanism approaches and trying to better understand the underlying causes of dangerous roadway interactions. However, existing research into crash causation has focused on instrumental factors (e.g. intersection type, vehicle speed) while little research has probed the role of attitudes or socio-cognitive mechanisms in interactions between roadway users.

Social psychology suggests that attitudes and social cognitions can play a role in conflict. Drivers’ attitudes toward bicyclists, and how those attitudes may affect drivers’ behavior, are a largely unexplored area of research, particularly...

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Using Fuzzy Cognitive Maps to Model Policy Issues in the face of Uncertainty and Limited Data

Friday, February 17, 2017, 12:00pm to 1:00pm PST

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Planners and policymakers are often faced with the need to make decisions about issues for which there is uncertainty and limited data. For example, transportation planners are now faced with the prospect that new transportation technologies such as autonomous vehicles could greatly alter future transportation system needs. Decisions about these types of issues are difficult to reason about and consequently are likely to be ignored or made on the basis of simplistic logic. Although modeling could be helpful, especially for issues involving complex systems, it is rarely used because models usually require large amounts of data and and handle uncertainty poorly.

This presentation is about how a fuzzy systems dynamic model (FSDM) may be used to model policy issues involving uncertainty and limited data. The FSDM is a type of fuzzy cognitive...

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