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Understanding Transportation in Urban China - Local Residents vs Migrant Workers

With rapid urbanization in China and other developing economies around the world, it has become imperative to understand household transportation behavior and expenditures in these urban areas. The objective of this study is to examine the differences in the determinants of household transportation expenditures within two very distinct populations...

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Summary: Ten new megatrends will be presented with a discussion on the resulting shifts on the transportation industry. Details will include a look on broken trends and the new challenges introduced for transportation planning. Thoughts will also be presented introducing a pivot to the current model being pursued by the Connected Vehicle program. Finally, planners will be challenged to consider a new question for the future of our connected communities, you have to come to hear it.

Bio: Ted Trepanier is the Senior Director for the Public Sector with INRIX, Inc.  Prior to joining INRIX, Ted was the Director of Traffic Operations for the Washington State Department of Transportation.  In addition to his extensive background in traffic operations, he has experience in design, planning, project management and toll operations. Ted earned his Bachelor's Degree in Civil Engineering from Washington State University and Masters in Civil Engineering from the University of Washington.

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Abstract: We propose to decompose residential self-selection by understanding its formation process. We take a life course perspective and postulate that locations experienced early in life have a lasting effect on our locational preferences in life. In other words, what was experienced spatially is a key factor contributing to our residential self-selection and our preferences in residential locations are formed long before our own self-selection begins.  We further hypothesize that prior locational influence interacts with period effect such that the same location experienced in different periods may have distinct effects.  Using an empirically collected dataset in the New York Metropolitan Region, we estimated a series of models to test these hypotheses. The results demonstrate that prior locational influence precedes residential self-selection. Furthermore, we show a variety-seeking behavioral pattern resulted from locations experienced during adolescence.

The video begins at 5:58.

A system for modelling commercial movements has been developed for Calgary in Canada, implemented as part of the transportation system modelling used by the City of Calgary in policy analysis. This effort included an extensive set of surveys collecting information on the roughly 37,000 tours and 185,000 trips (within these tours) made in the Calgary Region, with its population of just over 1 million, by commercial vehicles on a typical weekday in 2001. The resulting system of models includes an agent-based microsimulation framework, using a tour-based approach, based on what has been learned from the data. It accounts for truck routes, responds to truck restrictions and related policy and provides insight into various aspects of commercial vehicle movements. All types of commercial vehicles are represented, including light vehicles, heavier single unit and multi-unit configurations. All sectors of the economy are incorporated into the representation, including retail, industrial, service and wholesaling. This modelling system has been integrated with an aggregate equilibrium model of household-related travel covering the Calgary Region, with the microsimulation processes being done in external Java applications.

Dr JD (‘Doug’) Hunt is a Professor of Transportation Engineering and Planning in the Department of Civil Engineering at the University of Calgary in Canada. He is...

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Pricing and Reliability Enhancements in the San Diego Activity-Based Travel Model

The estimation of demand for priced highway lanes is becoming increasingly important to agencies seeking to improve mobility and find alternative revenue sources for the provision of transportation infrastructure.

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Special Seminar: Room 315 of the Maseeh College of Engineering & Computer Science on the Portland State University campus.

Florida’s Turnpike Enterprise has completed planning studies to forecast the revenue earning potential of tolled special use lanes along Interstates in Florida. The tolled special use lanes or “Managed Lanes” will be contained within the interior of the Interstates' highway corridors. The Managed Lanes concept has been incorporated into larger widening projects in Central and South Florida, which is under development by the Florida Department of Transportation. The presentation will focus on the approach and methodology for estimating traffic and revenue for Express Toll Lanes in an existing limited access corridor. The core content is the required data, traffic modeling efforts, and how the results are used by the Finance Department to estimate potential revenues.

Bio: Jack Klodzinski received his Bachelors’, Master’s and Ph.D. in Civil Engineering from the University of Central Florida where his focus was on toll road operations. He is now the Travel Forecast Manager at Florida’s Turnpike for the URS Corporation where his main focus is on traffic forecasting for toll facilities. He works with a team of modelers to produce toll traffic forecasts used in roadway design, operations, or future revenue estimates. Jack also stays active with UCF as a Graduate Faculty Scholar for the Department of Civil, Environmental, and Construction...

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Abstract: Existing regional travel forecasting systems are not typically set up to forecast usage of bicycle infrastructure and are insensitive to bicyclists' route preferences in general. We collected revealed preference, GPS data on 162 bicyclists over the course of several days and coded the resulting trips to a highly detailed bicycle network model. We then use these data to estimate bicyclist route choice models. As part of this research, we developed a sophisticated choice set generation algorithm based on multiple permutations of labeled path attributes, which seems to out-perform comparable implementations of other route choice set generation algorithms. The model was formulated as a Path-Size Logit model to account for overlapping route alternatives. The estimation results show compelling intuitive elasticities for route choice attributes, including the effects of distance and delay; avoiding high-volumes of vehicular traffic, stops and turns, and elevation gain; and preferences for certain bike infrastructure types, particularly at bridge crossings and off-street paths. Estimation results also support segmentation by commute versus non-commute trip types, but are less clear when it comes to gender. The final model will be implemented as part of the regional travel forecasting system for Portland, Oregon, U.S.A.

The video begins at 4:30.

The San Francisco Bay Area, like other metropolitan regions in California, is in the process of developing regional plans to reduce greenhouse gas emissions in response to state legislation that sets targets for such reduction, and prescribes that Metropolitan Planning Organizations develop Sustainable Communities Strategies that leverage changes in land use patterns in combination with transportation investments, that will meet those targets. This talk describes the land use modeling that is being used, in combination with the activity-based transportation model system at the Metropolitan Transportation Commission, to analyze alternative combinations of land use policies and transportation policies. It also will demonstrate visualization technology that has been developed to facilitate community engagement in the process

Speaker Bio: Paul Waddell is Professor and Chair of the City and Regional Planning Department at the University of California, Berkeley. He teaches and conducts research on land use and transportation modeling and planning. He designed and leads the development of the UrbanSim land use modeling platform, now being used in metropolitan planning organizations across the U.S., and in research projects throughout the world.

The video begins at 4:15.

Abstract: The California High-Speed Rail Ridership and Revenue Forecasting Model is a state-of-the-practice transportation model designed to portray what future conditions might look like in California with and without a high-speed train. The model was developed by Cambridge Systematics, Inc., and took roughly two years to complete. The resulting ridership and revenue forecasts provided, and continue to provide, sound information for planning decisions for high-speed rail in California. This presentation briefly describes the underlying model that was developed to generate the ridership and revenue forecasts along with summaries of ridership forecasts from published reports.

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