Report: travel-time data lacking at key spots on Portland-area freeways

Mar 16, 2011

It’s a common occurrence: a digital signboard over the freeway tells you to expect a 15-minute trip, but traffic clears and you arrive in 10 minutes. Or, worse, you hit a clog and arrive in 30 minutes.

Sometimes those signboards, called dynamic message signs, are way off, Portland State University researcher Kristin Tufte found. But sometimes that doesn’t matter.

Tufte examined the signboards, called dynamic message signs, along Portland-area freeways in an OTREC project. Drivers typically reach their destinations earlier or later than the signs told them to expect when a so-called “shock wave” forms or dissipates; that is, when traffic suddenly bunches or clears up.

Currently, only three of the 30 or so message signs in the Portland metro area display travel times. Detectors at freeway onramps feed those signs. As a result, large swaths of freeway without onramps also have no data. To be most useful, new message signs would require more detectors in certain areas.

Take the busy Marquam Bridge in Portland, where busy freeways merge and there is no signboard. “There’s no detection for the whole length of the bridge,” Tufte said. “If you really want to have accurate travel times, you have to have detection there.”

As expected, Tufte found that traffic bunching or clearing in blind zones can throw off the accuracy of travel times displayed. Surprisingly, that inaccurate information is...

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Transit stations operate in sweet microenvironment

Dec 06, 2010

Even residents of a gingerbread candyland can't get around with holiday magic alone. After all, Santa's elves still need a reliable way to get from their cozy homes to the workshop.

Sadly, transportation planners have turned a frosty shoulder to sugar-based transit systems. Until now.

On Dec. 3, Portland State University's Students in Transportation Engineering and Planning held the first gingerbread transit station competition. Four teams of students pulled their attention away from human transit to focus on the needs of gingerbread people and misfit toys.

Dealing with building materials of unknown structural properties, students field engineered solutions. Licorice sticks stood in for steel rails, candy canes for bicycle racks. For a binding agent, students mixed cream of tartar and egg whites instead of portland cement.

The resulting transit system has already resulted in fewer traffic gum-ups and a drastic reduction in ultrafine powdered-sugar emissions. Sleigh-travel-time reliability has also improved.

Researchers are now assessing the durability of corn-syrup-reinforced composites in candy bridges, the potential for alkali-silica reaction in gingerbread pavement and the possibility that someone hungry will stumble in and eat the infrastructure.

The winning design team was Transit Wonderland, composed of Jesse Boudart, Sara Morrissey, Mark Haines and Meeyonwoo Lim.

USDOT official visits Portland to launch transportation modeling initiative

Nov 10, 2010

Good transportation decisions rely on good models. Yet, despite advances in transportation modeling, there had been no dedicated training ground for the next generation of modelers. That all changed with the launch of the Oregon Modeling Collaborative Nov. 12. The collaborative will serve as a living laboratory to put the research from some of America’s top modelers into practice across Oregon.

On Nov. 12, we welcomed Peter Appel, administrator of the federal Research and Innovative Technology Administration, to Portland to kick off the collaborative with researchers, practitioners and policymakers from across the Northwest. Appel, confirmed by the U.S. Senate as administrator in 2009, has worked on U.S. Department of Transportation initiatives aimed at getting researchers and professionals to address safety, efficiency and environmental sustainability across all forms of transportation.

Groundbreaking research at the Oregon Transportation Research and Education Consortium has already produced models to account for bicycle trips and greenhouse gas emissions and to predict earthquake risk to highway bridges. However, models don’t do any good if agencies can’t afford the staff time and resources to use them. The Oregon Modeling Collaborative helps fill this gap by educating the next...

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Residential Choice Locations - A Search in the Mirror of the Past

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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.

SPECIAL SEMINAR: Modeling Urban Commercial Vehicle Movements Using Tour-based Microsimulation

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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Clouds, Crowds, and Traffic: What 10 emerging Megatrends mean for the future of transportation

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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.

Developing a Bicyclist Route Choice Model Using GPS Data

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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.

Integrated Transport/Land Use Modeling

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Managed Lanes in Orlando, FL

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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Modeling High Speed Rail Ridership and Revenue in California: An Overview

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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