Identification and Characterization of PM2.5 and VOC Hot Spots on Arterial Corridor by Integrating Probe Vehicle, Traffic, and Land Use Data: The purpose of this study is to explore the use of integrated probe vehicle, traffic and land use data to identify and characterize fine particulate matter (PM2.5) and volatile organic compound (VOC) hot spot locations on urban arterial corridors. An emission hot spot is defined as a fixed location along a corridor in which the mean pollutant concentrations are consistently above the 85th percentile of pollutant concentrations when considering all other locations along the corridor during the same time period. In order to collect data for this study, an electric vehicle was equipped with instruments designed to measure PM2.5 and VOC concentrations. Second-by-second measurements were performed for each pollutant from both the right and left sides of the vehicle. Detailed meteorological, traffic and land use data is also available for this research. The results of a statistical analysis are used to better understand which data sources are most valuable in estimating PM2.5 and VOC hot spot locations consistent with empirical data, as well as which variables have the greatest impact on emissions and pollutant levels at a microscale level. This research highlights the importance of considering both consistency and peak emission levels when identifying hot spot locations. An objective of this research is to develop a method to identify urban arterial hot spot locations that provides a balance of efficiency (in terms of capital expenses, time, resources, expertise requirements, etc.) and accuracy.

Modeling Impact of Traffic Conditions on Variability of Midblock Roadside Fine Particulate Matter Concentrations on an Urban Arterial: This paper presents an innovative modeling of fine particulate matter (PM2.5) concentrations as a function of very high resolution meteorological and traffic data. Peak period measurements were taken at a mid-block roadside location on an urban arterial commuter roadway. To capture the impact of dynamic traffic conditions, data were analyzed at 10-second intervals, with substantially higher resolution than typical roadside air quality study designs. Particular attention was paid to changes in traffic conditions, including fleet mix, queuing and vehicle platooning over the course of the study period, and the effect of these changes on PM2.5. Significant correlations were observed between vehicle platoons and increases in PM2.5 concentrations. Traffic state analysis was employed to determine median PM2.5 levels before and after the onset of congestion. A multivariate regression model was estimated to determine significant PM2.5 predictors while controlling for autocorrelation. Significance was found not only in the simultaneous traffic variables but also in lagged traffic variables; additionally, the effects of vehicle types and wind direction were quantified. Modeling results indicate that traffic conditions and vehicle type do have a significant impact on roadside PM2.5 concentrations. For instance, the addition of one heavy vehicle was shown to increase PM2.5 concentrations by 2.45% when wind blew across the roadway before reaching the monitoring location. This study serves as a demonstration of the abilities of very high resolution data to identify the effects of relatively minute changes in traffic conditions on air pollutant concentrations.

Effects of the Objective and Perceived Built Environment on Bicycling for Transportation:

This paper investigates the relative effects of the objectively-measured built environment versus stated perceptions of the built-environment on bicycling. Data are from a random phone survey conducted in the Portland, Oregon region. Binary logit and linear regression models, using objective measures, perceived measures, and both sets of measures, were estimated to predict odds of bicycling and frequency of bicycling separately. Results showed that the perceived environment and objective environment had independent effects on bicycling. This suggests that future bicycling research should include both perceived and objective measures of the built environment when possible. In addition, it indicates that interventions that focus on changing perceptions of the environment may be as important as actual changes in the built environment. The objective environment was necessary but not sufficient for bicycling. Intervention programs to improve people’s perceptions of the environment may be necessary to reap the full potential of planning and design policies. The results also suggest that it is useful to predict odds of bicycling and bicycling frequency separately, as the predictors of each behavior do vary. Finally, the analysis confirms the importance of attitudes in predicting behavior.

Evaluating Driver and Pedestrian Behaviors at Enhanced Multilane Midblock Pedestrian Crossings: Case Study in Portland, Oregon This study examines driver and pedestrian behaviors at two enhanced midblock pedestrian crossings in Portland, Oregon. One crossing is on a five-lane arterial with a posted speed of 35/45 miles-per-hour (MPH) and features six rectangular rapid flash beacon (RRFB) assemblies and a narrow median refuge. The other crossing is on a suburban arterial with four travel lanes and a two-way left-turn lane. The crossing is enhanced with four RRFB assemblies and a median island with a “Z” crossing, or Danish offset, designed to encourage pedestrians to face oncoming traffic before completing the second stage of their crossing. Approximately 62 hours of video have been collected at the two locations. A total of 351 pedestrian crossings are analyzed for driver compliance (yielding) rates, pedestrian activation rates, pedestrian delay, and conflict avoidance maneuvers. The suburban arterial crossing is also evaluated to determine its effectiveness at diverting pedestrians to cross at it instead of away from a crosswalk, as well as pedestrian compliance with the Z-crossing. This study finds that average driver yield rates at both sites are just over 90% when the RRFB is activated, which is consistent with previous studies. RRFB actuation rates range from 83% to over 90%. The results also show that approximately 52% of all crossings at the marked crosswalk at the second location are from diverted pedestrians and that the enhanced crossing captures about 82% of all crossings near the crosswalk. Finally, approximately 52%, of the pedestrians using the crosswalk follow the Z-crossing pattern through the median.

Bicycling Is Different: Built Environment Relationships to Nonwork Travel There is growing investment in infrastructure to support non-motorized travel modes in the United States, in particular for bicycling. However, there remains a dearth of knowledge on the relationships between built environments and bicycling for non-work transportation. This issue is exacerbated by researchers and practitioners continuing to combine walking and bicycling into the category “non-motorized modes,” despite the two having many differences. This paper addresses these shortcomings through a segmented analysis of mode choice and mode share for walking, bicycling, and automobile travel. The data used are from a 2011 establishment intercept survey in the Portland, Oregon region and are destination-based. Results show pronounced differences in the empirical relationships between walking and bicycling and the built environment, when controlling for aspects of the individual, site, and trip. Models for mode choice and mode share indicate that the built environment attributes that influence automobile and walk travel are similar; yet, their influence is in the opposite direction. Empirical relationships with the built environment are altogether different for bicycling trips. Socio-demographic variable results are consistent with much of the non-work mode choice literature, but trip distance is not. Trip distance has the expected relationship with walking, but does not have a significant relationship with bicycling. The findings on the built environment relationships with travel modes support a move away from combining walking and bicycling together as non-motorized transportation for analysis and planning. They also lend insight into additional considerations for future work in non-work transportation research and policy.

Benefit-Cost Evaluation Method for Transit Stop Removal The introduction of wider stop spacing through the removal or consolidation of existing stops is one method transit agencies can use to reduce travel time and reliability on many transit lines. A great deal of research has been done to provide tools for determining optimal stop spacing, but tools are still needed to help service planners determine the optimal stops to remove. Stop-level bus performance data provide the information needed to develop a method for assessing the total benefits and costs to riders of removing individual stops. This tool compares the benefit to through-riders in terms of travel time savings with the additional access cost to riders using the stop. The tool was applied to a bus route in Portland, Oregon, using stop-level ridership data from TriMet, the regional transit agency. The case study identifies three stops with very high benefit-cost ratios and discusses the effects of removing those stops. A sensitivity analysis is performed to show the effect of changing the value of time factor or the assumed time savings from each stop removal. Further research needs are identified and tradeoffs are discussed regarding the use of this tool. Overall, the assessment tool provides a relatively simple way for transit service planners to identify ideal stops for removal or consolidation.

The Federal Transit Administration invests in building the capacity and improving the quality of public transportation throughout the United States of America. Under FTA's leadership, public rail, bus, trolley, ferry, and other transit services have reached greater levels of safety, reliability, availability, and accessibility. Come hear the highlights of FTA's impacts and participate in an interactive question/answer session and discussion on career options in public transportation!

Bio: Amy Changchien is the Director of Planning & Program Development of the Federal Transit Administration Region 10 Office in Seattle. Ms. Changchien has been a transportation professional for over 20 years, with experience spanning from highway to transit. In her career, she has worked on projects involving highway operations, Intelligent Transportation System, commuter rail, light rail, streetcar, ferries, and buses. Ms. Changchien holds a bachelor's degree in Civil Engineering and a master's degree in Public Administration from University of Washington.

How do you explain complex ideas? What do you say when reporters ask you to guess about the future? ODOT spokesperson and public affairs manager Dave Thompson will share tips on how to explain a complex topic to reporters and concerned citizens.

Thompson worked as a broadcast news reporter, producer and anchor for 20 years, including anchoring the weekend news at KPTV from 1992 to 2000. He’s been in public relations another 14 years, leading pre-IPO angel-invested startup branding efforts and providing company and government agency perspective to reporters and citizens. And of course, apologizing for Portland’s congestion and warning us about driving in snowstorms.

But Dave didn’t start out in communications: He was a math major! His message: With practice, you can and should speak in public, if you’re prepared and when you’re the subject matter expert. (If he can do it, you can do it!)

Dave will show you how to engage your audience’s imagination to explain the complex, yet stay true to the technical.

Urban bicyclists’ uptake of traffic-related air pollution is still not well quantified, due to a lack of direct measurements of uptake and a lack of analysis of the variation in uptake. This paper describes and establishes the feasibility of a novel method for measuring bicyclists’ uptake of volatile organic compounds (VOC) by sampling breath concentrations. Early results from the data set demonstrate the ability of the proposed method to generate findings for transportation analysis, with statistically significant exposure and uptake differences from bicycling on arterial versus bikeway facilities for several traffic-related VOC. These results provide the first empirical evidence that the usage of bikeways (or greenways) by bicyclists within an urban environment can significantly reduce uptake of dangerous traffic-related gas pollutants. Dynamic concentration and respiration data reveal unfavorable correlations from a health impacts perspective, where bicyclists’ respiration and travel time are greater at higher-concentration locations on already high-concentration roadways (arterials).

Alex Bigazzi is a Ph.D. candidate in Transportation Engineering at PSU, where he is also teaching a class on transportation emissions modeling. His dissertation investigates how urban bicyclists' uptake of air pollution while riding is affected by the transportation system. Alex's dissertation committee is chaired by Miguel Figliozzi, with members Jim Pankow, Robert Bertini, and Jennifer Dill.

In this seminar, Tara Weidner of Oregon DOT will discuss changes in the works to the State Analysis Procedures Manual (APM) to include three graduated levels of bike planning methods for use in Oregon communities, based on community size, data needs, and planning stage. These include the Bike Level of Traffic Stress (BLTS), a sketch tool used to assess bike network connectivity, the data-heavy Highway Capacity Manual Multi-modal Level of Service (MMLOS) procedures, and a simplified MMLOS developed by the same researchers.

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 characteristics, weather, and lighting conditions.

Since about 2008, the planning world has been experiencing a paradigm shift that began in places like California and Oregon that have adopted legislation requiring the linking of land use and transportation plans to outcomes, specifically to the reduction of greenhouse gases (GHGs). In response to this need, Calthorpe Associates has developed a new planning tool, called UrbanFootprint, on a fully Open Source platform (i.e. Ubuntu Linux, PostGIS, PostGreSQL, etc.). As a powerful and dynamic web and mobile-enabled geo-spatial scenario creation and modeling tool with full co-benefits analysis capacity, UrbanFootprint has great utility for urban planning and research at multiple scales, from general plans, to project assessments, to regional and state-wide scenario development and analysis. Scenario outcomes measurement modules include: a powerful ‘sketch’ transportation model that produces travel and emissions impacts; a public health analysis engine that measures land use impacts on respiratory disease, obesity, and related impacts and costs; climate-sensitive building energy and water modeling; fiscal impacts analysis; and greenhouse gas and other emissions modeling.

Where and when does overcrowding happen on TriMet's bus network? Which routes have the best on-time performance? Portland State University and TriMet have collaborated to make this kind of data available to anybody through Portal, PSU's transportation data archive for the Portland/Vancouver region. This presentation will cover the use of General Transit Feed Specification (GTFS) data for mapping TriMet’s performance data and the development of Portal’s innovative transit application. In the MAP-21 era of performance management, see how tools like Portal can support enhanced agency decision-making as well as community engagement.