Relation of modifiable neighborhood attributes to walking

Abstract Background There is a paucity of research examining associations between walking and environmental attributes that are more modifiable in the short term, such as car parking availability, access to transit, neighborhood traffic, walkways and trails, and sidewalks. Methods Adults were recruited between April 2004 and September 2006 in the Minneapolis-St Paul metropolitan area and in Montgomery County, Maryland using similar research designs in the two locations. Self-reported and objective environmental measures were calculated for participants\u27 neighborhoods. Self-reported physical activity was collected through the long form of the International Physical Activity Questionnaire (IPAQ-LF). Generalized estimating equations were used to examine adjusted associations between environmental measures and transport and overall walking. Results Participants (n = 887) averaged 47 years of age (SD = 13.65) and reported 67 min/week (SD = 121.21) of transport walking and 159 min/week (SD = 187.85) of non-occupational walking. Perceived car parking difficulty was positively related to higher levels of transport walking (OR 1.41, 95%CI: 1.18, 1.69) and overall walking (OR 1.18, 95%CI: 1.02, 1.37). Self-reported ease of walking to a transit stop was negatively associated with transport walking (OR 0.86, 95%CI: 0.76, 0.97), but this relationship was moderated by perceived access to destinations. Walking to transit also was related to non-occupational walking (OR 0.85, 95%CI: 0.73, 0.99). Conclusions Parking difficulty and perceived ease of access to transit are modifiable neighborhood characteristics associated with self-reported walking

Hiding Private Locations by Anonymizing Data

Researchers explore ways of masking private locations in the interest of making useful data publicly available

Modeling the Effects of Congestion on Fuel Economy for Advanced Power Train Vehicles

This paper describes research undertaken to establish plausible fuel-speed curves (FSC) for hypothetical advanced power train vehicles. These FSC are needed to account for the effects of congestion in long-term transportation scenario analysis considering fuel consumption and emissions. We use the PERE fuel consumption model with real-world driving schedules and a range of vehicle characteristics to estimate fuel economy (FE) in varying traffic conditions for light-duty internal combustion engine (ICE) vehicles, hybrid gas-electric vehicles (HEV), fully electric vehicles (EV), and fuel cell vehicles (FCV). FSC are fit to model results for each of 145 hypothetical vehicles. Analysis of the FSC shows that advanced powertrain vehicles are expected to perform proportionally better in congestion than ICE vehicles (when compared to their performance in free-flow conditions). HEV are less sensitive to average speed than ICE vehicles, and tend to maintain their free-flow FE down to 20 mph. FE increases for EV and FCV from free-flow conditions down to about 20-30 mph. Beyond powertrain type differences, relative FE in congestion is expected to improve for vehicles with less weight, smaller engines, higher hybrid thresholds, and lower accessory loads (such as air conditioning usage). Relative FE in congestion also improves for vehicle characteristics that disproportionately reduce efficiency at higher speeds, such as higher aerodynamic drag and rolling resistance. In order to implement these FSC for scenario analysis, we propose a bounded approach based on a qualitative characterization of the future vehicle fleet. The results presented in this paper will assist analysis of the roles that vehicle technology and congestion mitigation can play in reducing fuel consumption and emissions from roadway travel

Moving from Cars to People

The twenty-page comic includes a dialogue, taking place in various urban settings, between characters Kelly and Kristi who are based on National Institute for Transportation and Communities (NITC) researchers Kelly Clifton of the University of British Columbia and Kristina Currans of the University of Arizona. The two have a long history of collaboration around the data, methods, and processes used to plan for multimodal transportation impacts of new development. This short graphic synopsis is an engaging, approachable way for anyone – no matter their level of expertise in this topic – to learn about their findings. Illustrated by PSU Master of Fine Arts student Joaquin Golez, the comic was authored by Clifton and Currans and developed in conjunction with Susan Kirtley, director of the Comic Studies Program at Portland State University (PSU), and Portland, OR-based illustrator Ryan Alexander-Tanner, who has worked on academic comics before and drew on his experience to help guide the collaborative process

Adjusting ITE’s Trip Generation Handbook for Urban Context

This study examines the ways in which urban context affects vehicle trip generation rates across three land uses. An intercept travel survey was administered at 78 establishments (high-turnover restaurants, convenience markets, and drinking places) in the Portland, Oregon, region during 2011. This approach was developed to adjust the Institute of Transportation Engineers (ITE) Trip Generation Handbook vehicle trip rates based on built environment characteristics where the establishments were located. A number of policy-relevant built environment measures were used to estimate a set of nine models predicting an adjustment to ITE trip rates. Each model was estimated as a single measure: activity density, number of transit corridors, number of high-frequency bus lines, employment density, lot coverage, length of bicycle facilities, presence of rail transit, retail and service employment index, and intersection density. All of these models perform similarly (Adj. R2 0.76-0.77) in estimating trip rate adjustments. Data from 34 additional sites were collected to verify the adjustments. For convenience markets and drinking places, the adjustment models were an improvement to the ITE’s handbook method, while adjustments for restaurants tended to perform similarly to those from ITE’s estimation. The approach here is useful in guiding plans and policies for a short-term improvement to the ITE’s Trip Generation Handbook. The measures are useful for communities seeking to develop local adjustments to vehicle trip rate estimates, and all could be calculated from spatial data available in most locations. The paper concludes with a discussion on what long-term improvements to the ITE’s Trip Generation Handbook might entail, with further implications in planning and practice

Comparing objective measures of environmental supports for pedestrian travel in adults

Background: Evidence is growing that the built environment has the potential to influence walking--both positively and negatively. However, uncertainty remains on the best approaches to representing the pedestrian environment in order to discern associations between walking and the environment. Research into the relationship between environment and walking is complex; challenges include choice of measures (objective and subjective), quality and availability of data, and methods for managing quantitative data through aggregation and weighting. In particular, little research has examined how to aggregate built environment data to best represent the neighborhood environments expected to influence residents' behavior. This study examined associations between walking and local pedestrian supports (as measured with an environmental audit), comparing the results of models using three different methods to aggregate and weight pedestrian features. Methods: Using data collected in 2005-2006 for a sample of 251 adult residents of Montgomery County, MD, we examined associations between pedestrian facilities and walking behaviors (pedestrian trips and average daily steps). Adjusted negative binomial and ordinary least-squares regression models were used to compare three different data aggregation techniques (raw averages, length weighting, distance weighting) for measures of pedestrian facilities that included presence, condition, width and connectivity of sidewalks, and presence of crossing aids and crosswalks. Results: Participants averaged 8.9 walk trips during the week; daily step counts averaged 7042. The three aggregation techniques revealed different associations between walk trips and the various pedestrian facilities. Crossing aids and good sidewalk conditions were associated with walk trips more than were other pedestrian facilities, while sidewalk facilities and features showed associations with steps not observed for crossing aids and crosswalks. Conclusion: Among three methods of aggregation examined, the method that accounted for distance from participant's home to the pedestrian facility (distance weighting) is promising; at the same time, it requires the most time and effort to calculate. This finding is consistent with the behavioral assumption that travelers may respond to environmental features closer to their residence more strongly than to more distant environmental qualities.close0

Making Strides: State of the Practice of Pedestrian Forecasting in Regional Travel Models

Much has changed in the 30 years since non-motorized modes were first included in regional travel demand models. As interest in understanding behavioral influences on walking and policies requiring estimates of walking activity increase, it is important to consider how pedestrian travel is modeled at a regional level. This paper evaluates the state of the practice of modeling walk trips among the largest 48 metropolitan planning organizations (MPOs) and assesses changes made over the last 5 years. By reviewing model documentation and responses to a survey of MPO modelers, this paper summarizes current practices, describes six pedestrian modeling frameworks, and identifies trends. Three-quarters (75%) of large MPOs now model non-motorized travel, and over two-thirds (69%) of those MPOs distinguish walking from bicycling; these percentages are up from nearly two-thirds (63%) and one-half (47%), respectively, in 2012. This change corresponds with an increase in the deployment of activity-based models, which offer the opportunity to enhance pedestrian modeling techniques. The biggest barrier to more sophisticated models remains a lack of travel survey data on walking behavior, yet some MPOs are starting to overcome this challenge by oversampling potential active travelers. Decision-makers are becoming more interested in analyzing walking and using estimates of walking activity that are output from models for various planning applications. As the practice continues to mature, the near future will likely see smaller-scale measures of the pedestrian environment, more detailed zonal and network structures, and possibly even an operational model of pedestrian route choice

Adjusting ITE’s Trip Generation Handbook for urban context

This study examines the ways in which urban context affects vehicle trip generation rates across three land uses. An intercept travel survey was administered at 78 establishments (high-turnover restaurants, convenience markets, and drinking places) in the Portland, Oregon, region during 2011. This approach was developed to adjust the Institute of Transportation Engineers (ITE) Trip Generation Handbook vehicle trip rates based on built environment characteristics where the establishments were located. A number of policy-relevant built environment measures were used to estimate a set of nine models predicting an adjustment to ITE trip rates. Each model was estimated as a single measure: activity density, number of transit corridors, number of high-frequency bus lines, employment density, lot coverage, length of bicycle facilities, presence of rail transit, retail and service employment index, and intersection density. All of these models perform similarly (Adj. R2 0.76-0.77) in estimating trip rate adjustments. Data from 34 additional sites were collected to verify the adjustments. For convenience markets and drinking places, the adjustment models were an improvement to the ITE’s handbook method, while adjustments for restaurants tended to perform similarly to those from ITE’s estimation. The approach here is useful in guiding plans and policies for a short-term improvement to the ITE’s Trip Generation Handbook. The measures are useful for communities seeking to develop local adjustments to vehicle trip rate estimates, and all could be calculated from spatial data available in most locations. The paper concludes with a discussion on what long-term improvements to the ITE’s Trip Generation Handbook might entail, with further implications in planning and practice

Development of a Pedestrian Demand Estimation Tool: a Destination Choice Model

There is growing support for improvements to the quality of the walking environment, including more investments to promote pedestrian travel. Planners, engineers, and others seek improved tools to estimate pedestrian demand that are sensitive to environmental and demographic factors at the appropriate scale in order to aid policy-relevant issues like air quality, public health, and smart allocation of infrastructure and other resources. Further, in the travel demand forecasting realm, tools of this kind are difficult to implement due to the use of spatial scales of analysis that are oriented towards motorized modes, vast data requirements, and computer processing limitations. To address these issues, a two-phase project between Portland State University and Oregon Metro is underway to develop a robust pedestrian planning method for use in regional travel demand models. The first phase, completed in 2013, utilizes a tool that predicts the number of walking trips generated with spatial acuity, based on a new measure of the pedestrian environment and a micro-level unit of analysis. Currently, phase two is building upon this tool to predict the distribution of walking trips, connecting the origins predicted in phase one to destinations. This presentation will focus on phase two, which is one of the first studies to focus on destination choices among pedestrians separately from other modes. The approach can be extended to identify the spatial extent of potential pedestrian paths to these destinations. Ultimately, the products developed from the research can estimate various aspects of pedestrian demand – trip generation, trip distribution, and areas of potential pedestrian activity. These tools will add to the analytical methods available for transportation modeling, pedestrian and safety analysis, health assessments, and other pedestrian planning applications