published_or_final_version / abstract / toc / Transport Policy and Planning / Master / Master of Arts in Transport Policy and Planning

published_or_final_version / abstract / Urban Planning / Master / Master of Science in Urban Planning

The purpose of this thesis is to explore bicycle use and attitudes towards cycling through case study analyses in Halifax Regional Municipality and the Region of Waterloo. There are two main sections of analyses; the first investigates factors that have been shown by previous research to be associated with cycling behavior for each of the study areas, and the second focuses on the results of a bicycle survey administered for the purpose of this research. The statistical analysis in Part 1 applies Fisher’s Exact Test to reveal statistically significant associations in the survey data. These two sections of analysis are compared and the following conclusions offered: 1. Cycling use is likely associated with city size, density, weather, topography, age, and gender. 2. Cycling trip purpose in Halifax is associated with weather; in Waterloo, trip purpose is associated with weather, gender, and employment. 3. Cycling use in Waterloo is associated with weather, age, gender, employment, and income. 4. There is strong evidence that the provision of bicycle infrastructure has a strong association with bicycle use. In the context of increasing bicycle use, the principal finding is the association between the provision of bicycle infrastructure and increased cycling use. In Waterloo, where the rate of cycling use is higher than in Halifax, there is approximately twice the total number of kilometres of on-street bicycle routes and respondents reported living significantly closer to bike paths, lanes, or trails. In Halifax, where cycling use is less common, respondents expressed much more concern regarding inadequate cycling infrastructure and an overall dissatisfaction with the quality of cycling facilities. These findings reaffirm the previous research suggesting that the provision of more bicycle lanes, paths, route signage, and parking facilities is associated with higher rates of bicycle use among the general public.

Many cities in North America have stated goals in their Official Plans, Transportation Plans, and other municipal documents related to cycling. A common objective is to increase the number and proportion of cyclists for either utilitarian or both utilitarian and recreational trips. To determine whether they are progressing towards achieving their goals, it is necessary that cities periodically and accurately monitor and measure their levels of cycling. This thesis aims to assess the different methods used for monitoring cycling in Canadian cities, as well as individual cities’ overall monitoring programs. The advantages and disadvantages of different methodologies and technologies are discussed, and best practices are provided. Four case study cities: Vancouver, Halifax, Calgary and Toronto are assessed according to a list of best practices developed by Hudson et al. (2010). Themes and patterns emerge and the cities are compared and contrasted. A summary of Canadian cities’ efforts is presented and the cities are ranked in the following order: #1 Vancouver; #2 Toronto; #3 Calgary; and #4 Halifax. In addition, the results of two surveys from the Greater Toronto and Hamilton Area are compared at the census tract (CT) level to assess their reliability. The Bicycling Share of Work Trips (BSWT) from the Transportation Tomorrow Survey (TTS) and Statistics Canada’s Canadian Census (the Census) is examined to identify whether research from different sources is producing the same results. Geographic Information Systems are used to examine and compare the spatial patterns of the survey results and descriptive statistics are used to quantify the differences. It was found that the surveys are producing significantly different results and that there appears to be little spatial pattern in the difference between them. This research allows Canadian cities and other interested parties to learn about the various methods for monitoring cycling, to see which methods are being used in Canadian cities, to decide which methods are best for their specific needs, and to more comprehensively understand the BSWT from the Census and the TTS.

Thesis (M. Plan.)--University of Adelaide, 1988. / Includes bibliographical references (leaves 213-224).

Thesis (M.S.)--University of Wisconsin--Madison, 1969. / Title from title screen (viewed Nov. 6, 2007). Includes bibliographical references. Online version of the print original.

Thesis (M.S.)--University of Wisconsin--Madison, 1969. / Includes bibliographical references.

Non-motorized (i.e., bicycle and pedestrian) traffic patterns are an understudied but important part of transportation systems. A key need for transportation planners is traffic monitoring programs similar to motorized traffic. Count campaigns can help estimate mode choice, measure infrastructure performance, track changes in volume, prioritize projects, analyze travel patterns (e.g., annual average daily traffic [AADT] and miles traveled [MT]), and conduct safety analysis (e.g., crash, injury and collision). However, unlike for motorized traffic, non-motorized traffic has not been comprehensively monitored in communities throughout the U.S. and is generally performed in an ad hoc fashion. My thesis explores how to (1) best count bicycles and pedestrians on the entire transportation network, rather than only focus on off-street trail systems or specific transportation corridors and (2) estimate AADT of bicycles and pedestrians in a small college town (i.e., Blacksburg, VA). I used a previously developed count campaign in Blacksburg, VA to collect bicycle and pedestrian counts using existing monitoring technologies (e.g., pneumatic tubes, passive infrared, and RadioBeam). I then summarized those counts to (1) identify seasonal, daily, and hourly patterns of non-motorized traffic and (2) develop scaling factors (analogous to those used in motor vehicle count programs) derived from the continuous reference sites to estimate long-term averages (i.e., AADT) for short-duration count sites. I collected ~40,000 hours of bicycle and pedestrian counts from early September 2014 to January 2016. The count campaign included 4 continuous reference sites (~ full year-2015 counts) and 97 short-duration sites (≥ 1-week counts) that covered different road and trail types (i.e., major road, local road, and off-street trails). I used 25 commercially available counters (i.e., 12 MetroCount MC 5600 Vehicle Classifier System [pneumatic tube counters], 10 Eco-counter 'Pyro' [passive infrared counters], and 3 Chambers RadioBeam Bicycle-People Counter [radiobeam counters]) to conduct the traffic count campaign. Three MetroCount, 4 Eco-counter, and 1 RadioBeam counter were installed at the 4 continuous reference sites; the remaining counters were rotated on a weekly basis at the short-duration count sites. I validated automated counts with field-based manual counts for all counters (210 total hours of validation counts). The validation counts were used to adjust automated counts due to systematic counter errors (e.g., occlusion) by developing correction equations for each type of counter. All automated counters were well correlated with the manual counts (MetroCount R2 [absolute error]: 0.90 [38%]; Eco-counter: 0.97 [24%]; RadioBeam bicycle: 0.92 [19%], RadioBeam pedestrian: 0.92 [22%]). I compared three bicycle-based classification schemes provided by MetroCount (i.e., ARX Cycle, BOCO and Bicycle 15). Based on the validation counts the BOCO (Boulder County, CO) classification scheme (hourly counts) had similar R2 using a polynomial correction equation (0.898) as compared to ARX Cycle (0.895) and Bicycle 15 (0.897). Using a linear fit, the slope was smallest for BOCO (1.26) as compared to ARX Cycle (1.29) and Bicycle 15 (1.31). Therefore, I used the BOCO classification scheme to adjust the automated hourly bicycle counts from MetroCount. To ensure a valid count dataset was used for further analysis, I conducted quality assurance and quality control (QA/QC) protocols to the raw dataset. Overall, the continuous reference sites demonstrated good temporal coverage during the period the counters were deployed (bicycles: 96%; pedestrians: 87%) and for the calendar year-2015 (bicycles: 75%; pedestrians: 87%). For short-duration sites, 98% and 94% of sites had at least 7 days of monitoring for bicycles and pedestrians, respectively; no sites experienced 5 days or less of counts. I analyzed the traffic patterns and estimated AADT for all monitoring sites. I calculated average daily traffic, mode share, weekend to weekday ratio and hourly traffic curves to assess monthly, daily, and hourly patterns of bicycle and pedestrian traffic at the continuous reference sites. I then classified short-duration count sites into factor groups (i.e., commute [28%], recreation [11%], and mixed [61%]). These factor groups are normally used for corresponding continuous reference sites with the same patterns to apply scaling factors. However, due to limitations of the number (n=4) of continuous reference sites, the factor groups were only used as supplemental information in this analysis. To impute missing days at the 4 continuous reference sites to build a full year-2015 (i.e., 365 days) dataset, I built 8 site-specific negative binomial regression models (4 for bicycles and 4 for pedestrians) using temporal and weather variables (i.e., daily max temperature, daily temperature variation compared to the normal 30-year averages [1980-2010], precipitation, wind speed, weekend, and university in session). In general, the goodness-of-fit for the models was better for the bicycle traffic models (validation R2 = ~0.70) as compared to the pedestrian traffic models (validation R2 = ~0.30). The selected variables were correlated with bicycle and pedestrian traffic and cyclists are more sensitive to weather conditions than pedestrians. Adding model-generated estimates of missing days into the existing observed reference site counts allowed for calculating AADT for each continuous reference site (bicycles volumes ranged from 21 to 179; pedestrian volumes ranged from 98 to 4,232). Since a full year-2015 dataset was not available at the short-duration sites, I developed day-of-year scaling factors from the 4 continuous reference sites to apply to the short-duration counts. The scaling factors were used to estimate site-specific AADT for each day of the short-duration count sites (~7 days of counts per location). I explored the spatial relationships among bicycle and pedestrian AADT, road and trail types, and bike facility (i.e., bike lane). The results indicated that bicycle AADT is significantly higher (p < 0.01) on roads with a bike lane (mean: 72) as compared to roads without (mean: 30); bicycle AADT is significantly higher (p < 0.01) on off-street trails (mean: 72) as compared to major roads (mean: 33). Pedestrian AADT is significantly higher (p < 0.01) on local roads (mean: 693) as compared to off-street trails (mean: 111); this finding is likely owing to the fact that most roads on the Virginia Tech campus are classified as local roads. In Chapter 5, I conclude with (1) recommendations for implementation (e.g., counter installation and data analysis), (2) key findings of bicycle and pedestrian traffic analysis in Blacksburg and (3) strengths, limitations, and directions for future research. This research has the potential to influence urban planning; for example, offering guidance on developing routine non-motorized traffic monitoring, estimating bicycle and pedestrian AADT, prioritizing projects and measuring performance. However, this work could be expanded in several ways; for example, deploying more continuous reference sites, exploring ways to monitor or estimate pedestrians where no sidewalks exist and incorporating other spatial variables (e.g., land use variables) to study pedestrian volumes in future research. The overarching goal of my research is to yield guidance for jurisdictions that seek to implement systematic bicycle and pedestrian monitoring campaigns and to help decision making to encourage healthy, safe, and harmonious communities. / Master of Urban and Regional Planning

Expansive parking lots, miles of asphalt, and traffic jams: this is what the modern sport stadia has come to represent. Does it have to be this way? What does the future of sports stadia hold? Can we build a stadium that is better integrated to the community around it? The stadium must become a major urban element again and it must engage the urban context. D.C. United, the most storied franchise in MLS history, needs a new home. Baltimore and other locations in Maryland would gladly welcome the Black-and-Red, but it is vital for them to remain within Washington, D.C. in a soccer specific stadium. An area of land on Buzzard Point has already been chosen for the future development of a new soccer specific stadium and is now waiting for city council approval. This thesis aims to explore a new type of urban stadium and a new stadium type as a bicycle destination at Buzzard Point. To explore a new type of urban stadium, it is vital to investigate the site's present features as well as investigate the projected future infrastructure development and real estate growth on the site. These future developments must remain throughout the design process because they will one day make up the stadium's urban context. / Master of Architecture

Master of Regional and Community Planning / Department of Architecture / Jason Brody / This report examines the use of bicycling as a transportation alternative to the personal automobile in the United States. It begins with a review of historical trends that caused Americans to move away from bicycling for transportation and choosing to adopt automobiles as the primary mode of transportation. A review of articles, reports, and studies is used to consider the benefits connected with utilitarian cycling and electing to bicycle for transportation. The report focuses on three prominent barriers that affect an individual‟s decision to bicycle: bicycle safety, bicycle consciousness, and bicycle infrastructure. The study discusses how these three obstacles are considerable factors affecting bicycling. The study also discusses a number of exemplary solutions for overcoming these barriers that have been implemented in bicycle-friendly cities in the United States. An analysis of plans and policies for the bicycle-friendly cities of Portland, Oregon and Davis, California is used to determine what historical actions have led to a more complete bicycle network in these two cities which have elected to promote bicycling. An in-depth evaluation of Boulder, Colorado, provides insight for specific plans that have been adopted and strategies that have proven to be successful in improving bicycling for transportation. The report attempts to demonstrate that bicycling can be made a viable means of transportation in United States‟ communities by adopting comprehensive plans and policies that address the challenges of bicycle safety, bicycle consciousness, and bicycle infrastructure simultaneously.