How can redesigning the local transportation system  reduce automobile dependence at OSA? 

 

 

 

 

 

 

 

An International Baccalaureate Extended Essay in Design Technology 

 

Candidate Name: Keita Hill

Candidate Number:

Supervisor Name: Mr. Ho / Mr. Karas

Session: May 2010

Word Count: 3981

School: Old Scona Academic High School

 

Abstract    

This paper investigates the research question, “How can redesigning the local

transportation system reduce automobile dependence at Old Scona Academic High School

(OSA)?” The approach is a case study into the factors that cause automobile dependence within

the scope of the local youth demographic attending Old Scona Academic Senior High School in

Edmonton, Alberta, Canada.

This paper investigates the research question, “How can redesigning the local

transportation system reduce automobile dependence at Old Scona Academic High School

(OSA)?” The approach is a case study into the factors that cause automobile dependence within

the scope of the local youth demographic attending Old Scona Academic Senior High School in

Edmonton, Alberta, Canada.

An observational survey administered to 271 OSA students during June 2009 provides

the data for this study. The sample represents approximately 80% of the school population, with

representation from all grade levels.

An observational survey administered to 271 OSA students during June 2009 provides

the data for this study. The sample represents approximately 80% of the school population, with

representation from all grade levels.

After analyzing the results and determining a model for transportation decision making at

OSA, this paper concludes that any transportation system in which users feel the necessity to

own a car will consequently have a high level of automobile dependence. To avoid this problem,

many improvements are needed, primarily centered on improving the convenience, timeliness,

and convenience of sustainable modes of transport. Finally, this study concludes that redesign of

the transportation network must be accompanied by education of the public into the benefits of

the new system, to make currently automobile dependent commuters aware of their alternatives.

After analyzing the results and determining a model for transportation decision making at

OSA, this paper concludes that any transportation system in which users feel the necessity to

own a car will consequently have a high level of automobile dependence. To avoid this problem,

many improvements are needed, primarily centered on improving the convenience, timeliness,

and convenience of sustainable modes of transport. Finally, this study concludes that redesign of

the transportation network must be accompanied by education of the public into the benefits of

the new system, to make currently automobile dependent commuters aware of their alternatives.

184 Words 184 Words

 

Table of Contents        Introduction........................................................................................................................ Page 10 Introduction........................................................................................................................ Page 10 Procedure............................................................................................................................ Page 30 Procedure............................................................................................................................ Page 30 Design...................................................................................................................... Page 30 Design...................................................................................................................... Page 30 Administration ....................................................................................................... Page 40 Administration ....................................................................................................... Page 40 Analysis ............................................................................................................................... Page 50 Analysis ............................................................................................................................... Page 50 Modal Choice.......................................................................................................... Page 50 Modal Choice.......................................................................................................... Page 50 Time of Travel ........................................................................................................ Page 11 Time of Travel ........................................................................................................ Page 11 A Transportation Decision-Making Model ......................................................... Page 13 A Transportation Decision-Making Model ......................................................... Page 13 Recommendations .................................................................................................. Page 19 Recommendations .................................................................................................. Page 19 Evaluation........................................................................................................................... Page 28 Evaluation........................................................................................................................... Page 28 Conclusion .......................................................................................................................... Page 29 Conclusion .......................................................................................................................... Page 29 List of References............................................................................................................... Page 31 List of References............................................................................................................... Page 31 Appendices.......................................................................................................................... Page 32 Appendices.......................................................................................................................... Page 32 Appendix I. Annotated Survey ............................................................................. Page 32 Appendix I. Annotated Survey ............................................................................. Page 32 Appendix II. Data Tables from the Survey ......................................................... Page 37 Appendix II. Data Tables from the Survey ......................................................... Page 37  

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Introduction    

While the twentieth century saw the rise of the gasoline-powered passenger car, the

twenty-first century will inevitably see its gradual replacement with sustainable modes of

transportation. These modes – notably public transit, walking and cycling – promise to reduce

the pressing environmental and social problems associated with automobile dependence. They

move people in less space, encourage physical activity, and reduce the need for carbon-based

energy, making them attractive choices for urban transportation design. An increasing number of

cities with traffic problems are turning away from costly road expansion and instead attempting a

“modal shift” to sustainable transportation.

Unfortunately, this modal shift is not easy. Automobile dependence is “set firmly in place

by low density suburbia and a car-oriented culture” (Newman and Kenworthy, 1991). Since air

pollution and infrastructure maintenance costs are negative externalities not paid for by the

driver, little economic incentive exists to change. Furthermore, people who already own and pay

for upkeep of a car are the least likely to switch to sustainable modes of transportation.

Any redesign of transportation systems must therefore consider youth, since they have

not yet invested in a car and so have the greatest economic incentive to adopt a car-free lifestyle.

If public transportation, cycling, and walking were appealing to youth, and continued to be

appealing at later ages, a gradual generational decline in car use would result. Over time, this

process would allow automobile dependent cities to become more sustainable.

Edmonton, located in central Alberta, Canada, is the most automobile-dependent major

urban region in Canada (Iveson, 2008). With a municipal population of 782,439 in 2009,

Edmonton’s transportation system was ranked (Coyne, 2009) as 27th out of 31 major Canadian

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cities on criteria of effectiveness, cost, and

efficiency. Despite these major problems,

Edmonton's municipal government has

recognized the necessity of a modal shift

to sustainable transport. The question is

how to best encourage a city-wide modal

shift amongst tight budget restrictions.

To this end, this case study

investigates the research question, "How

can redesigning the local transportation

system reduce automobile dependence at

Old Scona Academic High School

(OSA)?" As a borderless school of 355 students, OSA draws students from throughout the city to

its central location, allowing for analysis of youth transportation choices throughout the city. The

results of this study provide insight into effective design of a sustainable transportation system

for the local youth demographic.

 

Location of Edmonton, Alberta, Canada               

Map 1. The yellow star indicates the location of Edmonton within Canada (shaded green).   Modified from: http://en.wikipedia.org/wiki/File:Canada_(orthographic_projection).svg 

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Procedure      

Design Design   

Full realization of redesigning the transportation system was not feasible, so I developed

an observational survey (Appendix I) to collect the following data: (1) demographics; (2) current

transportation trends for time of travel and (3) mode of transport; (4) factors effecting modal

choice; and (5) specific transportation-related preferences. An optional (6) open-ended written

response question was also included.

Full realization of redesigning the transportation system was not feasible, so I developed

an observational survey (Appendix I) to collect the following data: (1) demographics; (2) current

transportation trends for time of travel and (3) mode of transport; (4) factors effecting modal

choice; and (5) specific transportation-related preferences. An optional (6) open-ended written

response question was also included.

Each group of questions was designed to address a different aspect of the design cycle.

The table below outlines what aspects I considered in writing each set of questions.

Each group of questions was designed to address a different aspect of the design cycle.

The table below outlines what aspects I considered in writing each set of questions.

Stage of Design Cycle Stage of Design Cycle   

Approach Approach 

1. Identifying or clarifying a need or opportunity 

‐ Background research provides insight into the reasons why automobile dependence is undesirable. ‐ Results from (3) identify the current level of automobile dependence at OSA.  

2. Analyzing, researching and specifying requirements 

‐ Results from (4) identify the needs of currently automobile dependent students to change, as well as the needs of current sustainable transport users to continue using these modes. ‐ Research into city policy provides further refinement of local requirements.  

3. Generating ideas and solutions 

‐ Background research provided potential solutions that have been successful in other cities, or that already exist as pilot projects in Edmonton. ‐ Responses to (6) provide further solutions from survey participants.  

4. Developing the chosen solution 

‐ Not directly addressed 

 

4   

 

 5. Realizing the chosen solution  

‐ Not directly addressed 

6. Testing and evaluating the chosen solution 

‐ Responses to (5) provide student evaluation of proposed solutions. ‐ Results from (1) identify of the limitations to the findings of this survey and the associated bias of the sample.  

Reference: “Diploma Programme Design technology—guide First examinations 2009”   

Administration  

The survey was administered to 271 OSA students during math classes in June 2009.

Students were asked to consider their year-long commute, so that results would be representative

of trips made over the entire school year. Since students use computers regularly, the online

medium did not present any accessibility problems. Students who were not present or who were

not registered in math were not included in the sample (approximately 80 students).

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Analysis   

Modal Choice  

Modal choice data was collected through a question series asking how often the

respondent used each mode of transportation to commute to OSA. Since the response choices

were “never”, “rarely”, “half the time”, “often”, and “always”, I first needed to develop a method

to convert these descriptive responses to quantitative data.

The model I developed is based on the simplest case possible: a student who uses only

one mode of transportation to commute to OSA. A single student commuting to OSA for one

year, always by one mode of transportation, makes one “student-year-trip” in that mode. The

assumption of this standard of comparison is that all students commute to the same number of

instructional days. With this assumption, two students who commute to school by the same mode

“half the time” would together make one student-year-trip in that mode.

Mathematically, this model is expressed by multiplying the total number of each type of

response by a conversion factor relative to 1.00 for “always”. For example, “half the time” is

approximated as 0.50, since a student making half of her commutes over the school year by a

given mode will make approximately 0.5 student-year-trips in that mode. From this model, I

developed the following equation:

 

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R = (N“never”)*(0.00) +(N“rarely”)*(0.25) +(N“half the time”)*(0.50) +(N“often”)*(0.75) +(N“always”)*(1.00)  Equation 1. Where R = student‐year‐trips and N = number of responses. The conversion factors used are: 0.00 for “never”, 0.25 for “rarely”, 0.50 for “half the time”, 0.75 for “often”, and 1.00 for “always”. 

 I considered the terms “never”, “half the time” and “always” to be absolute, with “rarely”

and “often” as the sources for error. For example, the conversion factor for “rarely” could be any

value between “never” at 0.00 and “half the time” at 0.50. To account for this uncertainty, I

developed the following formula:

 

  

 Here is a sample R calculation, with uncertainty, for car passenger:

 

 

R“car” = (23)*(0.00) +(61)*(0.25) +(56)*(0.50) +(57)*(0.75) +(75)*(1.00)  R“car” = 161.00 ± 28.32 student-year-trips 

2 R = (61)*(0.49)+(57)*(0.99) -(61)*(0.01)-(57)*(0.51)  

R = 28.32 

2 R = (N“rarely”)*(0.49)+(N“often”)*(0.99) -(N“rarely”)*(0.01)-(N“often”)*(0.51) Equation 2. Generally, uncertainty can be calculated from (maximum‐minimum)/2. In this case, the maximum possible value for a given R occurs when all survey participants interpreted “rarely” as a value just under 0.50 (half the time) and “often” as a value just under 1.00 (always). Conversely, the minimum possible value occurs at the corresponding minimum interpretations. In this equation, 0.49 and 0.99 are used as the maximum conversion factors, and 0.01 and 0.51 are used as the minimum conversion factors.  

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Calculating R for each mode using the same method yields the following data:

  

 

Modal Share of Trips to OSA – Student‐year‐trips and % of Total Trips, by mode 

Mode of Transport  Student‐year‐trips (R)  % of Total Bike  14.75 ± 3.12  4.6 ± 1.7 % Car Passenger  161.00 ± 28.32  46.8 ± 9.8 % Car Driver  20.25 ± 4.56  6.2 ± 2.3 % Public Transit  131.25 ± 25.20  38.4 ± 9.3 % Taxi  6.50 ± 3.84  2.1 ± 1.5 % Walking  12.50 ± 3.36  8.9 ± 3.0 % TOTAL  346.25 ± 68.4  107 ± 27.6 % 

 Finally, comparing the 2009 OSA results to the City of Edmonton High School average

from 2005 provides the following graph:

 

 

Percentage of Trips by Mode ‐ OSA compared to the Edmonton High School Average

0

10

20

30

40

50

60

Bike CarPassenger

Car Driver PublicTransit

Taxi Walking School Bus

OSA

Percen

tage of T

rips (%

) 

Edmonton High Schools

* indicates that no data was available.  

*

Mode of Transport

Edmonton High Schools Data Source: “2005 Household Travel Survey”, Published May 2006 by the City of Edmonton Transportation Department (Note: In this survey, “bicycle” was used instead of “bike”, “transit” was used instead of “public transit”, and “walk” was used instead of “walking”.) 

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When the data from the City of Edmonton is compared to the OSA survey results, the

same general trends are evident. In both surveys, public transit and car passenger comprise the

majority of trips, with a relatively small use of active modes (walking and bicycling).

Notable differences include OSA’s somewhat higher level of automobile dependence

compared to the Edmonton average, and proportionately lower use of public transit. OSA also

has a slightly higher use of the active modes, especially bicycling.

Since detailed survey data is not available for other Edmonton high schools, only

speculations can be made as to the causes for these discrepancies. However, OSA’s open border

policy on enrolment is likely related to the high level of automobile dependence. Unlike many

Edmonton high schools, which draw students from their local areas, most OSA students

commute longer distances. When the city is split into 7 geographic zones (see map 2, following

page), each with roughly the same total population (except for “Outside Edmonton”), the OSA

population is distributed as follows:

OSA Population, by region

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Map 2. The 7 geographic zones used for analysis. I modified this map from “City of Edmonton Wards” map produced for the City of Edmonton Planning and Development Branch by The Cartographic Group. 

Only 6% of OSA students commute to the school from the central area. The remaining

94% of trips are over 2.5 km in length, a distance too long for convenient walking, especially

when carrying heavy loads of school materials. When the modal choice data is split by

geographic zone, the correlation is obvious: the percentage of trips made by walking in the

central area is more than double the average. (See graph, following page.)

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0

10

20

30

40

50

60

70

West North-West North-East Central South-West

South-East OutsideEdmonton

Percentage of Trips by Mode of Transport at OSA, by region Pe

rcen

tage of T

rips (%

) 

Region

BikeCar PassengerCar DriverPublic TransitTaxiWalking

Limiting enrolment to the local area is not feasible because this would defeat the purpose

a designated academic high school. Instead, this data confirms the benefit of densifying the urban

form of the city, thereby reducing trip distances. The strong correlation between the short trip

distances in the central region and higher use of sustainable modes suggests that a more compact

city would have lower automobile dependency. A broad vision to increase population density has

already been recognized by the city government, so the correlation found in this case study

confirms the validity of this strategic goal within the youth user group at OSA.

Across the geographic regions, the modal choice data reveals public transit as the most

accepted sustainable mode, with a much lower uptake of active modes. One student from South-

West Edmonton expressed that “it would take years to walk/bike to school,” reflecting the

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perception of many that distances are too long to commute by active transport. While this

perception is true for walking, many of the medium-length trips in the 3 to 8 kilometer range

could be covered by bicycle in less than 30 minutes. Thus, changing user perceptions about

cycling could substantially increase its use, a possibility further explored under the section titled

“Recommendations”.

Time of Travel   The survey confirms that OSA has two rush hour periods: 7:00 a.m. to 8:00 a.m., and

3:00 p.m. to 4:00 p.m. In both cases, generated traffic peaks sharply, but occurs before the peak

of city rush hour.

Because the majority of traffic is generated within these short time frames, localized

traffic congestion becomes an inconvenience as well as a safety problem. As one survey

respondent commented, there are “so many people” waiting for buses at the end of the school

day that boarding becomes inefficient “because the driver has to see every individual pass, or

give transfers, etc.” As will be discussed later, time taken for travel is major factor when OSA

students make transportation decisions, so delays in bus service would likely deter its use.

However, apart from localized congestion, the survey results suggest that traffic

conditions during OSA students’ commutes are generally good. Compared to the hourly city

traffic volumes, OSA students are traveling during the off-peak to beginning-of-peak hours,

when traffic congestion is less. As well, since infrastructure such as bus lanes, separated LRT

right-of-ways, and express service is most helpful during the rush hour, most OSA students are

commuting during periods when these time-saving mechanisms on public transit make less of a

difference. One student from South-West Edmonton commented that “the time to take public

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transit is about 5-6 times longer than [traveling] by car,” revealing the substantial time incentive

associated with driving. The contrast of an inefficient transit network compared to an effective

road network during the hours of travel reduces the incentive to take transit.

Percentage of Trips by Hour of Day – OSA compared to the Edmonton Average

0

5

10

15

20

25

30

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Percen

tage of T

rips (%

) 

Hour of Day – Lower Bound

Edmonton (River Screenline) Data Source: “2007 Traffic Flow Map”, Published May 2008 by the City of Edmonton Transportation Department 

 

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A Transportation Decision­Making Model   

The data about current transportation trends confirms that OSA has a high level of

automobile dependence, and that this dependence is related to the long distances to the school –

both perceived and real. To make any change to the present circumstances requires a thorough

understanding of the transportation decision-making model used by OSA students.

To develop such a model, I designed a series of survey questions of the form, “In

deciding how to commute to OSA, rank the importance you (personally) assign to…”, followed

by a list of factors. Respondents were asked to provide a ranking on a scale of 1 to 5 for each

factor, with 5 being the most important. The responses were more or less normally distributed in

each case, showing a substantial degree of consensus on the relative importance of each of the

factors. The data shows three main types of distributions: those factors with the statistical mode

at 1 or 2, those with the statistical mode at 4 or 5, and those with a statistical median of 3. I

interpreted the three classes of distributions as illustrated below:

Type 1: Mode at 1 or 2  Type 3: Median at 3

“Not Important”  “Very Important” “Somewhat Important”

Type 2: Mode at 4 or 5

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The following table shows the relative importance of the factors from the survey,

classified in this manner:

“In deciding how to commute to OSA, rank the importance you (personally) assign to…” 

Not Important  Somewhat Important  Very Important ‐ Social Acceptability (being cool) ‐ Enjoyment of the travel (scenery, exhilaration, etc.)  

‐ Privacy ‐ Freedom while travelling (to eat, drink, talk, use portable technology, listen to music, etc.) ‐ Environmental Impacts 

‐ Time Taken ‐ Reliability ‐ Safety ‐ Cost ‐ Comfort 

While most of these findings are not surprising, the placement of social acceptability as a

factor of low importance clashes with prior research by Nordahl (2008) in which he found that

“public transit is often scorned and considered ‘un-cool’ by teenagers.” At least in this local

survey (of math students at an academic school), utility far outweighs social acceptability in

transportation decisions.

To ensure that student responses actually reflect how transportation decisions are made, I

also included the question, “Who decides how you commute to OSA?” Fully 81% of students

responded that they made the decision (either with their parents or on their own), confirming that

student’s opinions have a strong bearing on the actual decision-making process.

Perhaps more than any other factor, a person’s familiarity and comfort with a mode affect

transportation choices. To discover what impact this might have on the local transportation

decisions, I included the question, “Which of the following modes of transportation are you most

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accustomed to?” The graph below shows the results, when converted to percent and compared to

the actual modal share of each mode.

% Modal Share and % Confidence in using mode at OSA, by mode of transportation

Not surprisingly, there is a very strong correlation between the comfort level with each

mode and the percentage of students using it to commute to school. The relationship is probably

causal and circular; students are most likely to use modes of transport they are comfortable with,

and in so doing become increasingly confident in using those modes of transportation. Notably,

biking and walking have higher percentage confidence of use than the actual modal share, while

car passenger and public transit have lower percentage confidence of use than modal share. This

Percen

tage (%

) 

Mode of Transport

0

10

20

30

40

50

60

Bike Car Passenger Car Driver Public Transit Taxi Walking

Note: Respondents were able to select more than one response for the mode that they were most comfortable using.

16 

demonstrates there are more students who would be willing and comfortable to walk or bike to

school, but whose needs are not being met by the local transportation network. These students

are instead forced to use the other modes, such as car passenger and public transit. This

observation also related to the general perception that trip distances to OSA are too long for

walking or cycling. Evidently, there are students who are comfortable using these modes when

commuting to other—probably closer—destinations, but who are not able to use these modes to

commute to OSA. This suggests a lack of good cycling and walking facilities connecting their

neighborhoods to OSA.

Even if the sustainable transportation system was the meet the needs of each user group

perfectly, some people would delay making a change, simply because of habit. To address this

possibility, I asked the question, “In general, how willing are you to make changes to your

current transportation choices?” The results showed the following distribution:

“In general, how willing are you to make changes to your current transportation choices?”

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140

1 – Very reluctant 2 3 4 5 – Very willing

Num

ber of Respo

nses (#

) 

Response

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This nearly normal

distribution suggests that the

transit decision making model is

much like the uptake curve of

new technology, as first modeled

by Everett Rogers in 1962. The

transition to sustainable

transportation is the gradual

conversion of segments of the

population, beginning with

“innovators” and “early adopters”. Judging by the high level of current automobile dependence

locally, Edmonton would be in the early days of making that transition. Like Roger’s technology

adoption lifecycle, the transition in Edmonton away from automobile dependence is likely to be

a slow process, with only small portions of the population making the transition at first.

Technology Adoption Lifecycle 

Figure 2. A graph of Everett Rogers’ Technology Adoption Lifecycle model.  Source: http://en.wikipedia.org/wiki/File:DiffusionOfInnovation.png 

Supporting this view, Domencich (1970), found that people rarely change their

transportation patterns except when these changes accompany other major lifestyle changes, such

as getting married or finding a new job. This explains the changing transportation patterns of

Edmonton students as they progress through the educational system and then into the workplace.

Since each new school setting (and finally the workplace) presents a lifestyle change, it is not

surprising that we should find substantial associated changes in transportation patterns. When the

modal choice data for Edmonton is plotted over this progression of stages through the

educational system, the period in which automobile dependence rises most markedly is the

transition from schools to the workplace. This is understandable, since students who are unhappy

18 

with a slow and unreliable local public transit system will likely buy cars as soon as possible. If

sustainable transit were to better accommodate the needs of high school students, it would not

only increase the number of students using sustainable modes during high school, but also

prevent a shift to automobile dependence afterwards. How to best meet these needs of students is

the focus of the next section.

Modal Share by School/Workplace in Edmonton

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40

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60

70

80

Elementary Junior High Senior High Post Secondary Work

Car Driver Car Passenger

 

 

Transit School Bus

Bicycle Walk

Data Source: “2005 Household Travel Survey”, Published May 2006 by the City of Edmonton Transportation Department 

 Destination

Percen

tage of T

rips (%

) 

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Recommendations   

There are thousands of specific

design improvements that have been

proposed to reduce automobile

dependence in cities. These range from the

general, such as developing more dense

urban centres, to the specific, such as the

“green wave” technology shown to the

right. The challenge is determining which

design improvements will have the

greatest impact for the least cost.

This section of the study suggests

which of these design improvements are

most effective towards increasing the use

of public transit, biking and walking. As

has been shown, a transportation network

that adequately fulfills the needs of the youth demographic will, over time, reduce the level of

local automobile dependence.

“Green Wave” Infrastructure in Denmark

Source: Making Cycling Irresistible (Pucher and Buehler, 2008)  Original Caption: Figure 16. Green wave for cyclists in Odense, Denmark. Bright green lights on the bollards along the path pulsate in a wave‐like forward motion guiding cyclists to the next green traffic signal at 20km/hr. If cyclists keep pace with the green wave, they get green traffic signals at all intersections. Source: Troels Andersen, City of Odense 

Most relevant to the redesign of Edmonton’s transportation network are the policy

recommendations outlined in the municipal Transportation Master Plan (TMP), a document

outlining the city’s strategic goals, many of which are interrelated to the reducing automobile

dependence. Such goals include, “shifting from an auto-oriented transportation system to a

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system offering citizens more choice of transportation modes”, “[encouraging] active

transportation,” and “diminished focus on catering to commuter traffic.” In this section, I will

evaluate the various existing policy suggestions, along with new recommendations found

through this survey.

General Recommendations

Because trip length and time taken are two leading factors leading to current automobile

dependence at OSA, approaches to reduce trip length through densification and mixed use

zoning are recommended:

• Integration between land use and transportation planning to ensure that

sustainable transit is built into neighborhoods rather than added afterward;

• Policies directed at limiting urban sprawl.

Public Transit - Specific Recommendations

Several conclusions about effective public transit design for the OSA demographic are

outlined on the following page.

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0

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Closer

bus/L

RT stop

s

Faster

servi

ce

Warm

er wea

ther

Cleane

r/new

er ve

hicles

Others

to tak

e tran

sit w

ith

Better

trip pl

annin

g too

ls

Impro

ved r

eliab

ility

Impro

ved s

afety

Higher

servi

ce fre

quen

cy

Fare re

ducti

ons /

Free tra

nsit

Other

“Which of the following changes would most encourage you to take public transit to OSA?”

Num

ber of Respo

nses (#

) 

Note: Respondents were able to select up to three responses.

22 

According to the data, providing

faster service, higher service frequency

and improved reliability are the most

expedient improvements. While fare

reductions, free transit and closer

bus/LRT stops are also suggested, they

conflict with the most requested changes

in the network. Instead of providing

reduced fares, increasing service quality will show a greater increase in ridership. Similarly,

decreasing the distance between stops should be carefully balanced with the primary goal of

reducing trip times. If funds are available, the improvement of transit service by providing

cleaner and newer vehicles, better trip planning

tools, and improving safety will also show some

benefits.

“Are you more willing to travel by city bus or LRT?”

Existing and Planned LRT 

Source: Transportation Master Plan 

Within the OSA demographic, LRT is

somewhat more popular than city bus service,

though nearly half of users are equally willing

to travel by both modes.

To improve the reliability of public

transit and reduce the trip time, policy

objectives such as the following are therefore

recommended:

• Continuing expansion of the

23 

LRT network as outlined in the TMP;

• Maintaining the current distance between bus stops at approximately 400 metres;

• Ensuring that the cost of transit does not become a significant disincentive to use

by freezing fares at 2009 levels;

• Continuing to increase service frequency on both LRT and buses, as well as

increasing the overall number of bus routes, especially in South-West Edmonton

• Development of transit avenues

(where a minimum bus frequency

of 15 minutes is provided weekday

peak, and weekday, Saturday and

Sunday midday periods), including

along Whyte Avenue, which runs a

block south of OSA;

Source: Transportation Master Plan 

Proposed Transit Avenues

• Continuing to develop and expand

on-road infrastructure for buses,

including bus lanes;

• Integrating the bus and LRT

network more effectively.

24 

Bicycle - Specific Recommendations

The following graph shows the improvements suggested by the survey to increase bicycle

commuting:

Which of the following changes would most encourage you to bike to OSA? 

Num

ber of Respo

nses (#

) 

Note: Respondents were able to select up to three responses.

0

50

100

150

200

250

Better

lighti

ng

Shorte

r dist

ance

Warm

er wea

ther

Better

scen

ery

Others

to bik

e with

Bike M

aps /

Trip pl

annin

g too

ls

Impro

ved s

afety

More/be

tter r

oad f

acilit

ies

More/be

tter b

ike pa

rking

Having

an op

eratio

nal b

ikeOthe

r

Geographic conditions, specifically the perceptions that distances are too long and

weather too cold for biking, are identified as the main disincentives. However, given that trip

distances of 3 to 8 km are easily manageable for most people by bicycle, and that at least half of

the school year have temperatures sufficiently warm for cycling, both of these perceptions are

somewhat mistaken. Thus, while these geographic factors can not be changed, educating students

about the feasibility of cycling and how to ride safely on the road could substantially increase

25 

bicycle commuting. Education would simultaneously improve the safety of cycling, a third major

recommendation, since a cyclist must take much of the responsibility for his own safety on the

road.

Having “others to bike with” is also a major incentive to cycling, so schools as well as the

municipal government should continue to support community cycling programs. At OSA,

helping students create neighborhood cycling groups could substantially increase the use of this

mode in student commutes.

Improved road facilities are another major recommendation. When asked specifically

what types of road facilities are most useful, the responses were as follows:

Road Type  Percentage 

Bicycle paths and sidewalks shared with pedestrians (mixed‐use paths)  45% 

Bike‐only lanes alongside traffic  29% 

Residential roads shared with vehicles  16% 

Service roads or alleys  8% 

Bike lanes shared with buses/taxis  7% 

Major roads shared with vehicles  1% 

Road Infrastructure Preferences for Cycling to OSA 

From a municipal standpoint, this survey identifies the following recommendations to

increase the use of cycling in Edmonton:

• Assist schools to integrate cycling education, both about feasibility of cycling and

bicycle safety;

• Expand the mixed-use path network and bicycle-only lanes on major roads;

• Continue to improve bicycle parking and bicycle trip-planning tools.

26 

Walking - Specific Recommendations

The following graph shows the improvements suggested by the survey to increase

pedestrian commutes:

Which of the following changes would most encourage you to walk to OSA? 

Num

ber of Respo

nses (#

) 

Note: Respondents were able to select up to three responses.

0

50

100

150

200

250

300

Better

lighti

ng

Shorte

r dist

ance

Warm

er wea

ther

Better

scen

ery

Others

to walk

with

Walk

ing m

aps

Impro

ved s

afety

More/be

tter w

alking

facil

ities

As with cycling, trip distance and weather are the main barriers to students walking to

school. Both of these problems can not be addressed without significant changes to the urban

form of the city. However, one solution is to better integrate walking and public transit, by

reducing the walking portion of a trip to a manageable length.

27 

After geographic factors, having “others to walk with” and “improved safety” are the

main desired improvements. Since walking with others also affords improved safety, a “walking

school bus” could be used to encourage group walking.

Improved road facilities are less of a concern for walking, suggesting that adequate

facilities already exist. The road infrastructure preferences for walking were as follows:

Road Infrastructure Preferences for Walking to OSA 

Road Type  Percentage 

Sidewalks   49% 

Off‐road paths only for pedestrians   28% 

Off‐road paths shared with cyclists   18% 

Service roads or alleys  4% 

To increase the use of walking in Edmonton, policy objectives such as the following are

recommended:

• Assist schools in developing “walking school bus” programs;

• Continue to maintain the city-wide sidewalk and multiuse trail network;

28 

Evaluation    

There are several limitations of the data collected in this case study, most notably,

demographic biases:

There are several limitations of the data collected in this case study, most notably,

demographic biases:

• OSA is an unusual high school because it draws students from a wide geographic

range. Results from an open-border academic school can not necessarily be

extrapolated to all high schools in Edmonton.

• OSA is an unusual high school because it draws students from a wide geographic

range. Results from an open-border academic school can not necessarily be

extrapolated to all high schools in Edmonton.

• Only math students present in their classes were surveyed. While only a small

percentage of students do not take math classes, this may have resulted in

unintended bias.

• Only math students present in their classes were surveyed. While only a small

percentage of students do not take math classes, this may have resulted in

unintended bias.

• While students commute from all parts of the city, most students at OSA live in

the South-West region of the city.

• While students commute from all parts of the city, most students at OSA live in

the South-West region of the city.

• The survey sample included more females (59%) than males (41%). • The survey sample included more females (59%) than males (41%).

Missing data was not a major problem, because all questions except written response and

demographics-related items were mandatory. However, misinterpretation of survey questions,

incorrect/mistaken responses, or repeated submissions by the same respondent could have posed

undetected problems with the data.

Missing data was not a major problem, because all questions except written response and

demographics-related items were mandatory. However, misinterpretation of survey questions,

incorrect/mistaken responses, or repeated submissions by the same respondent could have posed

undetected problems with the data.

Overall, the collected data revealed substantial trends within the OSA student

demographic. The close correlation between the data from OSA and that found in previous

studies suggests a high level of validity.

Overall, the collected data revealed substantial trends within the OSA student

demographic. The close correlation between the data from OSA and that found in previous

studies suggests a high level of validity.

29 

Conclusion   In answer to the research question, “How can redesigning the transportation network

reduce automobile dependence at OSA,” a variety of possible improvements have been outlined

through the course of this essay. Most importantly, so long as the transportation system is

centered on the private vehicle, users will be obligated to purchase and maintain a car in order to

have access to convenient transportation. In such a system, automobile dependence will

necessarily remain high. As one OSA automobile commuter commented, the greatest

encouragement to take public transit would be “if [she] didn’t have [her] own car.” Thus, the real

city-wide reduction in automobile dependence will only occur when students—who already use

sustainable modes more than the average—not only use sustainable modes to commute to school,

but never feel obligated to buy a car in the first place.  

In order to make such a drastic change, the access to quality of the transportation offered

by sustainable modes must increase drastically. To do this means to totally redesign the urban

transportation system: to reduce trip distances by increasing population density, to increase the

number of transit routes and their frequencies of service, to reduce transit fares, to expand

infrastructure for walking and cycling, and to educate the public about bicycle use and safety.

Because of the cost to taxpayers of making these changes, public support to develop and use

sustainable transit is critical. Education must be at the core of redesigning the transportation

network, so that the redesign of the system grows in sync with a public appreciation for

sustainable transit.

This survey has gone as far as to show what students need from a transportation system–

what remains is to make sure that sustainable transit offers what is being looked for, and to find

30 

ways to market the new modes. It is these latter design opportunities that I leave for future

research.

31 

List of References    

City of Edmonton Transportation Department. (2006 May). 2005 Household Travel

Survey Overview. Edmonton, Alberta, Canada.

City of Edmonton Transportation Department. (2006 May). 2005 Household Travel

Survey Overview. Edmonton, Alberta, Canada.

City of Edmonton Transportation Department. (2009 September). The Way We Move:

Transportation Master Plan. Edmonton, Alberta, Canada.

City of Edmonton Transportation Department. (2009 September). The Way We Move:

Transportation Master Plan. Edmonton, Alberta, Canada.

Coyne, A. (2009, July 16). Canada’s best and worst run cities [Electronic version].

Maclean’s. Retrieved September 13, 2009, from http://www2.macleans.ca/2009/07/16/canadas-

best-and-worst-run-cities/

Coyne, A. (2009, July 16). Canada’s best and worst run cities [Electronic version].

Maclean’s. Retrieved September 13, 2009, from http://www2.macleans.ca/2009/07/16/canadas-

best-and-worst-run-cities/

Domencich, T. A., & Kraft G. (1970). Free Transit. Lexington, MA: Health Lexington

Books

Domencich, T. A., & Kraft G. (1970). Free Transit. Lexington, MA: Health Lexington

Books

Iveson, D. (2008, March 12). Administrative Inquiry for March 12 Council Meeting.

Administrative Inquiry made at the March 12, 2008, City Council meeting, in Edmonton, AB.

Iveson, D. (2008, March 12). Administrative Inquiry for March 12 Council Meeting.

Administrative Inquiry made at the March 12, 2008, City Council meeting, in Edmonton, AB.

Newman, P. W.G., & Kenworthy J.R. (1991). Cities and Automobile Dependence: a

sourcebook. (pp. 1-3). Aldershot Hants, England: Gower Publishing Company.

Newman, P. W.G., & Kenworthy J.R. (1991). Cities and Automobile Dependence: a

sourcebook. (pp. 1-3). Aldershot Hants, England: Gower Publishing Company.

Nordahl D. (2008). My kind of transit: rethinking public transportation in America (1st

ed.). (p. 76). Chicago: The Center for American Places at Columbia College Chicago.

Nordahl D. (2008). My kind of transit: rethinking public transportation in America (1st

ed.). (p. 76). Chicago: The Center for American Places at Columbia College Chicago.

Pucher, J. & Buehler, R. (2008). Making Cycling Irresistible: Lessons from The

Netherlands, Denmark and Germany. Transport Reviews, 28:4, 495-528.

Pucher, J. & Buehler, R. (2008). Making Cycling Irresistible: Lessons from The

Netherlands, Denmark and Germany. Transport Reviews, 28:4, 495-528.

32 

Appendix I. Annotated Survey        

 

In Alberta, driver’s licenses are issued in Classes 1 to 7.  Those with Class 5 licenses can drive cars and pickup trucks. Those with Class 4 (and under) licenses can additionally drive other vehicles such as taxis, buses, and freight trucks.  Class 7 is called a “Learner’s Permit” because the permit holder can drive a car or pickup truck, but under the condition that there is a Class 5 (or lower) license‐holder supervising in the vehicle. 

 

33 

 

At OSA, early morning classes start at 7:09 AM, and regular classes start at 8:02 AM. Doors open at 6:50 AM.  

At OSA, regular classes end at 3:26 PM, although some students can leave earlier during their spare blocks.  Late evening classes end at either 5:11 PM or 5:31 PM.  

I designed this stem to account for student transportation patterns that vary by weather, time of day, day of week, season, etc. Here, my aim is to determine the approximate modal shares of total trips throughout the year, rather than the specific circumstances in which each mode is used. 

 

34 

  

35 

     

36 

 [End of Appendix] 

37 

Appendix II. Data Tables from the Survey         The tables below contain the breakdown of responses to each of the questions in the

survey (Appendix I). The raw data is provided digitally on a CD (Appendix III).

The tables below contain the breakdown of responses to each of the questions in the

survey (Appendix I). The raw data is provided digitally on a CD (Appendix III).

Notes Notes   

• In questions marked with an asterisk (*), respondents were able to choose multiple

answers, leading to some totals that were greater than the sample size.

• In questions marked with an asterisk (*), respondents were able to choose multiple

answers, leading to some totals that were greater than the sample size.

• The following abbreviations are used for the geographic zones: (See page 9 for map.) • The following abbreviations are used for the geographic zones: (See page 9 for map.)

1 W 1 W  2 NW 2 NW  3 NE 3 NE  4 C 4 C  5 SW 5 SW  6 SE 6 SE  7 O 7 O Zone 1 West 

Zone 2  North‐West 

Zone 3 North‐East 

Zone 4 Central 

Zone 5 South‐West

Zone 6 South‐East 

Zone 7 Outside Edmonton

• Selected responses from written response questions are included as the last table of this

appendix.

• Uncertainties and units of measurement were excluded intentionally due to the non-

dimensional nature of the data.

• In Question 1.4, many respondents identified their location based on the city’s quadrant

system (Appendix 4), which was problematic because more than 90% of the city

officially lies in the north-west. To resolve this issue, I manually re-sorted the data

individually based on the 7-Zone system (Page 9). The data reflects the location of the

neighborhoods collected from the question “From what neighborhood do you commute to

OSA?” rather than the faulty responses collected in Question 1.4.

38 

1  Demographics of Survey Participants at OSA  Question and Answer  Number of Responses (N) 1.1  Are you male or female?  Overall 1 W 2 NW 3 NE 4 C 5 SW 6 SE 7 O

  Male  112  22  8  5  11  52  12  2   Female  159  12  11  10  6  94  20  6   (No response)  1  0  0  0  0  1  0  0 1.2  Do you have a valid Alberta driver's ‐‐‐license? 

 Overall

 1 W

 2 NW

  3 NE 

 4 C 

 5 SW 

 6 SE 

 7 O 

  Yes, Class 7 (learner's)  103  11  7  7  6  60  11  1   Yes, Class 5 (or under)  34  0  1  1  4  18  3  7   No.  131  23  11  7  7  65  18  0   (No response)  4  0  0  0  0  4  0  0 1.3  How old are you?  Overall  1 W  2 NW  3 NE  4 C  5 SW  6 SE  7 O   14  0  0  0  0  0  0  0  0   15  58  11  3  1  3  33  7  0   16  108  10  10  9  6  54  16  3   17  76  10  5  3  7  40  8  3   18  28  3  1  1  0  20  1  2   19  1  0  0  1  0  0  0  0   (No response)  1  0  0  0  0  1  0  0 1.4 In which geographic region of  ‐‐‐Edmonton is your neighborhood? ‐‐‐† (See note, above.) 

  Overall 

             

  Zone 1 ‐ West  34                 Zone 2 ‐ North‐West  19                 Zone 3 ‐ North‐East  15                 Zone 4 ‐ Central  17                 Zone 5 ‐ South‐West  146                 Zone 6 ‐ South‐East  32                 Zone 7 ‐ Outside Edmonton  8               

 2  Current Transportation Trends at OSA – Time of Travel  Question and Answer  Number of Responses (N) 2.1  What time do you leave on your ‐‐‐morning commute to OSA?* 

 Overall 

 1 W 

 2 NW 

  3 NE 

 4 C 

 5 SW 

 6 SE 

 7 O 

  5:30 to 6:00 AM  8  1  3  1  0  3  0  0   6:00 to 6:30 AM  30  5  7  4  0  12  2  0   6:30 to 7:00 AM  81  10  8  6  3  41  12  1   7:00 to 7:30 AM  149  14  9  6  7  86  20  7   7:30 to 8:00 AM  65  6  2  1  9  40  7  0   8:00 to 8:30 AM  10  0  1  0  1  6  2  0   Other  2  ‐  ‐  ‐  ‐  ‐  ‐  ‐   (No response)  0  0  0  0  0  0  0  0 

[Continued…]    

39 

2.2  How long, on average, does your  ‐‐‐morning commute take?* 

 Overall 

 1 W 

 2 NW 

  3 NE 

 4 C 

 5 SW 

 6 SE 

 7 O 

  0:00 to 0:15  23  1  1  1  7  11  2  0   0:15 to 0:30  159  14  7  2  5  102  22  7   0:30 to 0:45  84  12  8  6  3  44  9  2   0:45 to 1:00  36  8  6  5  1  15  0  1   1:00 to 1:15  18  3  3  3  0  7  2  0   1:15 to 1:30  10  5  0  2  0  1  2  0   more than 1:30  3  2  0  0  0  1  0  0   (No response)  0  0  0  0  0  0  0  0 2.3  What time do you leave on your ‐‐‐ evening commute from OSA?* 

 Overall 

 1 W 

 2 NW 

  3 NE 

 4 C 

 5 SW 

 6 SE 

 7 O 

  1:00 to 2:00 PM  22  2  3  2  1  12  2  0   2:00 to 3:00 PM  59  5  5  1  5  37  5  1   3:00 to 4:00 PM  218  28  17  13  13  117  23  7   4:00 to 5:00 PM  69  9  4  2  5  36  11  2   5:00 to 6:00 PM  53  3  3  4  4  34  4  1   Other  15  ‐  ‐  ‐  ‐  ‐  ‐  ‐   (No response)  0  0  0  0  0  0  0  0 2.4  How long, on average, does your  ‐‐‐evening commute take?* 

 Overall 

 1 W 

 2 NW 

  3 NE 

 4 C 

 5 SW 

 6 SE 

 7 O 

  0:00 to 0:15  14  0  0  0  6  6  2  0   0:15 to 0:30  90  2  4  1  7  54  15  7   0:30 to 0:45  84  11  6  3  2  50  11  1   0:45 to 1:00  63  9  8  8  1  33  3  1   1:00 to 1:15  57  10  4  6  0  32  4  1   1:15 to 1:30  43  12  4  4  1  18  4  0   more than 1:30  10  5  1  0  0  2  2  0   (No response)  0  0  0  0  0  0  0  0 

 3  Current Transportation Trends at OSA – Modal Choice   Question and Answer  Number of Responses (N) 3.1  Throughout the year, how often do ‐‐‐you commute to OSA… 

               

  …by bike?  Overall  1 W  2 NW  3 NE  4 C  5 SW  6 SE  7 O     Never  247  32  17  13  10  136  31  8     Rarely  11  1  0  1  3  6  0  0     Half the time  3  1  0  0  1  1  0  0     Often  2  0  0  0  0  2  0  0     Always  9  0  2  1  0  5  1  0     (No response)  0  0  0  0  0  0  0  0   …by car (driven by someone  ‐‐‐else)? 

 Overall 

 1 W 

 2 NW 

  3 NE 

 4 C 

 5 SW 

 6 SE 

 7 O 

    Never  23  5  0  2  4  8  3  1     Rarely  61  6  6  6  7  28  7  1     Half the time  56  7  7  1  0  35  3  3     Often  57  8  3  2  1  32  10  1     Always  75  8  3  4  2  47  9  2     (No response)  0  0  0  0  0  0  0  0 

40 

[3.1 Continued]  Throughout the year,  ‐‐‐how often do you commute to OSA… 

               

  …by car (on your own)?  Overall  1 W  2 NW  3 NE  4 C  5 SW  6 SE  7 O     Never  238  33  17  15  12  131  28  2     Rarely  13  1  1  0  0  7  2  2     Half the time  5  0  0  0  0  2  1  2     Often  6  0  0  0  2  3  0  1     Always  10  0  1  0  0  7  1  1     (No response)  0  0  0  0  0  0  0  0   ...by public transit?  Overall  1 W  2 NW  3 NE  4 C  5 SW  6 SE  7 O     Never  47  3  3  3  3  28  4  3     Rarely  70  7  3  3  2  46  8  1     Half the time  65  11  7  2  1  34  8  2     Often  35  2  2  2  6  19  2  2     Always  55  11  4  5  2  23  10  0     (No response)  0  0  0  0  0  0  0  0   …by taxi?  Overall  1 W  2 NW  3 NE  4 C  5 SW  6 SE  7 O     Never  254  33  18  14  13  139  29  8     Rarely  15  1  1  0  1  10  2  0     Half the time  0  0  0  0  0  0  0  0     Often  1  0  0  0  0  0  1  0     Always  2  0  0  1  0  1  0  0     (No response)  0  0  0  0  0  0  0  0   …by walking?  Overall  1 W  2 NW  3 NE  4 C  5 SW  6 SE  7 O     Never  248  31  16  13  7  142  31  8     Rarely  12  1  1  1  5  4  0  0     Half the time  4  1  0  0  0  2  1  0     Often  2  0  0  0  1  1  0  0     Always  6  1  2  1  1  1  0  0     (No response)  0  0  0  0  0  0  0  0 

 4  Factors Effecting Modal Choice at OSA  Question and Answer  Number of Responses (N) 4.1  Who decides how you commute to ‐‐‐OSA? 

 Overall 

 1 W 

 2 NW 

  3 NE 

 4 C 

 5 SW 

 6 SE 

 7 O 

  I decide.   35  2  1  3  4  22  1  2   My parents/guardians decide.  51  5  3  3  1  28  10  1   We both decide.  186  27  15  9  9  100  21  5   (No response)  0  0  0  0  0  0  0  0 4.2  How much have you critically ‐‐‐compared and evaluated your ‐‐‐transportation options to OSA? 

  Overall 

  1 W 

  2 NW 

    3 NE 

  4 C 

  5 SW 

  6 SE 

  7 O 

  1 – I have never thought about it.  26  1  3  2  1  15  3  1   2  53  7  2  1  1  35  5  2   3  83  5  7  5  4  49  11  2   4  71  11  4  3  4  39  9  1   5 – I have thoroughly thought it out.  39  10  3  4  4  12  4  2   (No response)  0  0  0  0  0  0  0  0 

41 

4.3  In deciding how to commute to ‐‐‐OSA, rank the importance you ‐‐‐(personally) assign to… 

               

  …comfort  Overall  1 W  2 NW  3 NE  4 C  5 SW  6 SE  7 O     1 – Not important  10  3  0  1  2  3  1  0     2  33  6  3  1  2  17  3  1     3  78  8  6  4  3  49  4  4     4  101  14  5  6  5  55  16  0     5‐ Very important  50  3  5  3  2  26  8  3     (No response)  0  0  0  0  0  0  0  0   ...cost  Overall  1 W  2 NW  3 NE  4 C  5 SW  6 SE  7 O     1 – Not important  27  2  1  4  0  15  4  1     2  41  8  4  0  3  18  6  2     3  53  7  3  4  2  33  4  0     4  85  9  7  2  4  47  12  4     5‐ Very important  66  8  4  5  5  37  6  1     (No response)  0  0  0  0  0  0  0  0   ...environmental impacts  Overall  1 W  2 NW  3 NE  4 C  5 SW  6 SE  7 O     1 – Not important  52  10  5  5  1  25  4  2     2  63  5  3  0  2  42  9  2     3  91  10  6  6  5  47  13  4     4  45  5  3  3  3  26  5  0     5‐ Very important  21  4  2  1  3  10  1  0     (No response)  0  0  0  0  0  0  0  0   ...enjoyment of the travel   ‐‐‐(scenery, exhilaration, etc.) 

 Overall 

 1 W 

 2 NW 

 3 NE 

 4 C 

 5 SW 

 6 SE 

 7 O 

    1 – Not important  125  14  7  6  6  72  14  6     2  68  9  6  1  3  41  8  0     3  45  8  5  3  1  21  7  0     4  23  2  1  3  2  11  2  2     5‐ Very important  11  1  0  2  2  5  1  0     (No response)  0  0  0  0  0  0  0  0   ...freedom while traveling (to   ‐‐‐eat, drink, talk, use portable   ‐‐‐technology, listen to music, etc.) 

  Overall 

  1 W 

  2 NW 

    3 NE 

  4 C 

  5 SW 

  6 SE 

  7 O 

    1 – Not important  39  3  4  3  2  21  6  0     2  68  9  6  1  3  41  8  0     3  45  8  5  3  1  21  7  0     4  23  2  1  3  2  11  2  2     5‐ Very important  57  6  6  5  3  26  8  3     (No response)  0  0  0  0  0  0  0  0   ...privacy  Overall  1 W  2 NW  3 NE  4 C  5 SW  6 SE  7 O     1 – Not important  39  6  5  4  2  16  4  2     2  52  11  3  2  5  27  2  2     3  96  10  5  5  4  61  10  1     4  53  5  2  1  2  29  12  2     5‐ Very important  32  2  4  3  1  17  4  1     (No response)  0  0  0  0  0  0  0  0  

42 

[4.3 Continued]  …                   ...reliability (ability to keep a    ‐‐‐consistent schedule) 

 Overall 

 1 W 

 2 NW 

  3 NE 

 4 C 

 5 SW 

 6 SE 

 7 O 

    1 – Not important  6  1  0  2  0  3  0  0     2  8  1  1  0  1  4  1  0     3  22  3  1  3  2  7  3  3     4  67  10  4  3  4  34  11  1     5‐ Very important  169  19  13  7  7  102  17  4     (No response)  0  0  0  0  0  0  0  0   ...safety  Overall  1 W  2 NW  3 NE  4 C  5 SW  6 SE  7 O     1 – Not important  8  2  1  2  0  2  1  0     2  19  4  0  1  1  10  1  2     3  33  3  2  2  4  15  6  1     4  77  8  5  4  3  44  11  2     5‐ Very important  135  17  11  6  6  79  13  3     (No response)  0  0  0  0  0  0  0  0   ...social acceptability (being cool)  Overall  1 W  2 NW  3 NE  4 C  5 SW  6 SE  7 O     1 – Not important  140  20  8  10  10  76  13  3     2  61  6  7  2  4  33  5  4     3  46  3  3  1  0  28  11  0     4  15  5  1  1  0  6  1  1     5‐ Very important  10  0  0  1  0  7  2  0     (No response)  0  0  0  0  0  0  0  0   ...time taken  Overall  1 W  2 NW  3 NE  4 C  5 SW  6 SE  7 O     1 – Not important  3  1  0  1  0  0  0  1     2  7  1  1  1  0  3  1  0     3  21  0  2  2  1  8  6  2     4  71  9  3  2  6  40  10  1     5‐ Very important  170  23  13  9  7  99  15  4     (No response)  0  0  0  0  0  0  0  0 4.4  Which of the following modes of ‐‐‐transportation are you most ‐‐‐accustomed to?* 

  Overall 

  1 W 

  2 NW 

    3 NE 

  4 C 

  5 SW 

  6 SE 

  7 O 

  Bike    42  6  2  2  3  24  3  2   Car (driven by someone else)  233  33  14  11  10  127  31  7   Car (on your own)  33  1  2  0  2  19  2  7   Public Transit  190  28  14  11  10  102  20  5   Taxi  9  0  0  0  2  5  1  1   Walking  81  12  7  6  5  42  7  2   (No response)  0  0  0  0  0  0  0  0 4.5  In general, how willing are you to  ‐‐‐make changes to your current  ‐‐‐transportation choices? 

  Overall 

  1 W 

  2 NW 

    3 NE 

  4 C 

  5 SW 

  6 SE 

  7 O 

  1 – Very reluctant  16  1  2  2  1  6  3  1   2  55  6  1  5  4  29  9  1   3  121  14  8  6  6  74  9  4   4  64  11  8  2  2  31  8  2   5 – Very willing  16  2  0  0  1  10  3  0   (No response)  0  0  0  0  0  0  0  0 

43 

5  Specific Transportation‐related Preferences at OSA  Question and Answer  Number of Responses (N) 5.1  Are you more willing to travel by  ‐‐‐city bus or LRT? 

 Overall 

 1 W 

 2 NW 

  3 NE 

 4 C 

 5 SW 

 6 SE 

 7 O 

  City bus  56  7  4  0  2  25  15  3   LRT  81  12  5  6  5  44  6  3   Both equally  135  15  10  9  7  81  11  2   (No response)  0  0  0  0  0  0  0  0 

5.2  For biking to OSA, which of the  ‐‐‐following would you prefer to use?* 

 Overall 

 1 W 

 2 NW 

  3 NE 

 4 C 

 5 SW 

 6 SE 

 7 O 

  Bicycle paths and sidewalks shared   ‐‐‐with pedestrians (mixed‐use paths) 

 145 

 16 

 9 

 7 

 10 

 81 

 17 

 5 

  Bike‐only lanes alongside traffic  94  12  6  8  7  49  9  3   Bike lanes shared with buses/taxis  21  3  1  1  3  13  0  0   Residential roads shared with vehicles  50  11  1  1  4  29  3  1   Major roads shared with vehicles  4  0  1  0  1  2  0  0   Service roads or alleys  25  4  1  1  4  9  6  0   I don't know.  107  18  10  5  3  56  12  3   (No response)  0  0  0  0  0  0  0  0 

5.3  For walking to OSA, which of the  ‐‐‐following would you prefer to use?* 

 Overall 

 1 W 

 2 NW 

  3 NE 

 4 C 

 5 SW 

 6 SE 

 7 O 

  Off‐road paths only for pedestrians  114  16  7  4  7  64  12  4   Off‐road paths shared with cyclists  72  9  4  4  4  38  8  5   Service roads or alleys  18  2  2  2  2  8  2  0   Sidewalks  198  27  13  12  10  109  22  5   I don't know.  63  6  7  3  3  32  9  3   (No response)  0  0  0  0  0  0  0  0 

5.4  Which of the following changes  ‐‐‐would most encourage you to bike to OSA?* 

 Overall 

 1 W 

 2 NW 

  3 NE 

 4 C 

 5 SW 

 6 SE 

 7 O 

  Better lighting  12  3  1  1  0  6  1  0   Shorter distance  229  30  16  15  6  130  25  7   Warmer weather  148  19  9  9  8  86  13  4   Better scenery  19  2  2  2  2  9  2  0   Others to bike with  99  12  6  5  3  60  12  1   Bike Maps / Trip planning tools  28  3  0  4  1  18  2  0   Improved safety  105  14  5  5  6  63  9  3   More/better road facilities  80  9  6  4  4  50  4  3   More/better bike parking  35  5  2  1  3  18  4  2   Having an operational bike  41  8  2  2  3  21  4  1   Other  30  ‐  ‐  ‐  ‐  ‐  ‐  ‐   (No response)  0  0  0  0  0  0  0  0 

[Continued…]      

44 

 5.5  Which of the following changes  ‐‐‐would most encourage you to walk to OSA? 

 Overall 

 1 W 

 2 NW 

  3 NE 

 4 C 

 5 SW 

 6 SE 

 7 O 

  Better lighting  18  3  0  2  2  11  0  0   Shorter distance  246  32  17  14  8  141  26  8   Warmer weather  157  23  8  6  7  92  16  5   Better scenery  28  4  2  1  3  13  4  1   Others to walk with  124  12  8  8  3  80  12  1   Walking maps  22  3  0  3  1  14  1  0   Improved safety  92  11  7  8  6  47  10  3   More/better walking facilities  40  5  3  4  2  20  5  1   Other    21  ‐  ‐  ‐  ‐  ‐  ‐  ‐   (No response)  0  0  0  0  0  0  0  0 

5.6  Which of the following changes  ‐‐‐would most encourage you to take  ‐‐‐public transit to OSA? 

  Overall 

  1 W 

  2 NW 

    3 NE 

  4 C 

  5 SW 

  6 SE 

  7 O 

  Closer bus/LRT stops  102  9  6  5  2  63  11  6   Faster service  219  30  17  12  12  118  25  5   Warmer weather  38  2  3  3  0  22  7  1   Cleaner/newer vehicles  51  8  2  3  4  27  6  1   Others to take transit with  74  6  5  6  3  47  5  2   Better trip planning tools  23  3  2  2  1  14  0  1   Improved reliability  111  19  5  7  6  57  13  4   Improved safety  37  8  1  4  2  18  4  0   Higher service frequency  135  22  9  7  9  73  13  2   Fare reductions / Free transit  98  14  4  6  3  60  9  2   Other  15  ‐  ‐  ‐  ‐  ‐  ‐  ‐   (No response)  0  0  0  0  0  0  0  0 

 

6  Selected Written Responses  Question  Answer What time do you leave on your  ‐‐‐evening commute from OSA? 

‐ “11:00AM to 12:30PM” (10 similar responses)  

If you use a mode of transportation ‐‐‐not mentioned above, please specify: 

‐ “Motorcycle” 

Which of the following changes would  ‐‐‐most encourage you to bike to OSA? 

‐ “Exorbitant gas prices” ‐ “Actually know how to ride a bike” ‐ “Less Contruction”  ‐ “If I there is no hill on my way to school.”  ‐ “BETTER DRIVERS” 

Which of the following changes would  ‐‐‐most encourage you to walk to OSA? 

‐ “LIGHTER BACKPACK” (4 similar responses) 

Which of the following changes would  ‐‐‐most encourage you to take public ‐‐‐transit to OSA? 

‐ “if i didn't have my own car”  ‐ “it takes so long for me, especially for the final bus (only comes every 30 mins) so if i miss it, it takes forever”  ‐ “The transit and LRT connect better.  Right now I might end up waiting almost 30min for a bus to arrive after taking the LRT” 

45 

[continued…]  If there are other considerations that  ‐‐‐affect your transportation choices to ‐‐‐OSA, please add them below:  

‐ “Having a "park‐and‐ride" so i could drive to a place where bus/public transit stops exist. that would be lovely. :)”  ‐ “Most of my considerations in choosing my mode of transport are based on the fact that i live too far away to take any other mode of transport and get to school on time”  ‐ “distance for sure cuz i live in riverbend and it would take years to walk/bike to school…”  ‐ “I live in Sherwood Park, so biking/walking are both pretty much out of the question. There is no kind of incentive that would convince me to bike or walk to school.” ‐ “For biking, amount of hills in terrain. More hills = harder and longer commute.” ‐ “Winter is a bitch. ‐50, are you serious!? Dibs out.” ‐ “…sadly, i live in a new area where a 15 minute commute by walk is required to bus. Edmonton is too large of a city for me to walk or bike from my location. And cold... you know. Why does edmonton have to be so sparse?”  ‐ “My health does not always allow me the luxury of taking the time to walk or bike the distance I live from the school. My parents do not trust me enough to take the bus. I carpool to save energy, but my varying schedule/time taken to get home is a big issue when I have such a heavy work/study load.” ‐ “I wouldn't mind taking the bus, but it takes 3X‐4X longer than getting a ride, is expensive, and is unreliable...” ‐ “I like the transportation system in Hong Kong. There are a lot more stops all over the city and the transportation is easily accessable. Since Edmonton gets pretty cold in the winter time, it would be better to have a heated underground LRT system. If there is a stop in almost every neighbourhood it will be more convenient and efficient. And  safety is also a big issue for me.”  ‐ “It takes about two hours to take the bus from and to OSA. It's very disappointing.” ‐ “Distance, i simply live toooooooooooooooooooooo far away to really have any choices ( I don't want to have to walk for like 4 hours )”  ‐ “Since I have a morning class, it is very difficult for me to commute by walking/biking. In the winter, it is a lot colder out; therefore, walking to school would endanger my safety and my life. I live in the Northwest of the city so it takes a long time to get to school by bus. This is very annoying with the inefficient bus routes and the chroniclly late buses.”   

   

46 

  [Continued] If there are other  ‐‐‐considerations that affect your  ‐‐‐transportation choices to OSA, please ‐‐‐add them below:  

‐ “Perhaps I would like increased bus services in the mornings and evenings when there are the most riders, and ETS could get rid of a few of the buses that come during the day in residential areas and have three people on them. Perhaps you could get rid of one of those buses and add them to those random gaps in the evening or morning where buses will come, say, at 5:15, 5:30 and then not until 6:00. Those are just my thoughts.” ‐ “…As well, I'm a girl, which makes walking/biking/taking the bus alone not a very enjoyable experience,nor do I feel very safe alone, as most of the students who attend OSA do not live in the same area of town as I do.”  ‐ “The main reason for my transportation choices are dependant upon the distance from home to school.  Living in southern edmonton, not too far from the airport, the time to take public transit is about 5‐6 times longer than travelling by car.  ”  ‐ “Showing bus passes is very ineffective when bussing from OSA. There's so many people, and it takes so long because the driver has to see every individual pass, or give transfers, etc.”  ‐ “The only thing is that buses don't run efficiently from my house to the school. The 94 (Super express from heritage to university) used to run until April, when University was over, and then I couldn't bus anymore because the bus schedules suck otherwise.”  

 [End of Appendix]