University of Amsterdam
Graduate School of Social Sciences
Master’s of Urban & Regional Planning
Master’s Thesis:
Go with the Flow, Bro: The Link Between Bicycling
Infrastructure, Speed, and Flow in Washington, DC and
Amsterdam
Gregory Matlesky 11184248
June 26, 2017
Thesis – Dilemma of Urban Mobility Supervisor: Marco te Brömmelstroet Second Reader: Martijn van den Hurk
Abstract
This thesis examined the relationship between comfort, cycling speed, and flow in Washington, DC and Amsterdam. Data was collected from field observations, surveys, and interviews with cyclists in both cities to examine how the quality of bicycling infrastructure and separation from motor traffic influence and facilitate flow in low and high-cycling cities. Results suggested that cyclist comfort had no or a very minor effect on cycling speed, that increasing protection and separation from motor vehicles would facilitate flow in Washington, DC, and that widening cycle paths or constructing “fietsstraaten” or bicycle streets without any traffic signals would increase flow in Amsterdam.
Acknowledgements
I would like to begin by thanking my thesis advisor, Marco te Brömmelstroet, aka the “FietsProfessor” for his guidance and assistance throughout the course of this thesis. Many a frantic email were answered quickly, concisely, and nonchalantly, assuaging any fears and insecurities I had while pointing me in the right direction and inspiring confidence in times of doubt. Without his patience and help, this thesis would not be before you today.
I’d also like to thank my fellow MURPees at the University of Amsterdam, particularly my other advisor group members Ben, Paul, and Chris for countless texts, chats, coffees, and beers as we struggled through our thesis writing process. Ideas were bounced off each other, advice was shared, and frustrations commiserated throughout this past year. This past year has been a wonderful experience and I’ll never forget all the memories we had. No matter how much work there was to be done, there was always time for one more beer. We did it!
Thank you to the lovely city of Amsterdam for playing host to me for the past year. I’ve traveled countless miles through your streets and cycle paths perched upon the seat of my trusty fiets. I’ve seen the good, the bad, and the plain ugly and everything else in between of your bicycle infrastructure, providing endless inspiration that I would love to take back to the District of Columbia and implement. One day, we too shall become a city of cyclists!
Thanks are due to my wonderful parents who supported me throughout the entire process, despite my constant weekly kvetching. No matter how down, depressed, or disinterested I was, they were always there to lend a helping hand or provide an outlet for my frustration. I hope I made you proud, Mom and Dad!
Of course, the greatest of thanks goes out to my lovely fiancé Alli, who without her incredible patience, warmth, and hospitality, I would not have made it through this past year, particularly the last week of thesis writing. Dinners were made, errands were run, and life was, in general, a whole lot easier with her around. Words cannot even begin to express my gratitude. I love you!
And lastly, thanks are due to Duane, wherever he may be, who inspired the title for this thesis. Go with the flow, bro!
Table of Contents
1. Introduction ... 4
2. Theoretical Framework ... 7
2.1 Bicycle Facility Quality Measurements ... 7
2.2 Bicycling Comfort/Stress/Exertion ... 9
2.3 Bicyclist Route Choice ... 10
2.4 Flow ... 11 2.5 Comfort-Flow Relationship ... 21 2.6 Conceptual Framework ... 23 2.7 Research Question ... 25 3. Methodology ... 30 3.1 Case Studies ... 30 3.1.1 Washington, DC ... 32 3.1.2 Amsterdam ... 37 3.2 Research Design ... 39 4. Results ... 44 4.1 Washington, DC ... 44 4.1.1 Speed Observations ... 44 4.1.2 Interviews ... 45 4.1.3 Surveys ... 48 4.2 Amsterdam ... 55 4.2.1 Speed Observations ... 55 4.2.2 Interviews ... 56 4.2.3 Surveys ... 61 5. Discussion ... 67 5.1 Washington, DC ... 67 5.1.1 Speed ... 67 5.1.2 Flow ... 68 5.2 Amsterdam ... 71 5.2.1 Speed ... 71 5.2.2 Flow ... 73 6. Conclusion ... 77 6.1 Summary ... 77 6.2 Reflection ... 81 References ... 84
1. Introduction
Repetitive physical activities are really like a Zen practice. You know what the Zen monks said; you sweep the temple garden and it’s in the motion where you’re actually in tune with the whole universe, in that motion. I find that’s just as easy to get when you’re gardening or when you’re cycling around the neighborhood or when you’re putting a load of wash in or whatever. Then you’re moving your body and you feel extremely in tune with everything. (Hunter & Csíkszentmihályi 2000, p. 22).
I’m not quite sure how I ended up on the hood of his car, but I soon realized I was in trouble.
It was around 11:30 one late September evening in 2014 and I was making my nightly commute from my apartment next to Washington’s National Zoo to my girlfriend’s apartment on Capitol Hill when I had my first run-in (bike-in?) with someone else’s car as he T-boned me pulling out of a driveway at 15th & P Streets, NW. Don’t get me wrong, it’s not like I haven’t had several (hundred) close calls during my time cycling through my nation’s capital. It’s just, of all the times and places to have happen, I never thought my first actual collision would be late at night on the District’s first protected bicycle lane. But alas, so it happens.
I was fine, fortunately. The only damage was to my bicycle’s front wheel, my sense of invulnerability on the road, and the pleasure from my night time slow rides. Police were called, information was exchanged, and I soon received a new bicycle wheel and a $1000 check from the crasher’s insurance. As far as car-bike collisions go, it was perfect, though I’m not looking to try my luck again.
When I retreated back to my apartment that night, I went over the details of the incident in my head. How did I not see this guy coming in my peripheral vision? I concluded that I must have been lost in my thoughts, as I often was on these roughly 5.2 mile (or 8.37 km) pleasure cruises to my girlfriend’s place. I enjoyed these late night trips across the District of Columbia as traffic was light, the weather was a little cooler during the summer nights, and I had the freedom to cycle at my own pace, taking in the sights and wonder of the lively streets in DC, clearing my head of the stresses and anxieties from the day at work while blasting out to some Bruce Springsteen or Kanye West. I was in the zone that night, as always, and believed I was too lost in my thoughts to react to the car approaching from my side. That explanation worked for me.
I hadn’t thought much about that night or my enjoyment derived from these rides until I was writing this very thesis. I had originally intended to write about a classic indicator of transportation performance: speed, or in this case, average cyclist speed, to examine a relationship between it and comfort. However, my advisor guided me to the work of Mihaly Csíkszentmihályi and his wealth of research around the concept of flow.
First developed in 1975, Csíkszentmihályi has pretty much paved the way on flow, or what he describes as the optimal experience, when our skills match perfectly to challenges that face us to transcend the moment, unlocking the powerful potential of their minds when they are allowed to become fully engrossed in an activity where time as much as anxieties seem to melt away as users experience a loss of self-consciousness (1990; Hunter & Csíkszentmihályi 2000).
I first dismissed it, thinking it would be a minor portion of my thesis, but as time went on and I conducted further and further research in to it, I thought back to that night on the hood of that man’s car and why I loved those night time rides so much. I hadn’t known it then, but it was all too clear to me later: all those late night rides were my Zen practice. I was experiencing flow!
I was hooked and wanted to research it further. With these two indicators—speed and flow— I wanted to take a look at how the protection and separation from motor traffic provided by protected bicycle infrastructure had an effect on individual cyclists to see what influenced flow and how to facilitate it.
Cycling is on the rise in the United States as policymakers and transportation planners try to correct the mobility imbalance caused by decades of autocentric transportation planning. The main barriers to cycling are seen as a dearth of safe, dedicated cycling infrastructure that protect cyclists from the dangers and stress of speeding motor traffic (Sorton & Walsh 1994; Heinen, Maat, & van Wee 2011; Tilahun, Levinson, & Krizek 2007; Taylor & Handy 2009; Broach, Dill, & Glebe 2012; Mertens et al. 2016). While best practices have been established from European cities such as Copenhagen and Amsterdam, many North American cities are hesitant to devote the necessary road space to cycling, which often entails taking space away from cars and reducing capacity on an already overburdened road network. Policymakers are loath to
make the political choice in reprioritizing road networks often because the critical mass for cycling has not yet been reached.
Of the many theories attempting to explain the failure to attract people to cycling, one main barrier, particularly in North America, is the perception that cycling is a sport, suitable only for the young, fit, and fast as they race with traffic (Gatersleben & Appleton 2007). While cycling may be seen as safer and more comfortable while riding on dedicated bicycle paths, there is still a question of physical exertion that may prevent people from hopping on the saddle (Gatersleben & Appleton 2007; Wardman, Tight, & Page 2007). Riders do not wish to show up to their office sweaty and a physically-taxing commute is not the most appealing when faced with the choice of a seat on a bus or train or the door-to-door convenience of the car (Heinen, Maat, & van Wee 2011), particularly those in advanced age or limited physical stamina (Hölzel, Höchtl, & Senner 2012).
Could the case be made that physically separated cycling infrastructure not only provides protection from cars, but also lower the challenge presented by cycling and providing the grounds for the optimal experience? Could infrastructure that protects cyclists from traffic allow them to slow down, take it easy, and allow them to “go with the flow”? Further, would this potential link persuade those interested but concerned to take the ride (Geller 2006)? These questions motivated me to write this thesis before you.
2. Theoretical Framework
In order to establish a theoretical frame of which to base my thesis research on, I conducted an extensive review of literature related to theories, concepts, and general thoughts and trends related to bicycling comfort, cyclist choice, and flow. The summary of these findings is presented below.
2.1 Bicycle Facility Quality Measurements
While there have been considerable measurement schemes for car travel, there has been relatively limited measurements of cycling facility quality. Sorton & Walsh (1994) reports that the first measure of bicycle stress was developed by the Geolong bike plan team in Australia. They developed their own method of bicycle stress, determining three types of cyclists (children, casual, and experienced) and a rating scale of 1 (very low stress) through 5 (very high stress). Botma (1995) developed a Bicyclist Level of Service, modeled after the automobile Level of Service Scale, looking at facility capacity and bicyclist passings and meetings to determine a level of service from A through F. Mekuria, Furth, & Nixon (2012) developed a “Bicyclist Level of Traffic Stress” system using Dutch guidelines, classifying road segments on scales of 1-4, ranging from a level most children can tolerate to those tolerated only by the “strong and fearless” cyclists as classified by Geller (2006). They used criteria of classifying roads based on traffic characteristics such as road width, traffic speed, presence of car parking, if bicyclists rode in mixed traffic, presence of bicycle lanes, and separated paths.
Lowry, Callister, Greshman, & Moore (2012) looked at the concept of “Bikeability”, or comfort and convenience of an entire bikeway network for accessibility, in their method. They incorporated the suitability of adding bicycle facilities to roads, looking at the potential of adding new bicycle lanes, shared-use paths, and a combination of both with zoning and land use changes to determine bicycling improvements. Recently, Foster, Monsere, Dill, & Clifton (2015) developed a system to rate physically-separated and protected cycling paths in the United States from A through F, looking at the type of buffer provided, direction of travel (one-way vs. two-(one-way), adjacent car speed limit, and average daily motor vehicle volume to determine comfort.
Recently, governments in the United States have begun to measure and map bicycle stress levels, including the District of Columbia and Montgomery County and Arlington County in the surrounding states of Maryland and Virginia, respectively (see Figures 1 and 2). The three jurisdictions measurement criteria are similar, measuring streets based on traffic counts, street width, speed, facility provisions, etc. and classifying streets in the individual jurisdiction’s network into categories ranging from a seven-point scale (Montgomery County, Maryland 2016) to a four-point scale (District Department of Transportation 2017) to a three-point scale (Arlington County, Virginia 2016).
Figure 1: District Department of Transportation's Bicycle Comfort Network. (districtmobility.org)
2.2 Bicycling Comfort/Stress/Exertion
Comfort and stress are considerably important factors in cycling. Naturally, as with any other activity in life, we’re not likely to participate in anything that makes us feel scared, frightened for our lives, and extremely uncomfortable. The thought of riding a bicycle on a busy street with motor traffic zooming past mere centimeters away is not what many would consider a safe or particularly comfortable experience. As governments around the world look to tackle the issues of congestion, pollution, obesity, and climate change by making cycling a legitimate form of transportation, they must keep in mind what factors and characteristics cyclists prefer as well as the reasoning and rationale behind their preference. Fortunately, there have been numerous studies determining the barriers to cycling.
Gatersleben & Appleton (2007) found that the largest factors preventing people from cycling were travel distance, gradient and hilliness, traffic safety, vehicle traffic flows, driver behavior, pollution, inclement weather, personal fitness, and social pressure. Wardman, Tight, & Page (2007) added credence with their research finding tiredness and cycling ability significantly affected cycling participation. Bicyclists choose the route with the least amount of effort (Sorton & Walsh 1994), choosing routes with not only least physical effort but also mental stress (Heinen, Maat, & van Wee 2011). They prefer routes they perceive as safe (Tilahun, Levinson, & Krizek 2007; Emond, Taylor, & Handy 2009; Broach, Dill, & Gliebe 2012; Mertens et al. 2016) and avoided routes they perceived as dangerous (Larsen & El-Geneidy 2011; Joo, Oh, Jeon, & Lee 2015). Further, cyclists found increased comfort and less stress the more physical protection and separation from traffic was provided (Li, Wang, Liu, & Ragland 2012; Caulfield, Brick, & McCarthy 2012; Vedel, Jacobsen, & Skoy-Petersen 2017).
Bicycle path congestion was found to have a negative impact on route utility and preference (Li et al. 2012; Caulfield, Brick, & McCarthy 2012; Vedel, Jacobsen, & Skov-Petersen 2017). In Copenhagen, widely considered another cycling Mecca of Europe, 82% of respondents in a study by Vedel, Jacobsen, & Skov-Petersen (2017) said crowding and congestion on cycletracks from other cyclists made them feel very unsafe or unsafe, citing an increased risk of collisions and negative social interactions. Similarly, a study of Dublin cyclists (Caulfield, Brick, & McCarthy 2012) found that across all types of cycling infrastructure, cyclists of all confidence levels slightly preferred routes with fewer cyclists.
Effects of the environment were found to have an effect on cycling comfort and physical exertion as well, including wind (Kim & Macdonald 2016) and topography (Li et al. 2012; Broach, Gliebe, & Dill 2012). Broach et al. found that cyclists in Portland, Oregon would go out of their way to avoid slopes and inclines, traveling 37% further to avoid a slope of 2%; 120% further to avoid a slope of 4%; and up to 320% to avoid a slope of 6%.
Different types of cyclists experience traffic stress differently, not only with cycling experience (Sorton & Walsh 1994; Krizek & Roland 2005; Caulfield, Brick, & McCarthy 2012) but also different genders (Tilahun, Levinson, & Krizek 2007; Emond et al. 2009). Emond et al. found that women prefer on-street paths to off-street paths due to personal safety (i.e. crime and visibility) reasons. For women, comfort was the most important determinant for cycling. Comfort also matters when it comes to quality of the cycling facility, finding that proper maintenance and surface quality (Hölzel, Höchtl, & Senner 2012; Ayachi, Dorey, & Guastavino 2015; Calvey, Shackleton, Taylor, & Llewellyn 2015) affected cyclist comfort.
2.3 Bicyclist Route Choice
Just as important as determining the barriers to cycling are studying what routes cyclists actually choose and the two seem to go hand in hand as cyclists choose routes with the most amount of protection from cars.
There is a wealth of literature finding that cyclists and non-cyclists alike prefer segregated, physically-protected infrastructure that separates them from automobile traffic (Gatersleben & Appleton 2007; Wardman et al. 2007; Emond et al. 2009; Winters, Davidson, Kao, & Teshke 2011; Li et al. 2012; Caulfield, Brick, & McCarthy 2012; Mertens et al. 2016; Vedel, Jacobsen, & Skov-Petersen 2017). Research of cyclists in Montreal, Canada from Larden & El-Geneidy (2011) examined this theory deeper, finding that while many preferred physical separation, it was actually length of the cycling facility that was the greatest factor for cycling preference. Cyclists in their study added an average of 2.2 km to their trip (or 34% of total trip distance) to use a cycling facility such as a bike lane, physically-separated bicycle path, or off-road path. Winters et al. (2011) surveyed cyclists in Vancouver, Canada and found routes away from traffic and physically-separated paths were two of the three strongest motivators to cycle. Additionally, Broach et a. (2012) found cyclists were willing to go 140% out of their way to
avoid high traffic streets (defined as 20,000 vehicles/day and up) and preferred separated paths, then traffic-calmed bicycle boulevards. Painted lanes were preferred only when low-traffic and low-stress streets were not an option.
Data gathered from 38,000 cyclists in the Netherlands revealed popularity of different routes and average speeds (Fiets TelWeek 2015; Fiets TelWeek 2016). Strangely enough, Ton, Cats, Duives, & Hoogedoorn (2016) examined route choice of cyclists in Amsterdam using Fiets TelWeek data and determined that distance and number of intersections were the greatest factor in cyclist route choice, finding no relation between separated cycle paths and route preference, bucking the trend of nearly every other city and country in the world. Similarly, cyclists in Dublin, also preferred routes with fewer intersections, but still greatly preferred separated and protected cycling paths (Caulfield, Brick, & McCarthy 2012).
Research on the optimal cycling facility has been mixed. While cycling infrastructure with physical separation and protection from automobiles has been seen as the best practice cycling facility to provide, Li et al. (2012) found that cyclists in China preferred different types of infrastructure dependent on cyclist numbers. Cyclists were observed to prefer physical separation when cycling congestion was low (determined as under 400 cyclists per hour) and on-street painted lanes when lanes were more congested (greater than 400 cyclists an hour). Wang et al. (2016) also found that access to low-stress cycle networks doesn’t necessarily correlate with increased cycling mode share.
2.4 Flow
“Flow is a state in which an individual is completely immersed in an activity with reflective self-consciousness but with a deep sense of control”
(Ergeser & Schiepe-Tiska 2012, p. 1)
Flow. In your groove. In the zone. One with the world. We’ve all heard of these phrases to
describe the mental state of total immersion in an activity, be it something as mundane as typing reports at your desk at work, to practicing the guitar at home, to scaling a cliff in the desert, where we are lost in our own world for long periods of time. Flow is a state of consciousness
where a person, totally absorbed, feels tremendous amounts of exhilaration, control, and enjoyment (Hunter & Csíkszentmihályi, p. 12).
The majority of research on flow has been conducted by one man, Mihaly Csíkszentmihályi, who first formulated the theory in his 1975 work “Beyond Boredom and Anxiety” (Ergeser & Schiepe-Tiska 2012; Moneta 2012) after several years of research into play activities, looking at creatives and artists’ personalities seeking to understand what made activities inherently motivating. During the course of his research, several of his participants used similar phrasing to describe the complete and total immersion in an activity they were performing, either at work or in leisure, likening the sensation to “flowing” in a river. Csíkszentmihályi believes that entering the flow state or achieving the flow experience in our daily activities, and learning how to harness its creative capabilities, could be the key to a rich, productive life (Ergeser & Schiepe-Tiska 2012).
The definition of flow has more or less remained the same since Csíkszentmihályi first defined it in 1975 (Moneta 2012), though he and others have made slight modifications over the years. Csíkszentmihályi originally described six components (Ergeser & Schiepe-Tiska 2012:
1. Merging of Action and Awareness: One is aware of their actions but not of the awareness itself.
2. Centering of Attention: One has a high degree of concentration on the task at hand. 3. Loss of Self-Consciousness: Considerations about the self become irrelevant. 4. Feeling of Control: One feels total control over their actions and demands of the
environment.
5. Clear Goals and Feedback: Goals and the means of achieving them are logically ordered, and action and reaction are automatic.
6. Autotelic Nature: The activity is performed for the sake of itself, with no need for external goals or rewards.
Over time, Csíkszentmihályi made slight changes to the original six components, later splitting the “Clear Goals and Feedback” component into two separate components and adding the eighth component of the “distortion of temporal experience of time” (Nakamura & Csíkszentmihályi 2005), described as experiencing time as passing shorter or longer than normal during the flow experience. Later, the ninth component of “balance of challenges and
skills” was developed. All in all, nine components of flow are, more or less, agreed upon by researchers as the nine components and experiences of the flow state (Jackson & Marsh 1996; Jackson & Csíkszentmihályi 1999; Ergeser & Schiepe-Tiska 2012):
Concentration: Focused Concentration on the Present Activity
“Scrambling eggs is like hitting a baseball”, adds [Ted Williams] the last man to bat over .400 -- the hardest thing in the world to do. “A man has to devote every ounce of his
concentration to the task if he wants it done right.” (O’Neill 1999)
According to Csíkszentmihályi, our attention is the most important tool in the task of improving the quality of our daily experience (Csíkszentmihályi 1990, p. 33) and thus the flow experience requires total concentration on the task at hand. Though seemingly simple enough, one would say that it’s becoming increasingly harder to shut out the world from all distraction. After all, we live in a world of constantly bombarding information that diverts our attention seemingly every few moments, contending with all the other drama, threats, and anxieties already present as we go about our daily lives. Our commute to work is crowded as we jostle among countless others on highways, trains, and sidewalks worldwide. Phone and email keeps us in constant contact with clients and superiors. Now, with the advent of the internet, 24-hour news networks, and the smart phone with countless mindless apps, we face a daily deluge of notifications for likes, comments, texts, calls, breaking news, alerts, etc. that intrude and interrupt pleasure during our leisure time. Our brains can only process so much information at any one time, and we must constantly decide which stimuli to pay attention to and which to ignore.
This perpetual worrying about external threats, stresses, and other distractions prevents one from entering the flow state (Csíkszentmihályi 1990). Being able to focus the energy of attention on the present and its essential figures, thoughts, and experiences that matter allows everything else of less concern to fade into the background (Hunter & Csíkszentmihályi 2000).
Sense of Control Over One’s Actions
The flow experience is typically described as involving a sense of control, or lacking the sense of worry about losing control that is typical in many situations in life (Csíkszentmihályi 1990, p. 59). Csíkszentmihályi refers to this as the “paradox” of control. Later amended to a sense of control, one feels that they have absolute control over the situation (to the furthest extent
possible), without actively trying to exert that control (Jackson & Marsh 1996). In his 1990 book, Flow: The Psychology of Optimal Experience, Csíkszentmihályi lists several quotes from participants engaging in activities ranging from ballet to chess to rock climbing. They reference a high sense of control over the situation, knowing that while they may face danger or failure, theoretically perfection is possible. Participants have the possibility, rather than the
actuality of control. This potential for control is central to the flow experience (Jackson &
Marsh 1996).
Merging of Action and Awareness
This component of flow involves the seemingly contradictory state of being aware of one’s own actions, but not of the awareness itself (Ergeser & Schiepe-Tiska 2012). One of the most unusual and distinctive features of the flow experience takes place: people become so involved in the activity at hand that their actions becomes spontaneous and/or automatic (Csíkszentmihályi 1990, p. 53; Hunter & Marsh 1996). A person in flow would stop being aware of themselves as separate from the actions they are performing (Csíkszentmihályi 1990) as if they and the world became one. For example, for a cyclist in flow, there would no longer be “me and the bike”; these distinctions become collapsed into a unified sense of motion (Csíkszentmihályi 1990, p. 14) where the physical boundaries of the body have been transcended and extended to the motion-making tool (the bicycle), and the construction of the world becomes based more on the sensation of movement rather than being a person on a bike riding down the street.
Csíkszentmihályi has speculated that this component is the clearest sign of the flow experience (Ergeser & Schiepe-Tiska 2012), and is highly associated with phrases such as being “in the groove” or “in the zone” (Hunter & Marsh 1996, p. 18).
Autotelic: An Experience In and Of Itself
For Csíkszentmihályi, a key component of the flow experience is that the activity being performed is an end in and of itself (Csíkszentmihályi 1990), or autotelic. Deriving from auto, meaning the self, and telos, or the Greek word for “goal”, autotelic activities are intrinsically-motivated, goal directed activities that require significant physical or mental energy done not with the expectation of some future benefit, but rather because performing the activity itself is the reward with no need for external goals or rewards (Csíkszentmihályi 1990, p. 67;
Abhuhamdeh & Csíkszentmihályi 2011; Ergeser & Schiepe-Tiska 2012). Csíkszentmihályi uses the example of a stock broker playing the stock market: playing to make endless amounts of money, an obvious external monetary reward and motivation, is not in line with an autotelic activity. Rather, if one partook to prove their skill at foretelling future financial trends, even if the final monetary outcome is the same, then it could be considered be autotelic.
While one of the nine listed components, not all flow researches agree that this component of flow is necessarily true. Some believe, and I am inclined to agree, that the flow state can be achieved regardless of whether the activity is done for intrinsic and/or extrinsic reasons (Ergeser & Schiepe-Tiska 2012).
Loss of Self-Consciousness
This component of flow could be described as the “loss of ego” or a “fusion with the world”. In flow, there is no room for self-scrutiny, and as we enter the state of optimal experience, one item that disappears from our awareness is concern for our own self (Csíkszentmihályi 1990). This is quite unusual, as we often spend considerable amounts of time and energy thinking about how we look, sound, act, etc. In the moment of flow, however, there is little opportunity for the self to be threatened.
This loss of self-consciousness does not mean that one has lost their sense of self, nor does it imply a loss of consciousness. Rather, a person in the flow experience loses their consciousness of the self (Csíkszentmihályi 1990, p. 64). This does not mean that a person experiencing flow has given up control of their mental energy, or unaware of what is happening in their body or mind. Instead, the concept of self, or the information we use to represent to ourselves and others who we are, slips below the threshold of our mental awareness.
Time: Loss of Time Awareness or Time Acceleration
One of the most common descriptions of flow is that one’s sense of the duration of time is affected (Csíkszentmihályi 1990; Ergeser & Schiepe-Tiska 2012). As our perception of the self changes, so too does the perception of time. While our attention is focused on the present, we lose our awareness of the passing of time (Hunter & Csíkszentmihályi 2000). Time can feel like it’s passing either slower or quicker than normal, an experience that the average reader has probably experienced quite frequently in his or her lifetime, depending on how positive or
negative the experience is. Or simply, time may be irrelevant and out of one’s awareness (Jackson & Marsh 1996).
Who among us hasn’t been out with friends, looked at their watch, and realized that it was much later than they expected? Or, conversely (and I imagine more common) who hasn’t experienced the dread of sitting through a boring and arduous meeting, where minutes seemingly turn in to hours? Timing and time-perception invokes not only cognition, but is internally connected to our emotional life (Droit-Volet & Meck 2007). This distortion of time is ever present in the flow experience, with people reporting numerous hours lost as they are immersed in their activity, be it practicing the guitar, painting a picture, or reading.
Clear Proximate Goals
When we set out to do an activity, we usually have a clear goal in mind to give us a sense of what we are going to do (Hunter & Marsh 1996). To paint a picture, a painter knows that he must transform a canvass into an artistic representation of an object, feeling, or abstract state of being, depending on one’s particular style. A baseball player knows he has to get on base, or move a baserunner over, or score a run. A commuter has to get to work, hopefully on time and without too much stress, or at least slink in late without being noticed. Goals are absolutely essential to most activities we partake. If an activity lacks tightly defined goals, our actions become diffused and aimless (Hunter & Csíkszentmihályi 2000). In other words, what are we doing out here?
In the flow state, clear goals inform which stimuli can be attended to and which can be ignored. To achieve the flow state, one needs logically-ordered goals and means of achieving them (Ergeser & Schiepe-Tiska 2012).
Unambiguous Feedback
Going hand in hand with clear goals, clear and unambiguous feedback about how we are performing our activity and whether we are succeeding is also required for the flow state (Hunter & Marsh 1996). We need feedback to evaluate our behavior: do we need to change our course of action or continue on as usual (Hunter & Csíkszentmihályi 2000)? Is a painter’s portrait resembling the subject? Did the baseball player get on base? Is the commuter making great time? No matter the activity, feedback provides information to tell us whether we are
succeeding or failing in our goals and is essential to the flow experience (Hunter & Marsh 1996).
Dynamic Balance Between Perceived Challenges and Skills
One of the most important components of the flow experience is the balance between challenges and skills (Hunter & Csíkszentmihályi 2000). A simple enough concept to understand on its own: we like challenges that suit our skills. We tend to shy away from activities that are way outside of our skill set for fear of failure and the ensuing embarrassment and shame that may come, or threat of personal injury in more serious and physically-challenging activities, and similarly avoid activities that are beneath our skill set as they are too boring or too easy, with no reward for completion. When challenges vastly surpass our perceived skills, we tend to feel a sense of anxiety. When the challenge is far below our skills, we tend to feel quite bored (see Figure 3).
Figure 3: Balance between challenge and skill is essential to flow. (motivateplay.com).
Csíkszentmihályi & LeFevre (1989) and Abuhamdeh & Csíkszentmihályi (2011) found that our most enjoyable activities tend to be those where our skills and challenges are evenly matched, with even more enjoyment derived from challenging situations slightly outside our skill range where we must perform at our very best, and even beyond it, in order to compete.
Similarly, situations and activities with both high challenges and high skills are found to induce more intense flow experiences compared to those with low challenge and low skills, despite being evenly matched (Moneta 2012).
This can be quite apparent in sports. Who hasn’t felt a sense of satisfaction from besting a tough opponent on the court, where we were able to overcome adversity and challenge to win? When both skills and challenges are high, a person not only enjoys the moment, but stretches their capabilities and increases the likelihood of learning new skills and increasing their self-esteem (Csíkszentmihályi & LeFevre 1989).
Where challenges and skills are evenly matched, one can enter in to the flow state.
Components of or Conditions For?
While there is agreement about the nine components above, Hunter & Csíkszentmihályi further refined the theory of flow breaking the nine characterizations into two: conditions for entering the flow state; and experiences of the flow state (2000).
Their research indicates four conditions for entering the flow state: concentration; goals; feedback; and balance of challenges and skills. The five remaining components of control, merging, autotelic, loss of self-consciousness, and time distortion are believed to be the ensuing experience of the flow state. One must meet the conditions of the first four components to fully experience the flow state and feelings and experiences associated with flow.
What this means precisely is that unless one is able to fully concentrate on the task at hand, has outlined clear goals, has a source of unambiguous feedback, and possesses an evenly-matched set of skills relative to the perceived challenges, it is not possible to enter in to the flow state
Modeling Flow
Over the years, there have been several methods developed to model the flow state. I’ll discuss a few of them below.
The first model from Csíkszentmihályi featured three states: anxiety, both when challenges were high and skills were low and vice versa; worry, when challenges were moderate and skills low and; boredom, when skills were moderate and challenges were low (see Figure 4).
Figure 4: The first model of the Flow State. (Adapted from Csíkszentmihályi 1975; in Moneta 2012).
The “sweet spot” of the model, the coveted “Flow channel” lied directly in the middle of the diagram, representing the ideal condition when both challenges and skills were even matched. Csíkszentmihályi later removed the “worry” and low-challenge/high skill “anxiety” labels, simplifying the model into the three states of anxiety, boredom, and flow (Moneta 2012).
Figure 5: The Quadrant Model of the Flow State (Adapted from Csíkszentmihályi & LeFevre 1989; in Moneta 2012).
A later model from Csíkszentmihályi & Lefevre (1989) divided the model into four “quadrants”, with anxiety, apathy, and boredom representing high-challenge/skill, low-challenge/low-skill, and low-challenge/high-skill situations, respectively (see Figure 5). Flow was determined to occur only when challenges and skills were both high. This model had
perceived strengths of being a relatively simplistic model to follow and allowed for simple testing of the flow theory. Perceived weaknesses, according to Moneta (2012) were that the model represents an approximate classification system, allowing for medium-challenge/high-skill flow situations and vice versa, and the related issue of the flow quadrant being overly-inclusive.
Figure 6: The Experience Fluctuation Model of the Flow State (Adapted from Massimini, Csíkszentmihályi, & Carli 1987; in Moneta 2012).
Another model of the flow state developed was the Experience Fluctuation Model from Massimini, Csíkszentmihályi, & Carli (1987) with eight labels according to perceived challenges and skills: arousal, anxiety, worry, apathy, boredom, relaxation, control, and flow (see Figure 6). This channel model provided a narrow operationalization of the challenge and skill balance, and more detailed characterizations of the non-flow states (Moneta 2012).
For purposes of this thesis, I highly prefer the modified version of the first and simpler model from Csíkszentmihályi (1975) in Figure 7 listing the three states of anxiety, boredom, and flow. The latter two models, while being more detailed with their own respective strengths and weaknesses, are better suited to students with a greater background in psychological research.
2.5 Comfort-Flow Relationship
After defining the conditions and characteristics of the flow state, we are ready to dive in to the main theory underpinning this thesis: the relationship between cyclist comfort and the flow state. I believe that in order for cyclists to enter the flow state, they must be comfortable enough to satisfy the four conditions necessary to experience flow: concentration on the task at hand, clear goals, unambiguous feedback, and a balance of challenge and skills. I think the two bookending conditions, concentration and balancing challenges and skills, are of particular importance to cycling and are absolutely crucial for a cyclist to enter flow.
As previously discussed, research indicates that bicyclists prefer to ride on safe routes (Tilahun et al. 2007; Emond et al. 2009; Broach et al. 2012; Mertens et al. 2016) with both less physical (Sorton & Walsh 1994) and mental (Heinen et al. 2011) effort and stress. Similarly, cyclists prefer to avoid routes they perceive as dangerous and stressful (Larsen & El-Geneidy 2011; Joo et al. 2015). Further, cyclists heavily favor physically-protected and separated infrastructure that protects them from automobile traffic (Gatersleben & Appleton 2007; Wardman et al. 2007; Emond et al. 2009; Winters et al. 2011; Li et al. 2012; Caulfield et al. 2012; Mertens et al. 2016; Vedel et al. 2017).
Figure 2: The Flow Channel Wave. (Adapted from Csíkszentmihályi 1975.) Image from "The Art of Game Design" by Jesse Schnell (gamasutra.com)
The relationship between these two trends, a desire for safe, stress-free, and comfortable routes and a strong desire for physically-protected and/or separated cycling paths goes hand in hand and doesn’t require much explanation. Car traffic is a major source of stress for cyclists as it represents a direct threat to their material well-being and safety, and outside the most hardcore of cyclists, such as the “Strong and Fearless” 1% identified by Geller (2006), most people prefer not to take their chances battling it out among cars. The more protected the path is, the further away from traffic it is, and the number and speed of cars on a route all factor into a cyclist’s perceived safety.
Let’s examine this in relation with the first condition to enter flow: concentration on the task at hand. Csíkszentmihályi’s research explicitly indicates that constant worry about external threats and stresses prevent someone from entering into the flow state (1990; Hunter & Csíkszentmihályi 2000). Flow occurs when our attention can be freely invested in our task because we have no disorder to straighten out, or a threat to the self to defend against. I would argue that traffic stress and fear of being hit and possibly killed by a car would weigh quite considerably on the mind of a cyclist riding amongst traffic and present a formidable barrier preventing them from entering flow.
It’s not a hard concept to consider, as one would say it’s quite difficult to really focus on something when your physical safety is in jeopardy. Many consider speeding automobile traffic whizzing by, mere centimeters away, to be a distraction, to say the least. With a cyclist commuting to work on a painted bike path, wedged in between parked cars on one side, and speeding motor traffic on the other, he or she cannot focus the energy of their attention on the present, that is the act of cycling. Instead, their mental energy is consumed by a fear of being hit by a passing car, a door being flung open in their path from a parked car, or buses pulling in and out of traffic in front of them. All these very real, dangerous, and possible potential scenarios on the commute to work are significant barriers to providing the full concentration necessary for flow.
Going hand in hand with concentration would be the condition of an even balance between challenges and skills. Again, let’s use the example of a narrow painted bicycle lane placed on the roadway between parked cars on one side and speeding motor traffic on the other, an all too common excuse for bicycle infrastructure in the United States. One could quite reasonably say this scenario presents a high level of challenge for all but the most fearless of cyclists.
We know from Csíkszentmihályi and LeFevre that experiences will be the most positive when one perceives that challenges presented before them are evenly matched with their perceptions of their own skills (1989). Cyclists, like all people, are diverse and varied, and thus have varying levels of skills and preferences (Geller 2006). Some cyclists may consider themselves highly-skilled “vehicular cyclists”, preferring to ride their bicycle at great speed in general traffic lanes amongst cars as if they themselves were a car, while other, lower-skilled cyclists may prefer to avoid interactions with cars as much as possible, riding on off-street paths completely separated from automobile traffic, with numerous types of cyclists in between.
For an average cyclist attempting to navigate on a painted lane on a busy street, they may feel that their cycling “skills” are not quite up to par to meet the challenges of riding between a lane of motor traffic and parked cars. Using the Flow Channel model previously presented in Figure 7, they would be considered firmly within the “Anxiety” area, representing a scenario with high challenges and low skills. They may compensate for this lack of skills by riding on the sidewalk (separating themselves from the threat of motor traffic as much as possible), choosing a more comfortable route that may take them out of their way, or as is all too common of a case in the US, avoiding cycling altogether.
In contrast, protected cycling paths or lanes would present a much less challenging situation for cyclists. These barriers, be they as flimsy as a plastic bollard to as secure as a physical curb or a line of parked cars, help separate cyclists from motor traffic and physically protect them from the threat of motor traffic with an actual barrier to keep intruding cars out. This protection and separation, I would argue, considerably lowers the challenges of cycling and the subsequent skills necessary to cycle comfortably and smoothly. This arrangement allows cyclists to focus on things other than their potential impending doom at the hands of an errant or careless motorist. With skills and challenges evenly matched, the potential to entering the flow state would be greatly increased, while simultaneously providing a more hospitable environment for potential cyclists.
2.6 Conceptual Framework
Based on the research above, the following models represent the conceptual framework of my thesis. We know what factors influence a cyclist’s speed to include levels of stress and general
comfort while cycling (see Figure 8). This stress and comfort, I argue, also plays into the ability to enter in to the flow state. The four conditions necessary for flow are concentration on the task at hand, clear goals, unambiguous feedback, and a balance of challenges and skills (see Figure 9). When cyclists are highly stressed, most often by motor traffic, they are unable to focus their attention on the activity at hand while feeling that their skills are not evenly matched with the challenging environment around them, and will feel anxious (see Figure 10). Thus, with these two conditions unable to be fulfilled on cycling paths without physical protection or separation from motor traffic, the flow experience is next to impossible.
These three models will guide my research design and subsequent thesis.
Cycling Speed
Personal Factors
Environmental Factors
Congestion Traffic Topography BicycleType Fitness & Health
Time Stress & Comfort
Facility Quality
Cy
cl
is
ts
2.7 Research Question
As cities around the world begin to transform their autocentric transportation networks by constructing bicycle infrastructure, they will have to make important decisions regarding level
Balance
Goals
Feedback
Concentration
Flow
Control
Merging
Autotelic
Self-Consciousness
Time
Figure 9: Conditions and Components of Flow. Adapted from Csíkszentmihályi 1975; Csíkszentmihályi & Csíkszentmihályi 1988; Jackson & Marsh 1996; Hunter & Csíkszentmihályi
2000; Moneta 2012. Image from author.
Figure 10: The Flow Channel Wave. (Adapted from Csíkszentmihályi 1975.) Image from "The Art of Game Design" by Jesse Schnell (gamasutra.com).
of protection to offer cyclists, which routes to choose, how much of their overburdened road space to take away from cars, and other such considerations regarding the quality of their infrastructure.
In many parts of the world, particularly in the United States, what passes as bicycle infrastructure in the minds of some transportation planners and/or mayors and councilmembers is nothing more than a narrow lane wedged between parked cars on one side and speeding automobile traffic on the other, with no barrier in between other than a layer of paint. Often times, not even this meager form of infrastructure is provided, leaving cyclists to fend for themselves among general traffic as they rely on “sharrows” painted on the roadway reminding car drivers that cyclists may use the full lane or a “Share the Road” sign as their only protection from cars (see Figure 11). Perversely, lane miles of these “sharrows” and other such non-infrastructure are frequently counted in a city’s statistics of lane-miles of bicycle non-infrastructure.
Figure 11: Shared-lane markings, or "sharrows" and road signs are often the only form of bicycle infrastructure in many US cities. Images from placematters.org and wikipedia.org, respectively.
These excuses for bicycle infrastructure, in my mind, do not tend to consider the actual user experience of the cyclist and seem more oriented for a “check the box” form of bicycle infrastructure, boosting the quantity of lanes and lane-miles to boast about on a city’s Department of Transportation page, rather than actually improving safety or roadway conditions. Politicians from both branches of government are risk-averse (Coate & Morris 1999; Ciccone 2004; Sjöberg, L & Drottz-Sjöberg 2008; Bøggild 2016) favoring the status-quo over any transformational change. Marginal, incremental change to the transportation network in the form of painted lanes and measures like these are seen as doing something for bicycling, without actually putting up a political fight. Further, these lanes are seemingly
designed for the “Fearless & Strong” cyclists mentioned by Geller (2006) and paint the picture of cycling as a high-challenge sport, rather than a low-challenge form of transport, requiring high speeds on expensive featherweight bicycles with skinny tires, a uniform of tight, garish sweat-wicking spandex, and a strong will and physical fitness to race amongst speeding traffic. This distorted image of cycling serves as a particularly notable barrier to increasing cycling participation rates (Gatersleben & Appleton 2007).
If transportation planners and politicians wish to build more safe, comfortable, and overall enjoyable bicycling infrastructure targeted towards more “lower-skilled” cyclists, I believe it is important to take the concepts of comfort and flow in to consideration. Csíkszentmihályi believes that the flow state provides the optimal experience, and it is on this basis and previous research above that lead me to believe that conditions that facilitate flow will also produce high-quality bicycle paths that allow cyclists to cycle at their own pace. Thus, the research in my thesis is guided by the following research question:
How does quality of infrastructure and separation from motor traffic influence flow?
As protection and separation from vehicle traffic increases (e.g. painted lanes with no separation or protection of any kind all the way to lanes and paths separated from motor traffic with a physical barrier), are challenges lowered to the point that cyclists in low-cycling cities are more able to enter into the flow state? Do cyclists in high-cycling cities such as Amsterdam have higher skills, and thus require higher challenges to enter in to the flow state? If so, could this be related to a matter of comfort on cycling paths? And, could this allow them to cycle slower than on unprotected paths? This leads me to form three hypotheses which will be confirmed or denied by my research:
1. As protection and separation from motor traffic increases, then cyclist speeds will decrease
2. As the perceived challenge level of cycling decreases in low-cycling cities, the chance of entering flow will increase
3. As the perceived challenge level of cycling increases in high-cycling cities, the chance of entering flow will increase
The logic behind these hypotheses is easy to follow. Knowing that cyclists tend to prefer cycling paths and infrastructure with a barrier that physically and spatially separate them from motor traffic, except in Amsterdam (Ton et al. 2016), it seems to follow that they are more comfortable on these routes and thus, more able to cycle at their own pace while at the same time more likely to enter in to flow.
Cyclists in cities with low amounts of cycling, such as Washington, DC, may feel like their skills are not in line with the challenges that cycling may offer. Increasing protection in these cities would lower the perceived challenges of cycling to be more in line with the perceived skills of cyclists, to the point that they can enter the “flow channel” and the flow experience (see Figure 12).
Figure 12: Cyclists in DC have lower skills relative to challenges and face anxiety while cycling. Would lowering the challenge facilitate flow? Image from Jesse Schnall and edited by the author.
Conversely, in the high-cycling city of Amsterdam, do cyclists find that their skills far exceed the challenges offered to them with their extensive network of protected and separated cycling paths and thus feel bored while cycling (see Figure 13)? If so, would the answer be to increase the challenge of cycling, by removing protection and separation?
Figure 13: Cyclists in Amsterdam may have higher skills relative to challenges. Would increasing the challenge facilitate flow? Image from Jesse Schnall and edited by the author.
When cyclists feel safe and comfortable, they are able to take their minds off of concerns about motor traffic and focus on the more pleasant aspects of their journey.
3. Methodology
The following chapter describes the research methodology undertaken for the thesis, the selected case studies chosen to examine the hypotheses, the methods employed to collect data, and the methods of analysis used to answer the main research question.
3.1 Case Studies
To test my hypotheses, I chose two cities that I am intimately familiar with: Washington, District of Columbia, USA in North America and Amsterdam, Netherlands in Europe. These two cities were chosen for several reasons.
The main reason is that I believe both cities would be instructive to looking at cyclists in two different contexts: one city with a developing and emerging bicycle network and another with a well-established bicycle network, representing low and high challenge cycling contexts. Both cities are national capitals of their respective countries and are of similar size and population: Washington is 68.34 square miles (177 km2) with a population of 680,000 and Amsterdam is 84.68 square miles (219.32 km2) with a population of 850,000 (US Census 2016; CBS Statline 2017). Further, I currently live in Amsterdam and previously lived for over eight years in the District of Columbia, and thus very familiar with bicycling in both cities.
I decided to look at three different types of bicycle infrastructure in each city to measure cyclist speeds and survey cyclists regarding comfort, stress, and flow. In both Washington and Amsterdam, I looked at a route with a protected bicycle lane or cycletrack separated from motor traffic, a painted on-street bicycle lane with no physical barrier or separation, and a completely off-street bicycle path. In Washington, the study corridors selected were 15th Street, NW, 14th Street, NW, and the Metropolitan Branch Trail, respectively (see Figure 14). In Amsterdam, I studied Weesperstraat, Rozengracht, and Vondelpark (see Figure 15). Though not entirely similar in terms of motor vehicles per day, width, and the like, I tried to control as best as I could for similarity between the lanes for accurate comparison.
Figure 14: Selected bicycle routes for study in the District of Columbia from left to right: 15th Street, NW; 14th Street, NW; and the Metropolitan Branch Trail (maps.google.com).
Figure 15: Selected bicycle routes for study in Amsterdam from left to right: Vondelpark, Rozengracht, and Weesperstraat (maps.google.com).
3.1.1 Washington, DC
Washington, DC is the seat of the US federal government. A dense, compact city of 680,000 American citizens denied representation in their national legislature that was founded before the invention of the automobile, the District of Columbia is one of the more walkable and bikeable major cities in the United States. Spared the majority of the destructive urban freeways in the 1950’s and 1960’s in favor of the mass transit Metrorail system, the city and its residents have favored more sustainable forms of transportation and currently boasts one of the higher mode shares of people commuting on public transit, walking, or bicycling in the country (District Department of Transportation 2014a; McKenzie 2014).
Bicycle facilities were made a priority of the Adrian Fenty mayoral administration from 2007 through 2011. Over that span, bicycling facilities in the District increased from 24.7 miles (or 39.75 km) to 51.3 miles (or 82.5 km) as cycling mode share rose from 2% to 3.3% (see Figures 16 and 17; District Department of Transportation 2014a). Subsequent mayoral administrations were less dedicated to cycling, though progress has still been made with mode share and cycling facilities, but not at the same speed or urgency. Latest figures from the District’s Department of Transportation show that cycling mode share is at 6% as of 2016 (District Department of Transportation 2017), though this number is likely to have risen as more facilities are installed and woes with the region’s Metrorail system force riders to alternative modes. The District now has about 80 miles (~128 km) of bicycle infrastructure, with about seven miles (11.2 km) of protected lanes (J. Sebastian, District Department of Transportation, personal communication, June 19, 2017; see Figure 18). Their long term goal is to have 136 miles (219 km) of bicycle lanes, 72 miles (116 km) of protected bicycle lanes, and 135 miles (217 km) of trails by 2040 (District Department of Transportation 2014b).
Figure 16: The miles of bicycle facilities and percentage of residents biking to work has steadily increased since 1990. (DDOT 2014a).
Figure 17: Mode share comparisons in the District of Columbia since 1990. Cycling increased from 0.75% in 1990 to 4.54% in 2014 and has likely risen. (DDOT 2014a).
Figure 18: Existing bicycle network of the District of Columbia as of 2014. Red represents painted bicycle lanes; blue represents protected cycletracks; pink represents shared lanes. (DDOT 2014b).
15th Street, NW: Protected Bicycle Lane
The first protected bicycle facility in the District of Columbia was installed on 15th Street, NW in 2009. The lane, protected from motor traffic by a combination of plastic bollards and parked
cars, stretches over two miles from the bustling U Street neighborhood all the way past the White House to Pennsylvania Avenue, NW. Originally installed as a southbound contraflow lane, the lane’s immense popularity soon prompted a change to a two-way configuration the following year (Goodno, McNeil, Parks, & Dock 2013). 15th Street, NW varies in its traffic configuration from the downtown to more residential portion of the District, and motor traffic has around two to three lanes depending on location (see Figure 19). According to 2014 figures from the District Department of Transportation, this portion of 15th Street, NW sees about 7,300 vehicles per day (2014c).
Figure 19: 15th Street, NW looking north at P Street, NW. Two-way cycletrack is on the left. (maps.google.com)
14th Street, NW: Painted Bicycle Lane
14th Street, NW is a major commuter artery in the District of Columbia, seeing over 21,100 vehicles per day (District Department of Transportation 2014c). The street has two lanes of motor traffic in both directions with a lane for curbside parking on both sides of the street. Painted bicycle lanes are located on both sides of the street between parked cars and general motor traffic (see Figure 20).
Figure 20: 14th Street, NW looking north at Q Street, NW. (maps.google.com).
Metropolitan Branch Trail: Off-Street Path
The Metropolitan Branch Trail is an eight mile (13 km) long on and off-street multi-use trail located on the right-of-way of the former Metropolitan Branch of the Baltimore & Ohio Railroad, that, when completed, will run from Union Station in the District of Columbia north to Silver Spring, Maryland along completely separated paths (see Figure 21). The majority of the path lies in the District among a mix of on-street and off-street paths between industrial buildings on the western side and active freight and passenger rail lines on the east. The trail serves as an important commuter connection for cyclists riding to downtown DC and connects with other bicycle lanes in the District’s bicycle network as well as several Metro stations.
Figure 21: An off-street portion of the Metropolitan Branch Trail, looking north, at S Street, NE. (lifeontheedgewood.blogspot.com).
3.1.2 Amsterdam
Amsterdam, the Dutch capital city, is perhaps the most famous and recognizable cycling city of the Netherlands and the world. A dense and compact city built around a network of picturesque canals and small, narrow streets, cycling has historically been a popular and practical mode of transport for Amsterdammers.
Though popular today, cycling in Amsterdam has not returned to its pre-war levels of mode share. As mass motorization took off in the Netherlands in the 1950’s and 1960’s, car traffic flooded Amsterdam and other major Dutch cities and cycling rates fell as traffic deaths rose precipitously. Nationwide, over 3,000 people were killed in traffic deaths in 1971, of which 450 were children (“Amsterdam’s Cycling History”). In response to massive public outcry and demonstrations, Amsterdam embarked on an extensive public safety campaign that calmed traffic on the majority of city streets, took away road space from private cars for other modes, and constructed Amsterdam’s extensive network of bicycle paths.
Today, the city boats over 470 miles (767 km) of cycling paths and bike lanes, of which 513 are dedicated cycling paths, as well as several parks with cycling paths through them. Nearly 60% of Amsterdammers over the age of 12 cycle daily and 83% cycle at least once a week.
Weesperstraat: Protected Bicycle Lane
Weesperstraat is a major street in Amsterdam that was widened in the 1960’s for use as an expressway that was planning to cut through the Nieuwmarkt neighborhood, though these plans were cancelled due to public outcry and demonstrations. Now it serves as a commuter artery into the center of Amsterdam. The street features a protected bicycle path on both sides of the
street, physically separated from traffic between the sidewalk and general traffic (see Figure 22).
Data collected from cyclists during Fiets Telweek found that the average cycling speed on this street was between 18 and 20 kmh (11.18 and 12.4 mph) in 2015 and mostly over 20 kmh at certain sections in 2016 (Fiets Telweek 2016).
Figure 22: Weesperstraat, looking north at Nieuwe Kerkstraat. (maps.google.com).
Rozengracht: Painted Bicycle Lane
Rozengracht is a major street running through the Jordaan neighborhood between the Lijnbaansgracht and Prinsengracht canals. Once a canal itself, it was filled in during the 1890’s and now carries one lane of traffic in each direction along with two tram lines down the middle and a row of parking for cars on both sides. Rozengracht has an unprotected painted bicycle lane that runs between parked cars and general motor traffic (see Figure 23).
Cyclists cycled on this street at an average of more than 20 kmh (12.4 mph) for the majority of the route in 2015 and 2016, with slight increases of speed at the eastern and western ends of
the street, going from an average of 16 and 18 kmh (9.94 and 11.18 mph) in 2015 to between 18 and 20 kmh (11.18 and 12.42 mph) (Fiets Telweek 2016).
Figure 23: Rozengracht looking east at Tweede Rozendwarsstraat. (maps.google.com).
Vondelpark: Off-Street Path The Vondelpark is the major urban park of Amsterdam, located in the Amsterdam-Zuid neighborhood, that sees over 10 million visitors annually. Though not officially designated as a bicycling path, the meandering paths through the entirety of the Vondelpark serve as crucial and convenient connections for commuters riding east-west (see Figure 24).
Average cycling speeds recorded by Fiets Telweek in 2015 and 2016 were more relaxed, with cyclists riding at average speeds between 18 and 20 kmh (11.18 and 12.42 mph) (Fiets Telweek 2016).
3.2 Research Design
To answer the main research and sub-questions, I employed a variety of qualitative and quantitative inductive research methods, including direct observation of cyclist speeds on different roadways in my two case studies, Washington, DC and Amsterdam, semi-structured interviews with cyclists I both encountered on the street and scheduled through flyering, and
Figure 24: A multi-use path in Vondelpark. (aseasyasridingabike.wordpress.com).
intercept surveys of cyclists. This represents a comparative case study looking at the differences and similarities between the two cities.
My units of analysis were commuter and utilitarian cyclists, or those using a bicycle to travel to work or education and/or run daily errands. I chose to exclude cyclists riding for sport or recreational purposes as they tend to have different motivations and goals of cycling than commuter and utilitarian cyclists (Ayachi et al. 2015). This is not to say that comfort levels of recreational cyclists aren’t interesting or valuable for flow research, but rather a reflection of different motivations for my research. To discern the two types of cyclists from each other, I relied on observations of their clothing style (lycra and spandex), type of bicycle they were riding (carbon-fiber, racing-style, skinny-tires), and other factors that signaled a purpose other than commuting.
Observations
Direct observation of cyclists occurred on the three routes mentioned in Section 3.1 in each city during the morning and evening rush hours, between 7:30 AM and 9:30 AM and 4:30 PM and 6:30 PM, respectively, over the course of three days. On each route, I measured and marked off two points 200 feet (or ~61 meters) apart and found a visible vantage point in-between to measure how fast randomly-selected cyclists moved between the two points. Speed was then calculated from these figures.
Jan Gehl found that walking speed and the amount of time spent in a location can provide information about the quality of a space, claiming that people walk slower and stay longer in places relative to the qualities and pleasures offered (1968; Gehl & Svarre 2013). I imagined that the same logic could apply to cycling speeds and comfort on different cycling facilities.
This data was collected and analyzed in Microsoft Excel to determine the average time and speed on a route and the resulting median, range, and standard deviation, as well as any outlying speeds on the different routes. Results between the two cities were compared.
Interviews
I also conducted a series of semi-structured interviews asking respondents a series of questions mostly regarding their likes and dislikes about cycling, their preferences for cycling infrastructure, and whether they had ever experienced any of the components of flow while
