Cycling As a Cooperative

DEGREE PROJECT IN THE BUILT ENVIRONMENT, SECOND CYCLE, 30 CREDITS

STOCKHOLM, SWEDEN 2020

CYCLING AS A COOPERATIVE

ACT

Observing cyclists' interactions with pedestrians at a zebra crossing in Stockholm

EDWARD PRICHARD

KTH ROYAL INSTITUTE OF TECHNOLOGY

SCHOOL OF ARCHITECTURE AND THE BUILT ENVIRONMENT Table of contents

Abstract...... 3 List of images, figures, and tables ...... 4 Preface ...... 5 Introduction ...... 7 Background and context ...... 7 What’s the problem? ...... 8 Aim of the thesis ...... 9 Delimitations of the study...... 9 Structure of the paper ...... 9 Impact of Covid-19 ...... 10 Ethics of the study ...... 11 Theory ...... 11 The practice of cycling ...... 11 The street as a social space ...... 14 Method ...... 17 Ethnomethodology ...... 17 Observations ...... 17 Observations in this study...... 18 The Study ...... 21 Observation sessions ...... 21 The time periods ...... 23 The location ...... 24 In-person Observations ...... 26 Video and Observiaire ...... 28 Data ...... 32 Results and Analysis ...... 33 Sociability ...... 33 Efficiency ...... 38 Final thoughts ...... 42 To note ...... 42 Discussion ...... 44 Strengths ...... 44 Limitations ...... 44 Further research ...... 45 Recommendations...... 45

Conclusion ...... 47 Reference List ...... 48 Appendices ...... 54 Contents ...... 54 Appendix 1, In-person observation template ...... 55 Appendix 2: Observation 1, Preliminary Studies ...... 57 Appendix 3: Observation 2, Traffic Count ...... 58 Appendix 4: Observation 3, Pilot Study...... 60 Appendix 5: Observation 4, Lunchtime ...... 62 Appendix 6: Observation 5, Morning ...... 66 Appendix 7: Observation 6i, Afternoon ...... 70 Appendix 8: Observation 6ii, Afternoon...... 72 Appendix 9: Time Periods...... 75 Appendix 10: In-person observation, collated results ...... 76 Appendix 11: Issues and recommendations ...... 78 Appendix 12: Observiaire amendments and removals ...... 78

Abstract

Cycling is undergoing a welcome renaissance, especially in urban contexts. However, there are tensions, in relation to pedestrians, which could negatively affect cycling’s growth. This thesis observes the social interactions and physical reactions of cyclists when co-present with pedestrians at a zebra crossing in central Stockholm. It uses both in-person and video observations with the films being processed using an observiaire, a relatively novel, quantitative method of capturing human behaviours. The results were explored using ideas on the practice of cycling and the street as a social space. It seems that cyclist’s momentum and desire to save energy is clearly important as cyclists will do almost anything except stop for a pedestrian. However, they also seem to have an ability and wish to cooperate. This could be using waves, nods, or shouts, but also invisible and physical communication, what I term peripheral communication. Overall, the cyclists observed were constantly balancing their desire for efficiency against their consideration of pedestrians.

List of images, figures, and tables

Images

Image 1, One of the locations trialled in Observation 1.………………………………... 23 Image 2, Location of the observations within the city centre of Stockholm…………... 25 Image 3, Satellite image showing the junction, and the different forms of pedestrian and cycling infrastructure 25 ……………………………………………………….. Image 4, View of the location from the northbound pedestrian’s perspective, looking towards 26 Vasabron.……………………………………………………… Image 5, View of the location from the southbound pedestrian’s perspective, looking from Vasabron………………………………………………………….. 26 Image 6, View of pedestrians and a cyclist interacting at the zebra crossing, from 27

Riddarhuskajen………………………………………………………..………….. Image 7, Observing and videoing the zebra crossing ………………………………….. 28 Image 8, Screenshot of the observiaire’s contextual variables…...…………………….. 29 Image 9, Screenshot of the observiaire’s behavioural variables………………………... 31

Tables & Figures

Table 1, Each observation session’s time and 24 flow……..…………………………...….. Figure 1, Comparing the percentage of social interactions across different flows when one or more pedestrians are 35 present……………………………... Figure 2, Comparing the percentage of specific social interactions across different flows when one or more pedestrians are 37 present.…………………………….. Figure 3, Comparing the percentage of physical reactions across different flows when one or more pedestrians are present.…………………………………… 40 Figure 4, Comparing the percentage of specific physical reactions across different flows when one or more pedestrians are 42 present……………………………..

Preface

This thesis was written as the final piece of work in my MSc in Sustainable Urban Planning and Design at KTH in Stockholm, Sweden. My academic supervisor was Martin Emanuel, my first thanks go to him for introducing new concepts to me, pushing me to go further and calmly reassuring me that I was on the right track when I was a little lost.

This research was done in partnership with the construction consultancy WSP and was written at their Stockholm’s office - at least until the Covid-19 pandemic forced us all work from home! My supervisor at WSP was Fanny Larsson and she was a constant source of support, guidance, and encouragement. Massive thanks go out to her for this. She also helped me with the observation sessions and therefore I may refer to ‘we’ at certain times throughout the thesis. Thanks also go to all of my colleagues there who helped me feel welcome and lent me the equipment needed.

More generally, my thanks also go to my friends and family who have been willing to put up with my insistence of shoehorning the importance of cycling into any conversation topic over the years. Thanks go to my classmates on my course who have been a great support circle - I’m amazed how well we’ve all done considering everything that was going on in the world during this all. Most of all however, my thanks go to my partner Malin who has supported and helped me a great deal throughout the process, giving her time and energy even when she had little herself.

“Cycling is possibly the greatest and most pleasurable form of transport ever invented. It’s like walking only with one-tenth of the effort. Ride through a city and you can understand its geography in a way that no motorist, contained by one-way signs and traffic jams, will ever be able to. You can whiz from one side to the other in minutes. You can overtake £250,000 sports cars that are going nowhere fast. You can park pretty much anywhere. It truly is one of the greatest feelings of freedom one can have in a metropolitan environment. It’s amazing you can feel this free in a modern city.” Kieran and Hodgkinson (2010), The Book of Idle Pleasures

Introduction

Background and context

After spending decades on increasingly congested roads and in packed buses and subway trains, more and more travellers are enjoying a newfound sense of freedom. Cycling is undergoing something of a renaissance in recent years with higher numbers and broader academic attention (Pucher J & Buehler R, 2012, p46; Handy et al, 2014). The explanations for this trend are complex and have been widely debated in academic circles – however the key points are worth outlining briefly at this point.

For the individual, the low cost involved in travelling by bicycle makes it of benefit to poorer groups, who struggle with the cost of transport – both public transport and the cost of owning a private car. It also leads to physical health benefits as people can easily incorporate exercise into their daily routine rather than sitting in a car while they commute (which some estimate could make you 13% more likely to become overweight (Garrard et al, 2012)). Finally, it gives the user a sense of freedom and control over their mobility, allowing them to avoid traffic and easily predict their arrival times at their destination.

For society, which is in a worsening climate crisis, transport is emerging as problem area. It is the second largest producer of greenhouse gas emissions globally (C2ES, nd) and in Sweden (SCB, 2019), yet the bicycle provides us with possibly most efficient vehicle in the world (Whitt and Wilson, 1982 cited in Nixon, 2012). Completely human powered, virtually silent, and efficient in terms of road space the CO2 savings are compounded by reduced noise pollution, air pollution, and traffic – all of which comes with economic and societal benefits (Garrard et al, 2012). Its final societal benefit is quite simple, it is cost effective – the infrastructure is relatively cheap (Börjesson & Eliasson, 2012) and the benefit cost ratio is estimated to be as high as 5:1 (Garrard et al, 2012).

These arguments are being recognised at various governmental levels: internationally, the EU wants to grow cycle use by 50% between 2019 to 2030 (ECF, 2017); nationally, Sweden has drawn up a national cycling strategy (Government Offices of Sweden, 2017); and locally, Stockholm aims to have at least 15% of peak hour journeys will be by bike by 2030 (Stockholms stad, 2012).

This is manifesting itself in the creation of new policy and the construction of new infrastructure across Sweden and within Stockholm. In recent years new bicycle routes have popped up across the city, sometimes even created with the removal of lanes that used to be for vehicular traffic. However, thanks to political decisions made in late 1970s, there are many cases where cyclists still share spaces with pedestrians (Emanuel, 2019). Often, they are on the same level, with a small, raised section or often just painted lines. This means there are many crossing points between the two modes, both formal (such as zebra crossings to get to a bus stop) and informal (such as desire lines). As population increases and cycling numbers rise in Stockholm it is likely that we will see an increase in different interactions and reactions based upon each other’s presence and behaviours.

One problem however is the dominance of rational or modernist traffic planning when it comes to the planning, design, and maintenance of these infrastructures (Spinney, 2009; 2011; Emanuel, 2019). This typically expresses itself in research focused on quantitative data - where bikes go, how many do so, accident numbers - and cycle infrastructure built upon the needs and demands of vehicular traffic (Brown & Spinney, 2010; Spinney, 2011). Mobility - the study of people moving (Spinney, 2006) – in general, lacks an understanding of how cyclists behave, especially in an urban context.

If we can see design as a conversation, a back and forth between the designer and their projected idea of a user, and the actual user (Norman, 1988; Akrich, 1992, pp208-9), then it could be argued that modern cycle planning is overlooking the actual users (Forsyth & Krizek, 2011). Rather than moulding itself to the actual and desired behaviour of its users, it is trying to mould their behaviour to itself. This is the argument made by Forsyth & Krizek (2011) who argue that cyclists have different design needs than other road users and the knowledge of these needs is lacking – including amongst practitioners, as has been raised by my supervisor at WSP.

What’s the problem?

There is a lack of understanding, both in academia and in practice, of cyclists needs and capacities as well their behaviours within existing bike infrastructures. But why is that important? Put simply, much as good design needs input from both the designer and the user, you cannot build infrastructure for people if you don’t understand how they will behave when they are using it.

This is pertinent if you consider the bike as a unique form of transport, which I will argue for later in the thesis but shortly put, the bike is neither pedestrian nor vehicle, it is a human- machine hybrid - highly flexible and intimately linked to the physical nature of its rider and their physical surroundings (Brown, 2012; Larsen, 2018; 2019). Therefore, the spaces designed for cycling cannot be evaluated in the same ways as other forms of transport. The spaces must be based upon something else, perhaps this could be something more human. There has to be an understanding of these spaces as social spaces, for if humans are social then all the spaces, they inhabit become social spaces.

As the number of cyclists increase in Stockholm there may be an increase in interactions between pedestrians and cyclists. Some of these will be positive and some may be problematic. Either way there is something here that could be observed. Partly because road design can include the user’s actual behaviour and interactions within the process, and partly because there is a history of misunderstanding between these two modes which has led to a discourse of conflict. This conflict is seen when there are booms in cycling and the spatial limitation of cyclists and pedestrians sharing spaces are exposed. This discourse of conflict contributed to the decline of cycling at those times (Emanuel, 2019), yet we can see the discourse potentially continuing today (te Brömmelstroet et al, 2014; Blume, 2017; Balkmar & Summerton, 2017) despite possible evidence that cyclists don’t break traffic rules as much as motorists (te Brömmelstroet et al, 2014; Marshall et al, 2017).

To avoid another decline in cycling, we need to observe and analyse how cyclists interact with those around them and how the spaces they cohabit are not merely traffic spaces but social spaces (Monderman cited in Hamilton-Baillie, 2004). In this thesis, zebra crossings will be used to explore this further.

In a paper by Weilenmann et al (2014), people using revolving doors are observed. These spaces force walkers together at a sort of pinch point, which leads to novel and interesting behaviours. The zebra crossing exists in a similar way, forcing interaction and reactions due to its user’s proximity, it’s just that in this case it’s between two different modes of mobility not one. The space is not controlled by signals or technology. The decision on who should go where and when is influenced by established formal rules or norms. Crucially however, as will be argued in this thesis, the interpretation of these are decided informally, through social interactions. Sometimes a pedestrian will yield to a cyclist, though they don’t have to, and sometimes a cyclist will carry on through the crossing with a pedestrian present, though they shouldn’t.

Whilst it is important to consider that there is a lack of understanding of how cyclists behave within existing bike infrastructures, it is also important to recognise that this behaviour will change depending on their context. For this reason, comparisons should be done within the study so that we’re not just taking a snapshot of one time.

The comparison point I have chosen is flow - a form of measurement that looks at the number of vehicles which pass a certain spot in a certain amount of time. For example, it could be expressed as, 144 bikes per hour cross the North Bridge. Flows are a valuable characteristic that are ‘basic to any public life study’ (Gehl & Svarre, 2013). Different masses of other road users can lead to different behaviours, for example Larsen (2017) studies how there is certain competency needed to cycle in high flows. It is also a useful comparison tool that allows us to see whether urban space is used differently at different times.

Flow is commonly used in mobility and observational studies as a technical point of reference. For example, Dutch regulations demand bike lanes must be installed when the flow of vehicles on a street reaches a certain level (Furth, 2012); to show the influence of traffic flows on social connections within a street (Gehl and Svarre 2013); or even in ideas around critical mass or safety in numbers (Furth, 2012).

Aim of the thesis

The aim of this thesis is, to better understand cyclist’s social interactions and physical reactions when co-present with pedestrians.

Its objectives are:  To video different flows of urban cyclists at a pedestrian zebra crossing in Stockholm.  To perform an observiaire1 upon these videos looking at cyclists’ social interactions with, and physical reactions to, pedestrians.  To analyse the results by conceptualising the street as a social space and considering the social practice of cycling.

The research questions it hopes to answer are:  How do cyclists interact with and react to pedestrians at zebra crossings?  How do these reactions and interactions vary in different flows?  How do cyclists create zebra crossings as social spaces?

Delimitations of the study

This is not a thesis which will recommend a set of measures or design a new form of bicycle infrastructure; this thesis will observe and analyse current behaviours so that these findings can be useful to those who will.

It will focus on cyclists and their behaviours when pedestrians are present, rather than focussing on cyclists and pedestrians’ behaviours. The difference in focus is a subtle but important one. Vehicular traffic and the various new forms of personal transport (electric scooters, skateboards etc.) are also excluded from this study. This isn’t to say that these wouldn’t be worth studying, just that it isn’t observed here.

Structure of the paper

1 Explained below.

To ease the readers understanding of this thesis, I will here outline its structure and explain what can be found in each section.

Theory In the theory section I will outline two concepts. First is the ‘practice of cycling’, a look at the actual act of cycling and the experiences and feelings it elicits. The second is the ‘street as a social space’, the idea that the street is and should be seen as a space that is socially constructed through human and technological interactions.

These are divided into sub sections which will look at particular facets of the concept. Within this I will explore the work of other scholars within these concepts and tie their various reflections into one explanatory narrative that will be of use when analysing the results.

Method This section will explore the methods that will be in the study. It starts by briefly outlining ethnomethodology, the area within which this thesis lies. Then it will look generally at observations, before outlining the exact methods used in this thesis, ‘in person observations’, ‘observiaire’ and ‘video observations’ and the importance of combining them.

Each sub section will include a description of the method, a look at their use and importance within urban and cycling research, and an evaluation of the strengths and weaknesses. It will not describe exactly how they are used, that happens in the next section.

Study The study section will outline how the methods were carried out in practice. Including descriptions of the preparations, the observation sessions and the data processing after.

Results and Analysis I combined the results and analysis into one section, largely to save the text becoming repetitive. I go through the results, discussing what it means, and then analysing them with the use of the theories previously outlined. Within this section I have two sub sections, through which I will explore two overall themes that I observed during my study – Sociability and Efficiency.

Discussion To wrap up I have a short discussion section where I look at the strengths and limitations of the study, especially the method and theories. I also look at possible further research that could build on this study, as well as outlining some rough recommendations.

Impact of Covid-19

Before starting, I would like to address the Covid-19 pandemic and its possible effects on this study. At the time of writing, and during the whole research period, Sweden has had relatively light touch restrictions on people’s movements. Other nations have imposed widespread lockdown measures on entire populations but the Swedish government has led with recommendations that encourage people to work from home more, travel less and to restrict social interactions (including a ban on large gatherings), but crucially they have not been commanded to stay at home. Importantly however, people have been actively encouraged not to use public transport. Many cities have also taken this approach, leading

10 to a boom in cycling, globally2 (Laker, 2020), in Sweden (TV4, 2020) and in Stockholm specifically – with consistently large increases compared to the same time last year (Stockholms stad, 2020a).

It is therefore felt that the changes in travel behaviours will not negatively affect the study. Whether it changes the behaviours of cyclists whilst they travel is harder to tell and would be interesting to study in the future.

Ethics of the study

As with any study that includes recording people in public there are ethical considerations, especially around the identification of the people within the video. As advised by my supervisor at WSP, in Sweden videoing the general public is legal as long as you are by the camera and it is portable. The data collected is anonymised, with each cyclist referred to as a number. The one photo within this paper in which someone is identifiable has been blurred.

As for the storage of these videos, they will be stored on my personal computer which spends most of its time within my apartment. They will not be stored online and will not be shared with others. Theory

The theories that will underpin the analysis in this thesis are less theories and more areas of study which aim to promote valuable ways of seeing that will elicit novel conclusions. The first is the practice of cycling, a look at the actual act of cycling and the experiences and feelings it elicits. The second is the street as a social space, the idea that the street is and should be seen as a space that is socially constructed through human and technological interactions.

The practice of cycling

There is a tendency within traffic planning to treat all modes of transport roughly the same. This means cycling is often treated as a rational practice, measured using ‘time, distance and safety’ (Brown & Spinney, 2010) however there are fundamental differences that make cycling and the act of cycling unique. Using practice theory, I will explore the originality of this mode and use this understanding to analyse the results of my study.

Being and acting a cyclist

Practice theory is being increasingly utilised within cycling mobility literature to explore how cycling is performed and ‘done’. As a theory it is concerned with how the things that we do emerge, last and change; how they are learnt, what the routines are and how it is performed (Larsen, 2019). Practices are conceptualised as being made up of three interconnected parts: materials, that is things or technologies; competences, that is know-how and skills; and meanings, that is symbolism and ideas (Shove et al, 2012). It is by performing the

2 If you are interested in urban responses - in terms of walkability and cycling - to Covid-19 crisis then the following is an excellent crowdsourced document of different response strategies from different cities across the globe: https://docs.google.com/spreadsheets/d/1tjam1v0NLUWkYedIa4dVOL49pyWIPIyGwRB0DOnm3Ls/e dit?usp=sharing

11 practice repeatedly that the practice itself can exist. This means that its practitioners are also its co producers and change the practice themselves over time.

If applied to cycling, this means we can explore whether it is simply a means of travel from A to B, as rational transport planning traditionally would see it, or whether it holds other purposes. Its materiality can be interpreted as fairly mechanical, of gears, locks, and parking racks, but there’s also the material experience of the rider, of fitness, weather conditions and topography. The competency is partly physical - balance, muscles, and steering - but it is also in knowledge - in the ability to read signage, interpret road situations and communicate with others. Cycling’s meaning is also complicated, it is transport, but it is also freedom and health. It is sustainability but it is also danger and poverty (Shove et al, 2012). From this we can already see the complexity and contested nature of cycling as a practice, it’s heterogeneity (Spinney, 2009), how it can change over time and how it differs from place to place.

Indeed it is writers such as Spinney, and Brown, who have extensively explored what it is to be doing cycling - the sensory and social aspects, its sometimes irrational and ephemeral nature, the intangible feelings it accrues in riders (Spinney, 2006; 2007; 2009; 2011; Brown, 2012; Brown & Spinney, 2010).

For example, in one article Spinney (2010) explores how urban cyclists use their act to perform resistance against the form of the built environment. He shows how BMX riders redefine spaces, such as plazas and roads, but also objects such as benches and stairs. He also explores how road cyclists perform similar critiques by changing rules and using infrastructure differently - by breaking red lights, taking the road lane, not stopping at pedestrian junctions.

Brown (2012) talks of the act of ‘becoming’ and ‘staying’ a rider, how cycling is a ‘fluid and fragile’ state in which the rider balances themselves upon a machine, against topographical and climatic conditions and push themselves forward in near constant motion. This act, the physicality of doing it is what makes cycling an act of ‘sensuous meaning’ (Brown & Spinney, 2010).

The cyclist as a hybrid

The idea of the cyclist as a hybrid has been observed by scholars (Larsen 2018; 2019) and Tour de France winners alike (Jacque Anquetil in Krabbe, 2002, p5 cited in Spinney 2006, p715). The body and the machine work in partnership, the legs and arms powering and steering the machine, and the machine providing efficient transport and sensory stimulation in return. They rely on each other, when the bicycle breaks the cyclist can no longer ride; when the cyclist is fatigued, the bike can no longer travel.

Partly this idea is used to differentiate cyclists from motorised drivers, to illustrate that they are more free than those stuck in their ‘iron cage’ (Urry, 2006 cited in Haddington & Rauniomaa, 2014, p177) or ‘mobile shell’ (Goffman, 1971 in Haddington & Rauniomaa, 2014, 177). Most of the discussion however, comes from the human qualities that are embodied within cycling. Beyond walking, cycling is likely the most human form of mobility – in that so much of the vehicle is controlled and powered by the person. Indeed Ingold (2000, p376, cited in Spinney, 2006) argues that the cyclist is a ‘different kind of creature’ than any other.

Therefore it can be argued that it is important that cycling is studied with a focus on the human. The human is the motor and controller, the sensor and reader (Larsen, 2019). The human is exposed, intimately connected to topography and weather, to their physical

12 condition. The human’s feeling whilst doing is a part of the practice, the burn in the legs, the heat on their neck, cold fingers, sweaty back, the shaking of cobblestones, fear of accidents (Nixon, 2012 in Larsen 2019). This means the human is also susceptible to feelings of sensory pleasure and desires, of rhythm, speed, and flow.

Importance of rhythm and flow

The importance of rhythm and flow have also been highlighted by Brown and by Spinney. They talk of how the cyclist seeks smoothness, good pedal actions, correct breathing, smooth gear transitions (Spinney, 2006). How the performance of cycling is often about fluid motions - gliding, weaving, freewheeling and flow - and how this may even be unconscious but at the same time known to the practitioner. It is a mundanity but also a key part of the experience of doing cycling (Brown & Spinney, 2010). So much so that to some flow is an ideal or a desire - road cyclists tend to seek ‘the zone’ or ‘mojo’ (Csikszentmihalyi, 1990 cited in Brown, 2012); mountain bikers want to ‘clean the route’, not put their foot down (Brown, 2012); ‘to roll and never stop’ (Eassom, 2003, 202 cited in Brown 2012). Its importance has also been highlighted in terms of commuting, or everyday cyclists (Larsen 2019; Spinney, 2008).

If we accept that rhythm and flow are strong sensory desires, then it is perhaps unsurprising that these affect the behaviours and decision making of cyclists (Bendixson, 1974 cited in Spinney, 2008). In particular, what is seen as rule breaking, such as turning right at a red light, or unorthodox behaviour, such as slowing before red lights and waiting for them to change (Nixon, 2012 cited in Larsen 2018). Once looked for you notice that the question of how to continue their flow and rhythm is ever present in the cyclist’s mind, Spinney (2008) suggests that this desire for flow has a rational motivation, that it allows them to save energy. This is the likely explanation and many scholars have discussed this as fact (Cochoy et al, 2017) - talking of how stopping momentum goes against the cycling experience (Liu et al, 2019) how red lights ‘kill’ or destroy flow how cyclists are worse affected than drivers (Larsen, 2018; 2019). The best illustration of this comes in Fajans & Curry’s concise article (2001) which shows two things clearly: first, that the average cyclist has to produce significant amounts of energy to keep a good pace on roads with many stop signs, perhaps as much as near professional road cyclists. Second, that rolling through stop signs is a smart tactic to conserve energy, as going through at 5mph needs 25% less energy to get back to 10mph than if you stop.

Learning to be a cyclist

As discussed above, practices are learnt and the identities around these developed. Therefore, the self-understanding of a cyclist as a unique hybrid, with a desire for flow and rhythm, is also something that can be learnt and assembled. It is not necessarily innate. It is learnt from experience and taught by others. This is the same for traffic conditions. The cyclist needs to learn the formal and informal rules and how they can use them in a safe and efficient manner that also allows them to communicate to others (Haddington & Rauniomaa, 2014). As discussed in the next section, the trafficked street is teeming with communication, cooperation, and conflict opportunities, but the important part here is that road users are able to, and need to, learn how to navigate traffic situations.

Many of these rules might seem obvious and hardly worth mentioning - of course you should look before crossing the road - but these are learnt behaviours that are part of the doing of a practice. Cycling is no different and as a point of comparison, Weilenmann et al (2014) discuss walking. There are ways of doing walking and it is only in odd circumstances that this becomes obvious, the slow stuttering walk you have to ‘learn’ when in a large crowd, or the hunched and weaving walk you do with a small, unruly child. In fact, walking and cycling

13 are built on many of the same patterns, gestures and customs or norms (Brown, 2012). Either way, cycling has established codes of conduct. This code has been established, and is being constantly redefined by authorities from above, and by cyclists from below.

Conflict may arise when cycling encounters other modes of transport, which also have their own codes of conduct and contexts. For example, although pedestrians may have similar codes to cyclists, the speed context is completely different (Weilenmann et al, 2014). Similarly, the users of each mode may presume knowledge of the other’s codes, so car drivers may believe they have a similar code of context as cyclists, but cyclists don’t. This is what I will explore in the next section, where I will talk about the street as a social space, and the interactions, cooperation, and conflicts that this entails.

The street as a social space

As was explained in the previous section there is a tendency within traffic planning to treat all modes of transport in roughly the same way, meaning that cycling is often treated as a wholly rational practice. This also extends to the infrastructure they use, roads are rationalised as spaces for traffic - but this hasn’t always been the case, and there is growing discussion of a redefinition of streets from traffic spaces, to social spaces. First it is important to set out why the street needs to be defined as social, then move onto to what this means, before finishing by looking at how this has been expressed in the urban environment.

Not just a transitory space

Spaces of mobility have long been seen as places that allow you to move from A to B, which is a limited definition with little meaning within it. According to this definition, places A and B are social but the spaces that connect them aren’t – these have limited space and resources (Jain & Moraglio, 2014) and therefore human interactions and meetings are also limited, and the rules strictly mobility orientated (Spinney, 2007). Monderman, a traffic planner working in Holland, (cited in Hamilton-Baillie, 2004) calls this the ‘traffic realm’, defined by traffic segregation, high regulation and enforcement, and governed by rational analysis. Monderman believes that streets should be treated as part of the ‘public realm’. That they should be multiple, diverse uses, full of life and human scale, and governed by a complex web of ever-evolving social and cultural conventions’ (Ibid. p51).

In fact, some would argue that the ‘traffic realm’ is already in some ways part of the ‘public realm’, that there is sociability and meaning to be found and encouraged here but that it needs to be defined as such (Spinney, 2007). If it can be defined, and accepted, as a social space then it can become one - as Jonasson (2004) points out, the formal and informal codes of streets are embedded within them, in the infrastructure, the discourse, and the representations of and about that place. This means accepting the chaotic, ‘messy’ elements of mobility and sociability, and accepting that streets cannot be strictly controlled (Imrie, 2000, p1644 cited in Spinney, 2007, p26).

Historically this used to be the case, streets were a fluidly private and public space - used for mobility of course but also social and commercial uses such as children playing, market stalls, and families promenading. Being able to walk and use the whole street was just ‘taken for granted’ (Jain & Moraglio, 2014, p518). If you search for old videos of busy streets, you’ll see bikes, horses, omnibuses, people, children, dogs, all sharing the same space. The coming of the car era changed this, the street was interpreted as a space for mobility and the speed differences were used to introduce higher separation of modes in the name of efficiency and safety (Ibid.). Jane Jacobs, writing as the balance shifted to the car, had this to say: ‘streets and their sidewalks, the main public places of a city, are its most vital organs’ (1992, p29).

This sociability can still be seen today however, as the next parts of this section will explore. Our streets, despite the rational and restricted way they are treated, are filled with sociability. To take one example, Spinney (2008; 2010) points to the ways in which cyclists are creating their own spaces for expression and communication.

Communication

It was Dannefer (1977) who was one of the first to point out the high levels of social interaction in traffic situations. Before then, there was a large focus on the effect of cars not on the humans that controlled them. He observed that drivers perform gestures, movements and identities that are supposed to communicate messages of different sorts to each other. These acts are ‘thick’ with meaning and offer a ‘limited yet sophisticated’ form of speech (Jonasson, 2004, p57) that allows people to anticipate the others behaviour and change their own accordingly (Asplund, 1987 cited in Jonasson, 2004)

Not everything in traffic is social, there is much that is restricted or predetermined by government regulations, social norms, or the size of the vehicle (Dannefer, 1977). However, these preestablished codes cannot cover the entirety of the traffic network, there will always be gaps and it is in these spaces in between that communication seems to flourish. For instance, in the UK it is common to thank another driver for something by flashing your hazard lights briefly, this is not codified but is a polite gesture that the rules do not account for. Once you think about it, much of moving in traffic is layered with formal and informal communications: The wave to let someone out in front of you, the nod of thanks, the shout of annoyance.

Interestingly, communication can also be defined through the individual’s placement of the body and/or vehicle and through movement (Jonasson, 2004; Haddington & Rauniomaa, 2014). This could be: offering space, e.g. by pulling to the side to allow someone to overtake; requesting space, e.g. by pushing out into traffic to join the lane, or a pedestrian stepping out into the road to try and cross; giving way, e.g. by slowing down significantly before the junction; protecting others, e.g. by riding alongside a child; or even threatening others, e.g. close passing a cyclist. These all signal intents to others and are sometimes reinforced with visual, oral, or verbal communication (Haddington & Rauniomaa, 2014).

When looking at communication in cycling we can see it is an important facet of the practice (Larsen 2017; Brown 2012; Te Brömmelstroet 2018), perhaps unsurprisingly considering the previously discussed humanity embodied with the act itself. Here, the importance of communication is high as the cyclist travels at speed on a precariously balanced machine. It manifests itself in many ways, through body language (so waves, nods, positioning, signalling), through eye contact, or through the use of bells or your voice for warnings. The exposed nature of the cyclist also makes it easier to do so. You can communicate your intentions with a subtle shaping of the body to the left, a lean of the head to the right, a dart of the eye ahead. Larsen (p888, 2017) observed this when studying high flows of cyclists, describing a ‘disciplined flow of signalling and negotiating cyclists’.

However, despite the need to interact the cyclist also wants to maintain flow, so these communications are made whilst maintaining momentum, what has been termed ‘negotiation in motion’ (te Brömmelstroet, 2018). This is a balancing act as lower speeds engender the communication, especially through eye contact, of the subtle messages that are needed to negotiate in traffic (Hamilton-Baillie, 2004). This is especially an issue between modes with significantly different speeds, such as pedestrians and cyclists. Often communication is not possible, or very limited, with these speed differentials (Brown, 2012).

Discussions around traffic can be dominated by ideas of conflict or struggle, and this is the same with communication - we’ve all seen some one lose their temper whilst driving, and maybe even experienced this ourselves (see Lloyd, 2015 for an interesting exploration of cycle rage). However, the majority of interactions are collaborative, small communications that signal a willingness to protect themselves and others as well as a deep trust in their fellow travellers (Jonasson, 2004; 1999; Dannerfer, 1977).

Cooperation

The number of unique happenings we may encounter on one journey in a city is potentially innumerable and, as mentioned above, there is no way that the formal rule structure that governs the road can cover every situation. There are, and always will be holes but within these gaps communication flourishes. Cooperation ties these two situations together, users both follow the formal rules and communicate to fill in the gaps as a form of cooperation (Jonasson, 2000). It’s a kind of implicit agreement that the different actors are sharing a resource, and that adapting to each other is for the benefit of all (Juhlin, 2010). Despite the popular narrative of conflict the majority of road usage is done in a cooperative manner, if this wasn’t the case then roads would be a ‘catastrophe’ (Jonasson, 1999; 2004).

Cooperation works because there is a mutual understanding of the condition, or situation, the users are in, and because there are also set rules, behaviour, norms that have been collectively built up over time that the various actors can access and utilise. This mutual understanding is constantly being reinforced and reinterpreted as each individual situation arises (Juhlin, 2010; Jonasson, 2004). This means cooperation in traffic is an ongoing discussion, continued at each unique happening in traffic.

The roundabout would be a clear example of cooperation between mostly motorised traffic. It forces traffic users to communicate, interpret and evaluate their own and other’s positions (Jonasson, 1999). For proper inter modal cooperation, the zebra crossing is a space where modes with high speed differentials are forced to communicate and negotiate to find the best collective solution at that time. More common, however, than the clear examples of spaces of communication and cooperation are the times that people act in cooperative manner, but do so without relating with another (Dannefer, 1977). Adherence to the general road rules would be one example, another would be leaving a space on the kerbside when you pull up to a traffic light so that a bike can pass through.

This is where ideas of trust come in, when moving around traffic spaces there is an ‘implicit trust’ that you will not hit another person and they will not hit you (Goffman, 1971 in Dannefer, 1977). This is especially the case in traffic where risk of injury and expense are that much higher. This trust is so implicit in fact, that it’s not even thought about or considered - it is almost invisible (Dannefer, 1977). It is this trust that is the underpinning of cooperation in traffic, without it you wouldn’t be able to rely on the other users to act as you have agreed in your communications.

Creating social streets

So, we can see that despite the best efforts of rational, modernist traffic planners that streets are still sociable places. Certainly, they are more homogenous than they were a century or so ago, but they are still social none the less. We can also see that this sociability is what keeps traffic spaces from slipping into chaos. So how do we embrace the cooperative and communicative side of mobility as a collective strength, rather than misunderstanding it as a weakness?

First you regard streets as part of the public realm, as defined above. Second, you understand that behaviour can be determined by that individual's surrounding environment - just think how we change our behaviours whether we are in the pub or the theatre (Hamilton- Baillie, 2004). Third, start changing the environment and encourage the behaviours you would like to see take place - encourage communication and cooperation through design. It is repeated rituals, actions, and behaviours that create a place (Jonasson, 1999).

Method

Transport planning has long been a rationalistic field of study, focussed on the technological and physical (Saaty, 1996), and littered with jargon dominated by engineering and economic logic. There seems to be little room for fuzziness, and a tendency to downplay transports inherent human qualities (Fruin, 1971).

Consider transport planning’s classic query - what do people do when they want to get from A to B? A traditional, quantitative approach would look at where from, what mode and how often, presuming that people will choose the most efficient way. This is a somewhat reductive approach however, missing out on the complexity of people’s decisions and experiences that can be illuminated via qualitative methods (Spinney, 2011).

My wish is that this thesis can join other scholars in combining the clarity of rational approaches with the more ‘fuzzy’ and human perspectives that social science can bring to create a richer picture. It will do this by collecting data via two methods: in-person observations and an observiaire of video recordings. These will work alongside each other, allowing me to take qualitative and quantitative results. These results will support each other, with certain things only observable by one method, and others only observable by the second.

Ethnomethodology

Before I describe the methods I will be using I should briefly explain that they will be inspired by the study of ethnomethodology. At its most basic it is the ‘study of everyday life’ (Slattery, 2003, p104). The small details, habits, norms, values, and rules that people use, interact with, and are influenced by as they go about their daily business. It was championed by Garfinkel (1967) who wanted to pay the same attention to these phenomena as is paid to ‘extraordinary events’ or overarching structural theories (Slattery, 2003).

Sometimes what is pointed out is blindingly obvious, but the mundanity is the point (Laurier, 2004 in Normark, 2006), these small details ensure social order (Rawls, 2008; Normark, 2006). For example, traffic rules. Strangers are able to organise their machines in ‘correct’ formations in different contexts, without observational forces, previous connections or codified rules to guide them (Normark, 2006). This order is also shifting constantly - it is reflected, reinterpreted, and recreated and there is a constant conversation over this between its users (Slattery, 2003).

Observations

Introduction to observations Qualitative research has been defined as a ‘situated activity that locates the observer in the world’ and observations would perhaps be the most obvious example of this (Denzin & Lincoln, 2005, p3). Rather than being in a laboratory with control groups and sterilized

17 conditions, the researcher becomes an observer of phenomena of the world outside where the researcher can sit back a little and look for what ‘catches their eye’ (Corbin & Strauss, 2008).

Observations are a primary data collection method, used to collect direct experiences and meaning of the ‘insiders’ within a process (Jorgensen, 1989). They are popular within any field that studies the ‘effects of treatments on people’ such as medicine, economics, psychology, sociology, or in the case of this thesis, urban studies or planning (Rosenbaum, 2010; Singh & Hietala, 2014; Davis Harte et al, 2014; Herkner & Male, 2010). With urban studies, there is a clear need to study the environment and its users in place - to study a city and its citizens as they go about their business in the spaces that they use. To borrow a phrase from the art world, you study en plein aire. In this way, it is the city itself that is the laboratory, its citizens the resource for data collection.

Examples of observational research in urban studies In studying the city as it is, this thesis will be building upon methods explored by classic researchers of the urban environment such as William H Whyte, Jan Gehl and Jane Jacobs. To those in public life studies, the data resource is the city and the activity within it. Jacobs’ influential writings were based on her observations of the busy street below her Manhattan window (1992, originally 1961). Whyte (1980) famously studied the behaviour of people in public spaces using observations in-person and by video. Gehl sees himself following in their footsteps and has distinguished himself as an urban designer who designed spaces based on how the people want to use them (Gehl & Svarre, 2013).

Thanks in part to the endeavours of the above researchers, the method of observing has become well established within urban studies. With scholars using them to look at topics such as urban design (Sha et al, 2014; Huang, 2006; Byomkesh, 2012), public participation (Maquil et al, 2018; Alrashed et al, 2015), and walkability (Alidoust, 2018; Moyano, 2019; Fruin, 1971). There are also examples within cycling research, including infrastructure assessments (Emery et al, 2003) a study of ‘cycle rage’ (Lloyd, 2015).

Observations in this study

Observations are often carried out from one of two vantage points - in-person or using video. This thesis will use both. In-person observations are as they sound, observations made by the researcher as they are present in or close to the thing they are exploring. They could be known to the subjects or not, take part in the activity or not and you can record data in different ways, it could be via a diary, by drawing maps, taking pictures, using a checklist or taking notes (Gehl, 2013; Ziesel, 1983).

Video observations are taken and analysed later. The camera can be obvious, or hidden, and the subjects can be aware or unaware. You can observe things repeatedly in slow motion or frame by frame, allowing you to see behaviours that are difficult to notice and record in real time - what Davis Harte et al call ‘minute...concurrent...and nonverbal behaviours’ (2014). The data could be collected via notes or maps, or in this case, via an observiaire.

In-person First it should be noted that there is not one position one can take when observing in-person, there is a sliding scale between the ‘pure’ observer and ‘pure’ participant. I will be positioning myself much closer to the pure observer than participant. However, the various benefits and drawbacks of the method are roughly similar.

As mentioned above, Gehl has had a large influence over the use of observations in urban studies and so he has on this thesis. He and Birgitte Svarre’s (2013) talk of the validity of ‘manual’ methods of data collection - your own senses, and a pen and paper – which can bring something ‘more than cold facts to the table’ (p6). As I was looking to bring the fuzziness and humanity into traffic planning this seemed like a useful approach.

Its greatest strength is perhaps that it can illuminate those ‘banal, ordinary, colourless’ actions and behaviours (Perec, 1974 cited in Gehl & Svarre, 2013, p5) that people do that they are unaware of or try to deny. This might be because they can’t articulate it, that they don’t think it relevant or interesting, or because they don’t want to admit that they do it (Corbin & Strauss, 2008; Ziesel, 1983).

By building up an image of the actions that are actually performed you can start to see the dynamism of what you are observing, how one decision leads to another in a rippling effect and how patterns emerge (Zeisel, 1983). It is empathetic, placing you where the action is taking place, allowing you to begin to understand what the participants are doing as well as their motivations and desires (Ibid.; Gehl & Svarre, 2013, p6).

This isn’t to say you will see everything. It’s impossible not to miss things (Ziesel, 1983; Corbin & Strauss, 2008), what is more of an issue is that as an observer you are inferring the experiences of others. This inevitably leads to conjecture as you cannot know the internalised experience of that person. You may well misinterpret things, attaching meaning to things that may not have any. As a researcher you may be looking for something in particular and therefore see it everywhere, even where it is not (Thiel, 1997). This is especially true of nonverbal behaviours (Patton, 2002 cited in Corbin & Strauss, 2008).

There are also issues with the practicality of the method. Observing is a skill and researchers talk of developing your eye, of learning to look for the right things, and training yourself (Gehl & Svarre, 2013; Thiel, 1997; Paterson et al, 2003). This makes the process time consuming and, in some ways, difficult. However, Gehl & Svarre (2013) would point out that the methods low cost and adaptability makes it a pragmatic choice, despite the time taken to develop the skill. I am inclined to agree. If you do want to access and capture those silent behaviours not usually picked up by other methods, then the usefulness and accessibility of this method seem to outweigh the drawbacks.

Finally the issue of confidentiality should be mentioned (Corbin & Strauss, 2008; Gehl & Svarre, 2013), where you place yourself and what you use to record your data should be sensitive to the cultural context - some cultures may be suspicious of people stood recording public life, especially if it is of certain groups or in certain spaces.

Observiaire The word observiaire is a portmanteau of observation and questionnaire. It is a cheap and accessible quantitative tool that fills the void between travel surveys and flow measurements, giving you statistical analysis but also the ability to place behaviour to certain individuals (Wikström & Persson, 2015, p60). Its flexibility allows you to choose different variables and customise the method to your requirements.

Its relatively short history seems to start in 2008 with a paper within marketing studies by Cochoy (2008), on observing and measuring human behaviour in supermarkets which built on Underhill’s (1999) research into the ‘millions of individually insignificant gestures’ that shoppers perform (Cochoy, 2008, p18). They chose multiple variables, including the characteristics of the person, their location, their behaviour. These were recorded on a ‘code grid’ (Ibid., p19) which had ‘all the formal attributes of a questionnaire’ (Calvignac & Cochoy, 2015, p137). Cochoy developed this method in his work with Normark, a scholar in Sweden

19 who works with mobility (Normark et al, 2019), who then in turn supervised Wikström and Persson (2015) when they used the method in their thesis on the introduction of new cycling infrastructure on a main Stockholm street (Wikström & Persson, 2015, p23). The method was recommended to me by tutor, after their work with Normark, and in some way I hope to develop this new method for studying mobility.

Its strength for this study lies in its ability to capture both conscious and unconscious action in a way ordinary language might struggle to (Calvignac & Cochoy, 2015, p137) and present the results in an easy and clear manner (Normark et al, 2019). It suits this study as it tries to capture ‘the sociological analysis of technicised behaviour’ (Ibid. p24) - it seems to be the quantitative method that could also capture ‘fuzziness’. Despite this, it is suited to descriptive and explanatory ends, meaning that although it may be able to tell what is happening, it will struggle to tell you why that is (Normark et al, 2019; Wikström & Persson, 2015). That is why analysis of the results using theory, is important.

Video Video is a common research tool within planning and, since the turn of the century, increasingly so within cycling studies. For example, Laurier (2009) specifically explores different ways of videoing cycling, including handheld, fixed, and multiple mini cameras. This interest is in part due to the difficulty of capturing behaviours that are embodied with high levels of human control, speed, and transience (Brown & Spinney, 2010), and in part due to recent advances in video camera. To try capturing the same phenomena with just quantitative methods or just the stationary human eye would miss crucial aspects. Those interested in the feelings and experience of cycling mobility, what is called mobile ethnography, are champions of the method. Spinney was an early adopter, using it to capture embodied mobility and fleeting sensory moments of feeling and experience (2009; 2011). Building on this McIlvenny (2014; 2015) uses multiple cameras fixed onto bikes to observe cyclists’ formations and the experiences of children cycling together.

Another benefit is video’s ceaseless concentration. It is suited for observations taken over an extended amount of time (Paterson et al, 2003) as, unlike a human, it doesn’t lose focus or get distracted. It also allows you to play back the videos in slow motion, frame by frame, or even sped up giving access to micro analysis of minute, non-verbal behaviours and interaction patterns that are not as observable in-person (Paterson et al, 2003) - the ‘taken- for-granted’ mundanities of cycling (Brown & Spinney, 2010). New meanings can come to the fore that would’ve been neglected if read at ‘full speed’ (McIlvenny, 2015). Video gives you a depth and richness of content, it allows you to feel like you’re there, giving you context and movement and even audio - something text can never give you, however well written (Brown & Spinney, 2010; McIlvenny, 2015). This is not to say that the camera is neutral - every shot is cropped, the selection of what to include and exclude is a choice, and therefore a subjective decision made by a human. It isn’t what happened, but a record of what happened, a representation, and therefore something will be lost during its capture and playback (Laurier 2009).

There are also criticisms of video’s detached nature, especially from feminist critics who see it as ‘antithesis of collaborative and engaged qualitative work’ (Crang, 2003 cited in Brown & Spinney, 2010, p136). This is a valid criticism; the act of capturing video does lead to the researcher stepping back and avoiding contact with their subject. Distancing themselves using the glass of the lens, rather than being alongside or with them. However this may also be changing, as Brown & Spinney (2010) note there is a growing move towards using video in feminist practices (Parr, 2007; Kindon, 2003; Pink, 2006; Shrum et al, 2005, all cited in Brown & Spinney, 2010)

Video is able to capture motion in a way static forms of recording like images or text cannot do - particularly useful for cycling. This allows us to see how people use the space, how they interact and react, and gain a better idea as to why this is - bringing us into the picture (Brown & Spinney, 2010). By understanding this we can ask, do people move in unexpected ways? Is there a practice of moving that goes against the norm and does this actually matter? In this way we can see video as a political device, capturing alternate realities and proving their viability (McIlvenny, 2015).

However, cycling is so embodied with flexibility, speed and movement that Palmer (1996 cited in Brown & Spinney, 2010) and Brown et al (2008 cited in Brown & Spinney, 2010) both discuss the difficulties they’ve found in recording the practice of cycling with video because of the speed involved and concentration needed. However, as the placement of the camera in this thesis will be fixed, I believe the above studies have shown enough evidence to validate the use of video.

The combination of methods By themselves, the methods may have positives and negatives; however, they have been chosen together as it’s felt that they balance and complement each other. The remoteness and distance of video is countered with in-person observations ability to feel and experience the context. If I had only used video there would have been micro expressions, external details that may be missed (Paterson et al, 2003) – something I noted in Observation 5 (See Appendix 6): ‘Important to do this in-person to get the little details - eg you couldn’t see the woman smile in thanks at 08.02 on the video.’. There were times that, watching a clip back, I was unsure what had happened, but if I consulted my notes it was able to give me wider context. For example, just out of shot a bike had signalled a certain direction confusing the pedestrian. This was also useful when I was faced with data, produced by the observiaire, that I didn’t understand. My observation notes were able to give the context that I was missing. I also used the in-person observations to spot patterns or to inform what I would then go on to quantify using the observiaire, to back them up with ‘hard data’ so to speak.

Similarly, the limited nature of human memory and concentration is balanced with a camera’s unceasing eye. There were multiple times that I was writing notes down for an incident, only for another to take place whilst I was writing. However, I knew that the camera was able to pick up details of what I might missed when I watched the videos back later. The use of playback tools is especially useful here, I regularly went back and forth over an incident to try and establish exactly who had done what.

The Study

The following section will discuss the original plan, the process, and issues that arose. At its simplest, this study contains two parts. Several sessions of in-person observations, noted down on paper; and video recordings of the same sessions, processed using an observiaire. In total there were 7 observations sessions, but the data used and analysed in this study only came from 3 of these. The observations were carried out by myself and my supervisor at WSP, Fanny Larsson.

Observation sessions

Observations 1, 2 & 3 Observation 1 (Appendix 2) was a preliminary observation, partly to try out the method; partly to see I could observe; and partly to try to find a location. I observed 4 different locations across one of the main islands of Stockholm, for 5 to 10 minutes at a time. Simple

21 notes were taken, describing notable things and the conditions of the location. After the session we recorded reflections that would go on to inform the design of the study. None of the locations observed would be chosen for the study.

Image 1, one of the locations trialled in Observation 1.

Observation 2 was a traffic count. Although the observation location had been chosen by this point (discussed below), the next stage of the study was delayed due to the Covid-19 pandemic. Before we could carry out the full observations, a traffic count was needed to ensure that the crisis had not negatively affected cycling mobility patterns. This showed that there were more cyclists compared to previous years - a phenomenon that had been seen in other cities at the time. It should be stressed that this is not an exact, ‘proper’ traffic count, rather a rough estimate. For a full description of the process and results, please see Appendix 3. Observation 3 was pilot study of the location that was eventually selected, please see Appendix 4.

Observations 4, 5 & 6

Observation 4 was taken at lunchtime and was the first with the finalised observiaire. We observed for 75 minutes, however we both reflected that this was too long to keep full concentration for and agreed 60 minutes would be best for the next two sessions.

Observation 5 was taken during the morning rush hour. The day before, SL had actually requested people not to take public transport unless they had no other option (SVT, 2020). It is not clear the effect this had on the flow during this observation.

Observation 6 ended up becoming 6i and 6ii, and both were taken in the afternoon. 6i had to be called off after half an hour as the changing weather conditions made it impossible to carry on. The wind had picked up to the extent that it blew the camera over,

22 and the cyclists crossing Vasabron were visibly struggling. I felt this would affect their decision making so much that it would not be comparable with the previous sessions, so I called it off. Session ii took place a couple of days later and was much less eventful, there was little to report from this session. Please see Appendices 5, 6 & 7.

The time periods

I wanted to choose three flows, high, medium, and low, so I tried to observe at three times that would produce these three flows. I had to estimate a little as there was no hourly data available. I chose: morning rush hour (Observation 5, 7.30-8.30), which is traditionally the highest flow of the day according to my colleagues at WSP; lunchtime (Observation 4, 11.15-12.15), which I hoped would provide a medium flow as people ran errands, fetched lunch etc; and mid-afternoon (Observation 6b, 14.15-15.15), which was supposed to provide a low flow. After collecting the data, I noticed that the number of ‘cyclists per minute’ (cph) was not consistent throughout the hour of observation. To ensure a more even distribution I pulled two twenty-minute segments and one thirty-minute segment from the videos.

Flow Obs. No. of Cyclists Video length (m) Flow (cph) Session

Low 4 54 20 162

4 32 10 172

Medium 6ii 101 20 303

High 5 260 20 780

Total 447 60 447

Table 1: Each observation session’s time and flow.

The location

Image 2, location of the observations within the city centre of Stockholm (Google, n.d.)

The location chosen is on the north west corner of the central island of Gamla Stan. I chose Vasabron after it was recommended by my supervisor at WSP who had noted the high number of cyclist and pedestrian interactions there. There are few functions surrounding as it is half surrounded by water, with a small car park and a pedestrian traffic island. It is a sort of multi modal crossroads, with cyclists, pedestrians, cars, and buses all with their own infrastructure. It is also one of two cycling routes that run from north to the south of the city centre, see Image 2, making it an important link in Stockholm’s network.

Image 3, Satellite image showing the junction, and the different forms of pedestrian and cycling infrastructure. (Google, n.d.)

The bike infrastructure consists of a two way, separated bike path (coloured in red in Image 3) which heads down the western side of Vasabron before turning 90° to the right where it immediately meets the zebra crossing (purple) - at the same time a bike lane joins from the side via a crossing specifically for cyclists (orange). Cyclists can also choose to head directly south by merging with Riddarhusgränd, although there is no infrastructure in place for them here. Pedestrians have a pavement either side of Vasabron, the east side pushes you onto the traffic island (from where the observations take place) whilst the pavement on the western side of Vasabron runs parallel with the bike path. It is at the same grade but separated by a small row of cobblestones (See Image 5).

Image 4, view of the location from the Image 5, view of the location from the northbound pedestrian’s perspective, southbound pedestrian’s perspective, looking towards Vasabron. Author’s own. looking from Vasabron. Author’s own.

The zebra crossing is at the southern end of a bridge (Munkbron) where a cycle and a foot path meet. The issue comes as most foot traffic walks straight on down Riddarhusgränd, whilst most cycle traffic turns onto Riddarhuskajen, meaning cyclists must turn across the pedestrian’s path. This is an interface between the social and the traffic realms that Monderman set out, impersonal yet unpredictable, controlled but cooperative (cited in Hamilton-Baillie, 2004). In most directions there are very good sight lines, with little blocking the view. This may allow for easy communication between the different modes. The only exception to this is southbound pedestrians who, when reaching the crossing at the same time as a southbound cyclist, must turn almost a full 180° to perform any sort of visual interaction with them. As it is a zebra crossing the pedestrian has the right of way and the cyclist has to stop (what is called väjningsplikt in Swedish) (Transportstyrelsen, 2013), however these types of junctions don’t always have the same rules in reality as they do on paper (Aluvihare et al, 2018). It’s also worth noting that sometimes the sun can be in the eyes of southbound cyclists and pedestrian in the middle of the day.

My exact location was slightly removed from the junction, (see the camera symbol on Image 3) on a traffic island across the southbound car lane, where I had a good view of both north

25 and west stretches of the cycle path - I could be seen but I wasn’t obviously in the immediate sight lines of cyclists.

There are also slight gradients that do have an impact. Southbound cyclists coming off the bridge are going downhill, meaning they’re often on the brakes as they approach the crossing, whilst northbound cyclists are going uphill and often peddling harder to climb.

Image 6, View of pedestrians and a cyclist interacting at the zebra crossing, from Riddarhuskajen. Author’s own.

In-person Observations

Preparations Before carrying out the observations there were some basic preparations. First is designing the sheet I was to fill in (Ziesel, 1983). As you can see from Appendix 1 this is quite basic, consisting of a small section at the top with a number of shorthand codes, and a large main section, in which I noted the time, specific observation, and the direction of the cyclist. Below this was ‘General Observations’, where I would write patterns or other things I had noticed, for example ‘Are people looking at body language not facial expressions?’ or ‘Southbound cyclists are more likely to stop’.

Carrying them out Whilst carrying out the in-person observations, I recorded my observations using pen and paper, which I later transcribed onto digital copies of my forms. I adopted the stance of what Ziesel terms a ‘recognised outsider’ (1983) whereby I was visible to the participants, but my

26 purpose wasn’t known to them. Of course, there is the irremovable issue that my presence as an observer may change the subject’s behaviour, the ‘Hawthorne effect’ (Roethlisberger and Dixon, 1939 cited in Ziesel, 1983). My exact position meant that I was in the eye line of northbound cyclists heading up Riddarhuskajen, but mostly I was removed from the junction and mostly ignored. As I noted in Observation 4 (Appendix 5) it seems most cyclists didn’t notice me as ‘the decision-making process and judgement needed for the junction tends to distract people from [my] presence’.

I was looking for both unique happenings and patterns and having done preliminary studies I was able to begin judging exactly what this meant. I looked for interactions, movements, reactions - particularly when pedestrians and cyclists approached the zebra crossing at the same time. Did they move around each other? Did they shout or speak, or wave and smile? What didn’t they do that they ‘should’ or could?

Image 7, Observing and videoing the zebra crossing. Author’s own.

After I had completed each session I collected some quick general thoughts on how the process went, for example, after observation 5 I noted: ‘[I had] Difficulty putting ages on people around 30-40 [years old]’ (Appendix 6) . This was usually done on the metro home when my thoughts and memories were fresh in my head. Once all the sessions had been completed, I compiled the observations and started to collate and categorise them (See Appendix 10). This allowed me to organise my observations and see patterns that could then be compared with the quantitative data the observiaire would reveal

Video and Observiaire

Preparations Creating the Observiaire was an iterative process. For exact details of what was removed or added then please see Appendix 12. This iterative approach is influenced by ‘grounded theory’ whereby you develop your framework from your observations, that is after you have recorded them (Glaser & Strauss, 1967 cited in Calvignac & Cochoy, 2015). As it is hard to guess what will be relevant without looking first, you could ‘follow the actors themselves’ (Latour, 2005 cited in Calvignac & Cochoy, 2015).

What follows is an explanation of each variable, why it has been chosen and how. The observiaire is split into 4 sections, within these are subsections and then variables. The first two sections can be seen as the context within which the cyclist in question is operating, the second two are recordings of their actions or interactions within that context.

Image 8, Screenshot of the observiaire’s contextual variables.

Cyclist Info This section includes the cyclists Demographics, in this case Age and Gender. These were collected more out of interest rather than with an ultimate purpose in mind. The age ranges were chosen arbitrarily. The cyclist’s demographics are presumed, from my own judgement, though these are obviously sensitive and personal aspects to judge. Both Gender and Age were presumed based up on obvious external cues, such as clothes, hair styles, size, colour of hair, visible aging, etc. I only chose an option if I was sure, if I wasn’t, I chose Unsure.

The Context of the cyclist was also collected, which is defined here as their Pace and Direction. Pace was determined in relation to the average speed of all cyclists in that direction. This was a judgement based upon my experience of watching this same point for hours at a time. Noticeably faster or slower will only be selected if it is obvious that they are much faster or slower than the normal rider. The cyclists Direction was collected to see if there’s a difference in behaviours between North and Southbound cyclists.

Junction Info This section collects information about what is happening with the other pedestrians and cyclists who are around the junction as the observed cyclist is there. Under Pedestrians the Numbers around the crossing and Status of were collected. The Numbers were collected to explore whether cyclists react differently to small or large numbers of pedestrians. This number is calculated as the cyclist crosses the zebra crossing, considering all pedestrians within a roughly 5 metre circumference of the crossing.

The Status of is related to the pedestrian’s position around the junction in an attempt to see if the pedestrian’s location, not just pure number, also affects the cyclist’s behaviour. The positions were: Approaching, getting close to the junction but not at it; At the crossing, being within a step of the kerb of the junction; On the crossing, being on the zebra crossing/in the bike path; Leaving crossing, being within a step of leaving or have just left the zebra crossing; and Surrounding, leaving and being a distance away from the junction. It should be noted that this is the only variable in the observiaire not marked with only a 1, but any number that corresponds with the number of pedestrians in that position.

Social Interactions This section contains the attempted and successful social interactions that cyclists have with pedestrians, and in some cases each other. The sub sections for social interactions are Visual, Physical, Aural and No communication.

Visual interaction was recorded as Successful and Searching for eye contact. I was looking for cyclists who are trying to establish eye contact. This was sometimes difficult to see via video. If the cyclist is clearly and obviously turning their face towards another road user for a relatively extended amount of time then I noted it down, if not I will ignore it. This means that I will miss subtle examples of this, such as flicking eyes or brief twists of the head.

Physical interactions were related to any body movement that communicated to another road user. Namely, a Nod of the head, a Wave of the hand or a Signal with the hand (that the cyclist intends to turn left or right).

Aural interactions were related to messages sent that are intended to be heard by other road users, here that means the cyclist using their Voice or their Bell.

Finally, No communication was also included as capturing when cyclists don’t communicate is almost as interesting when they do. A lack of communication may lead to problems, however during the processing of the data it became clear the data here was unusable. Please read more on this in Appendices 11 & 12.

Image 9, Screenshot of the observiaire’s behavioural variables.

Physical Reactions This section contains the different physical reactions that cyclists have in response to pedestrians around the zebra crossing. Reactions made by cyclists when there are no pedestrians near the junction are not recorded. The sub sections are Speed up, No change

30 in speed and weave, Slows down foot down and No reaction. As mentioned above, these were decided upon after the observations and were either commonly observed or it was felt that they were important to note

Speed up was marked when the cyclist notably tried to increase their speed. Occasionally the Pedestrian crosses first, otherwise Weaves around or Straight through was recorded depending if the cyclist moves around the pedestrian in some way (Weaves) or makes no real movement to either side even if there is a pedestrian present (Straight through).

No change in speed and weaves was marked if the cyclist didn’t visibly change their speed but did weave around the pedestrian in some way. The two variables being if the Pedestrian crosses first or the Cyclist crosses first. If the cyclist doesn’t weave then they would be recorded as No reaction, which is explained below.

Slows down was marked if the cyclist tried to reduce their speed. Within this sub-section were two ‘sub-sub-sections’, so to speak. First is where the cyclists slowed down but the Pedestrian crosses first. Within this the cyclist can Slow significantly or Slow slightly, this was subjective and based upon my own decision. Other than that, they could Weave around or go Straight through. The second sub/section is where the Cyclist crosses first. Here, as above, it is recorded whether the cyclist will Weave around or go Straight through. However, it is also marked if the Pedestrian gives way, that is the pedestrian clearly stops or slows and relinquishes their right of way to the cyclist.

Although not many cyclists were recorded putting their Foot down, this was still included as a sub-section because it is felt that this is the ‘most’ a cyclist can do to allow the pedestrian to cross. Complete stop, where the bike is not moving at all; or Still moving (just), where the cyclist has their foot down but the bike is still creeping forward.

The final sub-section was No reaction. This means the cyclist doesn’t change speed or weave around they just go straight through. There are two variable options here, if the Cyclist crosses first or Pedestrian crosses first. The key difference being that the cyclist may not be expected to react if they judge that the pedestrian will cross first, if the cyclist crosses first then it’s likely they should have reacted in some way.

Carrying it out I recorded the footage, using a HD video camera and tripod borrowed from WSP, from the same spot and at the exact same time as the in-person observations.

I used Microsoft’s Media Player to play back the footage as this has a variety of play back speeds. This proved invaluable for noticing smaller details, like a nod of the head. I used Microsoft’s Excel spreadsheet programme to create, fill and process the Observiaire. Filling the observiaire out is quite simple, what is taxing is the time and concentration needed to focus. My guess is that to process all 1299 cyclists took me about 5 days where I didn’t work on much else.

I observed every cyclist who passed over the zebra crossing, each one received a new numbered column and a time stamp, taken when they pass the crossing, so that I could refer back to it later. The time stamp taken was for the time within that particular video, so for example I can see that cyclist 444, video 5a, 14 minutes and 22 seconds in.

Processing the data After I collected all the data, I had to make sure that I hadn’t missed anything. This took significantly longer than I expected, thanks in part to the vagaries of Excel but mostly due to my lack of skill and competence with the programme.

As is to be expected when filling in the data by hand there were a number of missed pieces of data - mostly where I had just not filled in anything for a certain characteristic. Once I had located the missing bits of information I went back through the films and noted what was needed. This took time that could have been saved if better care were taken in the forming of the observiaire and in the recording of data. There were other issues with the data which required some serious amendments, see Appendices 11 & 12 for more detail on exactly what was changed.

Data

The data I have collected consists of the following. From the observiaire, 3 hours, 13 minutes and 17 seconds of footage was analysed. From this, 1299 cyclists were recorded. Of the 1299 cyclists, 53.6% were recorded as male, 36% were female, 0.3% were other, 10.1% I was unsure. 1.2% were recorded as under the age of 19, 54.8% as between the age of 20-50, 7.4% as 50 or above, and 36.6% I was unsure. From the observations, the crossing was observed for around 3 hours, 13 minutes. Within that time, I made 113 specific observations.

Results and Analysis

The following section will explore and analyse the results of the observations and observiaire simultaneously. There will be two main themes, sociability and efficiency, through which the results will be grouped and discussed - these themes are influenced both by the results and the theories used to analyse them.

Please note: I will be quoting figures from the observiaire using two different types of percentage. One is % of the time (ott), i.e. cyclists slow down 54% of the time or, if a cyclist goes through here 100 times they will slow 54 times out of 100. The second is % of cyclists (oc), i.e. 54% of cyclists slow down or, if 100 cyclists go through here, 54 of them will slow down. There is a difference because of the way in which the data was collated. I will also be using ‘codes’ when discussing the in-person observations. They will refer to the video and the time at which they were taken - so 6b:17.45 would refer to Observation 6, the second video (b), at 17 minutes and 45 seconds in. You can find the recorded observation in the corresponding appendices.

Sociability

When cyclists and pedestrians use the space observed there are many clear attempts to create a form of temporary sociability between themselves. This can be seen through gestures that attempt to explain their behaviours, waves that relinquish their right of way, eye contact that seeks the attention of the other person, and through nods of thanks. However, it can also be seen in the use of their bodies and other subtle movements and readings of each other, hinting at an obscured communication that is shared between the different users.

The whole sample Overall, cyclists interact 12.5% of the time, with most of these interactions being physical (7% ott) or visual (5.2% ott) and very few being aural (0.3% ott). These figures include when pedestrians were not present as I also recorded occasions when cyclists interacted with each other. When we separate these out we can see that there are more interactions when there are pedestrians around (20.2% ott) than when there are not (7.8% ott) suggesting that cyclists interact more with pedestrians than they do with each other.

When cyclists do communicate with each other they only seem to do so via hand signals (60 out of 62 interactions) - I even observed that cyclists were signalling when there were no other cyclists around (4a:09.55). This could be because the junction is a fairly straightforward one for cyclists. There are clearly demarcated lanes and only one real entry and exit point and as the signal is almost binary, there is very little to be misinterpreted. Whatever the reason, the use of hand signals before turning is not a formal rule of the road for cyclists. It could be that this is a behaviour carried across from driving, where it is a formal rule that you must indicate, or that they learnt this at traffic school3. However, it is also likely that this is an attempt by the cyclist to cooperate with their fellow road users. Each action is an attempt to fill in the gaps between the formal regulatory framework (Jonasson, 2000) and create a mutual understanding between cyclists and pedestrians (Juhlin, 2010; Jonasson, 2004).

3 It is possible that as high as 92% of cyclists in Stockholm also have a driving license (Cyclistbloggen, 2012).

Social Interactions with 1 or More Pedestrians Surrounding 45,0%

40,0%

35,0%

30,0%

25,0% All High 20,0% Med 15,0% Low

10,0%

5,0%

Percentage of the time that cyclists interactcyclists thattheoftime Percentage 0,0% Any Visual Physical Aural Type of Social interaction

Figure 1: graph comparing the percentage of social interactions across different flows when one or more pedestrians are present.

Communication between cyclists via other means is difficult. They are either following behind or heading towards each other with little time or space for interaction. As te Brömmelstroet et al (2014) point out, a lack of space leads to conflicts and stress. Despite this difficulty the cyclists seem to be able to move around each other without conflict or collisions. In Observation 4 I noted: ‘Are people looking at body language not facial expressions? Reading body movements and shapes?’ and in other places I noted that they were seemingly able to calculate the path of the pedestrians (e.g., 5a:16.05). It seems that there is certainly some sort of communication going on - perhaps what te Brömmelstroet called ‘negotiation in motion’ or ‘interplay’ (2018; 2014).

The cyclist’s communication with pedestrians seems to be more varied, with physical communications less likely. Visual interactions are the most common (13.2% ott, with 7.1% oc searching for eye contact and 6.1% oc being successful) followed by physical (6.3% ott, with 6.1% oc signalling) and then aural (0.6% ott). The difficulty of building communication channels when one travels at around 15kph and the other 5 kph is obvious (Brown, 2012; Weilenmann et al, 2014) so cyclists seem to use a variety of techniques to communicate their intentions.

Beyond signalling, physical communication is largely used as a means of thanking another road user, be it a pedestrian to cyclist (5a:28.35), or cyclist to pedestrian (6b:04.00), or even on one occasion, a cyclist to a motorist (6a:04.15). This is a clear example of both cyclists and pedestrians performing in a sociable manner, upholding politeness principles, that are outside of the formal traffic rules. This gesture, although small, is ‘thick’ with meaning (Jonasson, 2004, p57). Physical communication also depends in part on visual communication, a nod or a wave is usually only performed when there is someone who will

‘receive’ it. In this way physical gestures are reliant on visual communication to work; without your intended recipient's attention you will not be able to communicate with them.

Aural communication is possibly seen as a means of last resort. For example, in observation 4 it was noted that a cyclist rang their bell ‘several times’ at a pedestrian who was on their phone with headphones in and not looking as they crossed the zebra crossing (4a:13.50). Although the right of way was with the pedestrian, so they didn’t have to look, the cyclist was obviously concerned enough that they felt they had to use their bell. It is also worth noting that both the cyclist and pedestrian were travelling south bound so they were not naturally going to make eye contact or be able to easily physically communicate with each other, supporting the idea that aural communication is used as a last resort. It is also open to misinterpretation, words can be lost in the wind, and often cyclists and pedestrians wear headphones. Think of someone ringing the bell: does that mean look out, or get out of my way, or excuse me? It can easily be interpreted as either cautionary or aggressive or as a courtesy. Perhaps this is why it was rarely heard on these observations.

Visual interactions seem to be the logical choice for cyclists. It is the easiest and quickest way to build some sort of communication and cooperation. Time is limited in these situations, often the interaction comes and goes in under a second. A flick of the eyes is much quicker than lifting your hand or gesturing with your head. Whichever way they chose to do so however, it is clear that there is a wish from cyclists to communicate and cooperate with those around them and we can see that cyclists have a tendency to interact with others, pedestrians or cyclists, in a silent and subtle manner - either with eye contact, or something else. This could be ‘negotiation in motion’ or it could be something more peripheral.

Giving way was observed both in-person and via the observiaire from cyclists and pedestrians alike. As mentioned in the Study section, the right of way lies with the pedestrian at this junction however there were many times that pedestrians were observed giving way to cyclists (4a:8.30). This could be a full stop (4a:27.25), sometimes with a gesture (5b:09.35), sometimes not, or it could also be a small ‘check’ in their walk (5a:23.20), a slight slowing for a couple of steps before picking back up to their normal pace once the cyclist had passed. This was reflected in the observiaire where although giving way was recorded in just one particular type of circumstance, where a pedestrian gave way to a slowing cyclist, we could still see that this happened to 3.2% oc who met a pedestrian. This seems to match an idea developed by Jonasson (1999; 2004) which talks of the rule of continuity in traffic (along with competition and positioning). This states that ‘Continuity is the fundamental condition under which traffic works.’ (1999, p52) and therefore if you have continuous movement then you have the right to go first over those who are either less or not mobile (2004). This may explain why some pedestrians are willing to give way, that they recognise the momentum that the cyclists are carrying and defer to this. This is an empathetic act, recognising the effort and energy it will take for the cyclist to slow and then build back up to speed again.

Differences between flows When looking at the different flows we see that cyclists in low flows have the most interactions by quite a margin (25.6% ott), followed by high (12.7% ott) then medium (5.9% ott). Note, this is when pedestrians are both present and not present. Generally, the flow pattern for each specific interaction matches that of the general interactions - basically that the low flow has the most interactions and medium the least. That is, except for aural communication, with voice - then it was the medium flow that saw the most (1% oc) and low the least (0% oc).

When pedestrians are present the same pattern can be seen - the higher percentages of interactions can be seen in low flows (41.9% ott), whilst the medium (11.1% ott) and high

(17.3% ott) flows are much lower. This is especially true when looking at visual interactions: low (29% ott), medium (3.7% ott), high (8.7% ott).

Specific Social Interactions with 1or More Pedestrians Surrounding 20,0%

18,0%

16,0%

14,0%

12,0% All 10,0% High 8,0% Med 6,0% Low 4,0%

Percentage Percentage of cyclistsinteract that 2,0%

0,0% Visual, SearchVisual, for Successfuleye contact eye contactPhysical, WavePhysical, Physical,Nod Signal Aural, BellAural, Voice Type of Social Interaction

Figure 2, graph comparing the percentage of specific social interactions across different flows when one or more pedestrians are present.

It is interesting that the low flow sees the most interaction. It could be presumed that it would be high flows that would see the highest amount of interactions, largely due to necessity. With many cyclists travelling together it could be assumed that they need to communicate more with each other and those around them. However, it is in the low flows that the most interactions have been observed. One possibility is that as cyclists are less likely to arrive to the junction in flows or clusters, and more likely to arrive one by one, that there is more time and space at the junction to build more visible communications and cooperation. With fewer other cyclists and pedestrians around there is more time for them to focus on other individuals without having to think about, for example, another cyclist behind them. This makes it more important for cyclists to interact with other road users. With more ‘one on one’ situations, the cyclist may be more unpredictable as the pedestrian cannot estimate their behaviour based upon them following others. The pedestrian may also be more likely to step out and challenge the flow of a single cyclist, rather than a cluster.

Looking at the specific interactions, we can see that in high flow the most common interaction is signalling (5.8% oc), followed by searching for (4.8% oc) and successfully finding (3.8% oc) eye contact. In the medium flow, interactions are rare with only 3 recorded (3.7% oc) - vocal communication, searching for eye contact, and signalling. By far the highest % of cyclists doing any form of any interaction came in low flows, for example 19.4% oc in low flows search for eye contact. This seems to have led to the second highest percentage of any cyclist interaction as 9.7% oc attempt some form of eye contact. The only case of a person using their bell was also recorded during the low flow (3.2% oc).

So again, we see that low flow has the most interaction. This could be that cyclists are travelling at lower speed in low flows (worth remembering that the low flow was recorded in the afternoon, rather than during the morning rush hour). Therefore, they have more time to try to connect with those around them - as has been previously pointed out, the speed

36 differential between cyclists and pedestrians can hinder communication (Brown, 2012). The premise that communication and cooperation need more time and space to be effective is supported by the high cases of eye contact specifically in low flows. However, the ‘success rate’ of eye contact is much lower in low flows than it is generally. Generally, 7,1% oc search for and 6.1% oc are successful, however in low flows only half as many are successful (9.7% oc) as those that search for it (19.4% oc)

Thoughts Peripheral communication Despite the fact that one can observe high levels of sociability between cyclists and pedestrians at this junction it cannot be ignored that the vast majority of the time, cyclists are not socially interacting with others at all. When pedestrians are present it is 83% oc or 79.8% ott that they don’t interact. Or at least, I wasn’t able to capture social interactions with the variables I chose to observe. It is more than possible that there are more subtle forms of communication going on that are difficult to observe via film - the ‘negotiation in motion’ or ‘interplay’ mentioned above (te Brömmelstroet, 2018; 2014). This is discussed by Glaser (2017) who noted in their study of cyclists ‘instantaneous decisions...made unconsciously’. Interestingly, when they pressed the cyclists on these decisions in their interview process the cyclists struggled to put what they did into words. This matches an interview, unrelated to this study, with a cyclist who is trying to describe what it’s like crossing a junction with many cyclists all at the same time:

“It’s weird because people cross from all directions at the same time. But somehow, if you do it often, you anticipate having to brake or accelerate slightly so that you don’t bump into someone. You anticipate and look at the other cyclist. We don’t actually nod to each other, but it’s more like, okay, I have to brake slightly. Everyone watches their left and right.”

(Why We Cycle, 2018)

This accurately describes the almost invisible communication I sensed when observing this junction, what I call peripheral communication. These are split second decision and judgements that are made based upon hardly visible body movements or facial expressions. Often this is without even looking at the other person or people. Cyclists seem to sense what is going on in their periphery, make calculations based upon that and then change their behaviour and body language - which is then responded to in turn by other cyclists also sensing through their periphery in a sensory back and forth. I believe cyclists are communicating more than I was able to observe within this study, that there is another subtler level of communication going on which is difficult to capture using the methods utilised in this thesis.

Physical communication It could be that this peripheral communication which I was unable to capture through overtly social interactions, is actually partly captured through the physical reactions of the cyclists. Cycling is embodied with a high level of physicality - the bike is powered by leg muscles, the steering by the arms, as a cyclist turns a corner they lean in, using their body and their core to keep balance (Brown & Spinney, 2010). This means a degree of control over your body is needed in order to gain and maintain momentum and stability. So, it is possible then that, as discussed above, the cyclist may use their physical actions as a way to communicate with others (Jonasson, 2004; Haddington & Rauniomaa, 2014).

This may be done in a number of ways. For example, through the placement of the bike - if you were to clearly place your bike to one side of the lane you may be able to communicate that you intend to cycle in front or behind the pedestrian. Or through changing your cycling

37 speed visibly: by decreasing and braking hard or by speeding up, especially if one ‘makes a show’ of it by getting out of the saddle.

However, this is not just communicative behaviour, it is also cooperative. It has a purpose beyond just telling the other person what they’re doing. Its purpose is to ensure both cyclists and pedestrians can use the space that they are temporarily sharing in a safe and easy way (Juhlin, 2010; Jonasson, 2004).

The next theme will look at the physical reactions in more depth, but as they can also be interpreted as physical interactions, or communications, they will be considered here as well. Overall physical reactions from cyclists were higher than social interactions when pedestrians were present, 47.8% ott compared to 20.2% ott. 4.7% ott they speed up, 8.1% ott they weave around and 35% ott they slow down. Even if only half of these cases were cyclists trying to communicate through their physical reactions, that is still comparable with the numbers of social interactions seen.

This matches with the idea of peripheral communication, that cyclists can read others body positioning, and speak with their own. It can be argued then that cyclists communicate with the positioning and speed of their body and bike, and that this has been observed in part in this study.

Lower flows, higher interactions As the figures above indicate the highest likelihood of social interactions came when there were fewer cyclists, and possibly pedestrians, at the zebra crossing. It is possible to deduce from this that lower flows make for better interactions. However, I would guess that the key factor here is speed. As discussed in the Theory section, lower speeds make it easier for communication, especially of subtle messages (Hamilton-Baillie, 2004) and especially between modes, which often struggle with high speed differentials (Brown, 2012).

The low flow saw the highest proportion of cyclists who were judged to be going slowly (15.1% oc, compared to 5.9% oc at medium, 5.8% oc at high, 7.4% oc overall). If we look at the interactions of those cyclists going noticeably slowly, 22.9% of them interacted in some way. Of those going noticeably fast only 7.3% oc interacted (those going at a normal pace, 12.2% oc) showing that if the speed of the cyclist is lower than the average speed then there is a higher likelihood that they will socially interact. Of course, these were not accurate speed readings, they were judgements by myself, but I had stood at and watched videos of this spot for a number of hours, so I had some idea of the ‘normal’ pace.

Efficiency

The word efficiency may bring to mind ideas of quantitative and rational transport planning, however in this case I am considering the term efficiency in a different way. As explained in the ‘Practice of Cycling’ part of the Theory section, cyclists have a strong desire to continue their rhythm and flow and it is an important part of the practice of cycling, of doing cycling. In the same section I explain how the energy that can be saved by either not stopping at certain junctions, or even just coasting slowly through, is higher than is perhaps realised. It is this desire for flow tied in with the idea of energy saving, that explains what I mean by the term efficiency.

Whole sample When there are pedestrians present cyclists react just under half of the time, 47.2% ott, or 48.2% oc. Here, react means to change behaviours in response to a pedestrian’s presence at the zebra crossing. When they do so they are most likely to slow down (35% ott), followed by weaving, but not changing speed (8.1% ott) and then speeding up (4.7% ott). This means

38 that 52.8% ott, or 51.8% oc, don’t physically react at all when pedestrians are present. Looking at the specific reactions, the highest numbers are for when the cyclist slows slightly (16.4% oc) or significantly (13.4% oc). The next most common reaction is weaving but slowing and cyclists going first (6.5% oc).

Physical reactions with 1 or More Pedestrians Surrounding 70,0%

60,0%

50,0%

40,0% All High

react 30,0% Med 20,0% Low

10,0%

Percentage of the time that cyclists thattheoftime Percentage 0,0% Any Speed up None but weave Slow down Type of Physical Reaction

Figure 3: graph comparing the percentage of physical reactions across different flows when one or more pedestrians are present.

It is perhaps not so surprising that slowing down is the most common reaction - this is the expected behaviour at zebra crossings, where cyclists must give way to pedestrians. However, it is the standard, expected behaviour of vehicles to stop completely to allow pedestrians to cross at zebras. Here it is clear that cyclists are not doing that, even of those that do slow down under half of them slow significantly. The others will slow a bit, or weave around. There are very few cases of a cyclist putting their foot down (1%), and ever fewer of them coming to a complete stop (0.6%).

This was also observed in-person, where I noted that cyclists will go through all sorts of different manoeuvres so that they don’t have to stop or put their foot down. They will slow down a little, just checking their speed a bit (6b:26.30); slow down much before the zebra crossing to allow them to glide through (5a:43.50); they will swing in a wide arc around the pedestrian, or dart in front them (5b:10.45); sometimes they will slow down close to the zebra crossing but still cross it as the pedestrian is there (5a: 01.45); and finally, even when they slow down significantly they may still just about creep forward, maintaining the smallest amount of mobility (4a:24.00).

Some of these behaviours would be unacceptable if performed in a motor vehicle, and many would at least be unorthodox. If a car approaches a zebra crossing it should stop at a safe pace and not move around the lane at all, giving ample time for the pedestrian to cross. The balance is almost entirely with the right of way of the pedestrian. But cyclists seem to do almost anything they can not to stop. They seem to work within a different set of norms,

39 where it is ok to weave around, to slow slightly, to rush through, and not interrupt your own sense of flow as long as you balance this with the flow of the pedestrian. This may be acceptable and safe behaviour (note there were no accidents and next to no tensions observed in the near 4 hours of footage shot at this location), but there may also be a disconnect between what the cyclist sees as dangerous and what the pedestrian feels threatened by, and what the cyclist sees as ‘polite’ or correct behaviour and what the pedestrian sees.

We can also see that cyclists seem to rarely change their mind. Once they decide to slow down they let the ped cross first (153 out of 169 times), once they speed up they decide to cross first themselves (23 out of 24 times). They also tend to do one thing - they stay the same speed, but weave (8.1% ott); they brake but don’t weave (33% ott); they speed up, but don’t weave (3.2% ott). This is possibly an attempt to behave in a predictable manner, where the cyclist is considering their fellow road users who may be reading their actions, but more likely it is to continue the flow of their movement. Changing their mind halfway through a reaction will lead to a loss of momentum.

Differences between flows The different flows, when pedestrians are present, vary in terms of physical reactions, high (42.3% ott), medium (63% ott) and low (51.6%). Cyclists in the medium flow are the most likely to react, and those in the high flow are the least likely.

Specific Physical Reactions with 1 or More Pedestrians Surrounding

30,0%

25,0%

20,0%

15,0% All 10,0% High Med

5,0% Low Percentage Percentage of cyclistsreact that 0,0%

Speed up No change weaves Slows down, pd 1st Slows down, cy 1st Foot down

Figure 4, graph comparing the percentage of specific physical reactions across different flows when one or more pedestrians are present.

The low flow is quite balanced, with 6.5% to 9.7% oc here choosing between one of 6 different reactions. As discussed above, there is more time and space during low flows. Perhaps this leads to more flexibility in response choice. You are less likely to follow another cyclist and therefore more able to make your own decision. You may also be able to use the

40 extra time and space to perform less predictable behaviours, such as weaving and speeding up, and maintain your flow through a wide variety of different reactions.

The high flow is less balanced, cyclists were most likely to slow slightly (19.2% oc) or significantly (8.7% oc). This is the largest difference between these two variables in any flow, and the slow significantly figure is also the lowest of any flows. So, although there is a good chance the cyclist will slow slightly, there is a low chance they will slow significantly. As mentioned before, the higher flows see more cyclists cycling together through the junction as part of a whole, as a cluster where sudden movements - braking or swerving - can lead to problems for those following behind. In this way cyclists are able to maintain their momentum and flow by being part of a pack.

The medium flow stands out with cyclists slowing slightly (29.6% oc) or significantly (25.9% oc) the most. It is the least likely to do pretty much all of the other possible variables. The only other reactions, both 3.7% oc, were: no change in speed, weaving, cyclist first; and speeding up, straight through. In other words, they either slow and let the pedestrian cross first, or they move around/speed up and cross first themselves. So why is the medium flow the most likely to see reactions? The low flow saw more social interactions so perhaps physical reactions weren’t needed. The high flow may have seen more ‘herd mentality’, with cyclists moving in clusters copying those ahead. It seems that cyclists in the medium flow struggled to keep their momentum with limited options other than to stop for the pedestrians at the junctions.

Thoughts Momentum and efficiency The behaviours captured above show a clear desire on the part of the cyclists not to stop their own personal momentum and there are a wide range of different options that they chose to ensure this. Even in different flow contexts, alone or in groups, they manage to find different ways to ensure they don’t stop.

The motivation behind this is efficiency. Cyclists are keenly aware of the physical nature of their mobility, and of how it is their own muscles and energy that are powering them. Therefore, it is energy saving that motivates their desire for momentum (Spinney, 2008), not some wish to flout traffic rules.

Balancing efficiency There is a balancing of the cyclist’s own wish for momentum or efficiency (what Jonsson calls the right to continuity (1999; 2004)) and the pedestrians actual, codified right of way. The power to make this decision seems to ultimately rest with the cyclists, as they are the faster, heavier unit however pedestrians seem also to be willing to give up their own momentum and give way to the cyclists - as discussed above. The topic of cyclists breaking the rules is a controversial one but despite the dominant narrative of rule breaking cyclists it has been shown that perhaps this number is much lower than perceived - around 5% were found to ‘recklessly’ ignore the rule and 88% to follow them (te Brömmelstroet et al, 2014).

Either way, it is perhaps more useful to look at it from another side - if cyclists are breaking the rules consistently, perhaps this tells us something about the perceived legitimacy of those rules? (Ibid.) And perhaps this suggests that the rules were not designed to meet the needs and desires of those users, as Emanuel has raised (2019). To me, it would seem that rather than revealing some innate selfishness on the part of cyclists, it actually reveals an innate desire for momentum and efficiency. I observed this in-person, when I noted that multiple different cyclists were cutting the corner either onto the pavement (6a:10.15) or onto the opposite lane (4a:2.30). As previously discussed, the energy cost of stopping and starting are higher than presumed, and not insignificant (Fajans & Curry, 2001).

The behaviours observed in the section above, on sociability, would also suggest that there is a pattern of cooperative actions from cyclists. Add to this the many different ways in which cyclists will attempt to change their position or speed so that a pedestrian can cross unhindered, and a different picture emerges. One where cyclists are balancing an innate desire for momentum and efficiency against a will to create and communicate a cooperative social space.

Reactions over interactions Overall, we saw that cyclists are more likely to physically react when pedestrians are present than they are to socially interact. In a situation where time and space are limited the course of action you choose to take has important consequences. Decisions are made based upon on the finite ‘resources’ you have available to you. As cycling is a physical and sensuous act, then to reach for physical reactions as the solution to the situation is perhaps understandable – it would feel the natural choice. For example, if you’re approaching the zebra crossing and you’ve just weaved past a couple of slower cyclists, perhaps it seems the easiest option to do the same again, to weave around the pedestrian in the same manner.

As discussed above, this is not to say that these cyclists are not communicating in some way. Their physical reactions can be seen as a form of communication. For example, as the cyclist approaches the zebra crossing, they may already be slowing down in anticipation of a pedestrian, a fellow cyclist, or just for the tightness of the corner. It is therefore easy for the cyclist to slow down further when a pedestrian arrives, communicating their intentions via their physicality.

Final thoughts

What seems to be evident from the above section is that cyclists, when they are in spaces which they share with pedestrians, are often balancing the desire for the efficiency of their own movements against their desire to create a cooperative social space. They slow, they weave, they speed up, they stop, they go straight through. Each one is negotiating this balance each time they reach the junction. There is no concluding answer or solution, each time they reach the same space the situation will likely be different. It is a constant process, and a constantly changing process.

Often you can see this debate going on in the cyclist’s mind, in real time. They slow for the pedestrian, but they don’t stop and you can see their legs almost twitching to start pedalling again, their brain ticking down the milliseconds until the pedestrian has crossed enough of the zebra crossing for them to be able to go past. If they wished to completely ignore the rules, they would be more than able to, they could use their larger embodied mass and speed and force the pedestrians to wait by passing through the junctions without stopping. But they don’t, they do something else - they constantly renegotiate the space.

By doing this, cyclists are challenging established codes and attempting to create their own norms by repeating the same types of practices repeatedly. Any worry that comes as a result of their behaviour is rooted in a misunderstanding of the importance of these two pull factors. A failure to recognise that the urban cyclist is often negotiating between cooperative sociability and their own efficiency. This misunderstanding leads to ignorance of the unique aspects of cycling, that it has its own unique desires and needs as a form of transport, especially in regard to the regulations of the road.

To note

The following are things that should be noted when reading the results and analysis, such as quirks in the data or the way that the data was collected.

From the observiaire:  When looking at all cyclists physical reactions, the medium flow is the lowest (16.8% ott), however when you look only at the times that pedestrians are present then the medium flow actually sees the highest percentage of physical reactions (63% ott), with low at 51.6% ott and high at 42.3% ott. This may seem odd, but it is down to how the data is collected.  The number of cyclists that met pedestrians on the medium flow is quite low: 27, compared to 104 for high, and 31 for low. This may be because the medium flow was taken in the afternoon, instead of morning rush hour and lunchtime when you would expect there to be more natural footfall.  Some social interactions (especially signalling) were recorded when pedestrians weren’t around, whilst no physical reactions were recorded.

From the observations:  In order to process the various observations, I had collected them into similar ‘types of observations’. If I saw something several times or more it became a ‘type of observation’. For example, I noted several times that cyclists will signal with their arm, and that sometimes they signal when no one around. These two ‘types’ were joined together within a ‘group’. I then placed them with other similar ‘groups’, such as ‘Cyclists will react to each other’ within a wider category that was ‘Communicating and reading each other’. This allowed me to better see patterns and common occurrences. Appendix 10 shows you how the results were collected together.  The in-person observations did go on to influence the choice of variables in the observiaire, hence the level of crossover between the two sets of results.

Discussion

Here I will discuss the strengths and limitations of the study and the theoretical framework, as well looking at possible further research and recommendations for the future.

Strengths

Overall, I felt the two forms of observation, in-person and observiaire via video, worked well. They complimented each other with the observiaire capturing one thing, and the observations the other. For example, I wasn’t always able to capture certain subtleties via camera, however I was sometimes able to capture these in-person – eyes darting to one side or a slight nod of the head. The video was able to capture footage ceaselessly however, there were cases where I missed what was going on in-person as I was writing down notes from a previous observation, or because I lost focus temporarily.

They were both relatively easy to set up and operate, a basic knowledge of how to use a camera and a decent concentration was all that was needed to stand at a spot, film and observe all at the same time. The observiaire is also relatively simple to fill in, though admittedly it could be streamlined. Because the methods are relatively basic there is a high degree of flexibility for the researcher in terms of designing the study – the exact same study could be done of the same spot, but this time focusing on importance of weather conditions, or of the incline/decline of the path, and I feel the results would still be valid.

The theoretical concepts used also complemented each other well, with the ideas able to illuminate the motivations behind the individual decision making of the cyclist and the surrounding pressures on them. How cyclists can be motivated by both their own efficiency and cooperation with those around them. Understanding the needs, the being and desires of the cyclists was useful to appreciate the motivations of their actions. Conceptualising them as hybrids allowed me to understand the importance of flow to their mechanical side, and also the importance of communication to their human side. This worked well with the understanding of the crossing as a social one, seeing as the space and the mode of transport motivates the cyclists to cooperate and communicate with their fellow users.

Limitations

As mentioned, the design of the observiaire and the processing of the data it produces can definitely be streamlined. It was built from scratch for this study, and I confess to having limited experience in formatting questionnaires or in compiling statistics. Although it was usable, and produced good data, the whole process was time consuming. With proper input from those with expertise in statistics and programming it could be a usable and accessible tool for practitioners and researchers.

The other limits are more to do with how I chose to observe and what I included within the study. The analysis, and conclusions I came to, perhaps leant too heavily on supposition – on me as an external observer, supposing or projecting my thoughts and feelings upon the cyclists in the study. There are no discussions with the cyclists in question about how it felt for them, why they think they behaved in a certain way. Together these methods rely on the observer bring able to empathise with the subjects, something that may be difficult especially if they are not a cyclist themselves.

The study was also limited in terms of its perspective. For all of the observations I stood and filmed from one spot, never moving from there. However, scholars such as Laurier, Justin Spinney, Paul McIlvenny and Katrina Brown have been experimenting with recording the

44 experience and practice of cycling from new and novel perspectives. For example, observing their own experiences of cycling (Larsen, 2018; Spinney, 2006); interviewing and observing whilst riding with people (Brown & Spinney, 2010; Spinney, 2006); or using cameras fixed to the bike looking at the cyclists face, or to the helmet to capture a ‘point of view’ perspective (Spinney, 2011; McIlvenny, 2014; 2015; Laurier, 2009). These techniques could possibly allow the researcher to start to grasp the subtle, peripheral communications observed in this study.

Further research

The use of video in more original ways, such as those listed just above, would certainly be an interesting way to take this work forward. I feel there is more to be investigated in terms of peripheral communications which could illuminate what traditional practitioners may not be able to see.

Further to this, more qualitative investigations into why cyclists behave as they do could be pursued. The research could investigate the what, via novel video techniques, and the why, through questionnaires or interviews with cyclists. These could be done ‘on the saddle’, immediately after, or during an observation of their own ride. It would allow them to talk about their experience, perhaps lending the researcher a deeper understanding of the motivations and thoughts.

The combination of methods used in this study can certainly be taken forward, they are cheap and accessible and allow you to access subtler forms of data that may otherwise elude researchers. The observiaire especially is worth taking further, if made more efficient it could prove a valuable tool for collecting qualitative traffic data in a quantitative manner. This would be useful not just for studying cyclists but also other road users. For example, looking at cyclists as they interact with motor vehicles, or looking at the similarities between runners and cyclists when mobile (something I noted briefly in Observation 3, Appendix 4).

Finally, there is data collected by this study that has not been used. A similar study could be done but looking more at the identity of the cyclist – do women stop more? Do young people interact more? A study could also be done, investigating the influence of topography on cyclist’s decision making. There is data on the direction of the cyclists, and we know there is a slight incline for northbound cyclists. An investigation into whether they are more or less likely to stop for cyclists, and why, would be of interest.

Recommendations

The aim of this thesis has not been to recommend concrete policy proposals or suggest infrastructure designs, rather I have sought to promote better understanding of the behaviour and needs of the cycling community. However, to research and write for half a year on the same topic and not have further ideas on it would, in my opinion, be odd. So, I would like to conclude by offering some of the thoughts I have gathered. Namely that an improved knowledge of the ‘uniqueness’ and cooperative nature of cycling is needed, and that increased, and more suitable space should be given to cyclists. These thoughts are aimed at those interested in, or active within, cycling and cycling planning. This could be traffic engineers, academics, planners, or politicians.

I believe an improved knowledge of the unique demands and needs of cycling is needed, as well as its often cooperative nature – specifically within the media, local and national governments, and within traffic planning. Cycling cannot be understood in the same manner as motorised or pedestrian traffic. Neither can it be seen as a mode of transport that is in some sort of inherent conflict with those around it. This study at least goes some way to

45 show the many cooperative behaviours cyclists express in their everyday actions. How this knowledge is disseminated I cannot be certain, but better education of transport planners at university, in consultancies and in municipalities would be a good place to start. It should also be said that pro-cycling groups could play an important role here, both informing the general public and by putting pressure on local governments.

I also recommend that cycling spaces be better designed so as to fit the unique needs of its users. How this might look exactly would be for urban designers or traffic engineers to decide but it would seem that two things are important: increased physical space dedicated to cyclists in order to give them space to interact with those around them and secondly the creation of an infrastructure that takes into account the importance of flow and rhythm

What you may end up with is something similar or inspired by the ideas of ‘shared spaces’, ‘play streets’ or ‘woonerfs’. It doesn’t really matter the name; the idea is similar. All modes are welcome, but the pedestrian and then cyclist is prioritised. There is little in the way of signage and a greater emphasis on design features, such as the use of colour and different materials on the road surface. The idea is that this slows people down and encourages its users to negotiate and observe the space before them - a little chaos is actually desired (Hamilton-Baillie, 2004, p57). This accepts that traffic regulations can’t cover everything, that there will be times when people have to deal with things by themselves, to communicate and cooperate, and that actually this is desirable, especially when trying to create a more pleasant place for people to live, to socialise and to move (Glaser, 2017; Jonasson, 1999). Perhaps pedestrian and cyclist spaces like the one observed, where each mode has their specific space or lane, could be made more flexible. The space wouldn’t necessarily be shared but designed so as to encourage cyclists to slow a little, pedestrians to be more aware and for both modes to communicate more.

This type of communication led infrastructure can lead to complications, especially around power dynamics. With more reliance of human interaction and communication, human bias and prejudice comes in to play – especially judgements and decisions made on identity, such as gender, race, or class. There are also established criticisms of shared space from people with disabilities, especially visual. For these reasons, any design would have to be made sensitively and with repeat follow up observations of the area.

Conclusion

Cycling is an increasingly important and popular mode of transport with extensive benefits both to society and to the individual. Cities, including Stockholm, are beginning to reflect this with new infrastructure being built regularly. However, cyclists and pedestrians share spaces and interfaces, and as the number of cyclists go up, we could see an increasing amount of tension between the two modes. Historically this has affected the discourse around cycling, often meaning they are painted as the villain and leading to an eventual decrease in the number of cyclists.

To better understand what is going on at these shared spaces or interfaces, a zebra crossing was chosen where I could observe cyclist’s social interactions and physical reactions when co-present with pedestrians. I observed the spot with my own eyes, pen and paper, but also a video camera. Using the recorded films, I filled in an observiaire, a form of questionnaire specifically designed to collect observations. Beyond the analysis of cy-ped interaction itself, the thesis also aimed at developing this new method for studying mobility.

The results were considered through two lenses. The first, the practice of cycling, that is the feeling and the being of doing cycling. How cyclists act, what they desire and what they are – specifically, the cyclist as a hybrid which desires flow. The second, the street as a space of sociability. That the acts of the users of this space are communicative and cooperative, and therefore can be seen as sociable.

The results from the observiaire showed that cyclists are more likely to physically react to pedestrians than socially interact, however the observations suggested that maybe something else was going on. I observed a possible invisible communication between road users, that the study couldn’t capture but it could sense – this included subtle movements and glances, reading of bodies, and involved people not directly looking at or communicating with each other. I term this peripheral communication. Part of this is the communication that cyclists are able to do with their physicality – the placement of their bike or shape of their body – which could partly explain why more reactions were collected that interactions. This suggests that cyclists are co-creating the crossing as a space of sociability.

The results also showed, both in-person and via the observiaire, that when there are pedestrians present cyclists will do almost anything except stop. Although this may at first seem like a selfish, antisocial act, when you look at the practice of cycling itself you begin to understand the importance of flow and momentum. Partly this is because of the intrinsic role that momentum plays within cycling, but it is also because of efficiency. The effort which it takes for cyclists to stop and start regularly in a journey is often underestimated. So, when the cyclist only slows slightly, or weaves around the pedestrian, this is actually the cyclists balancing their desire for efficiency with their wish to create sociability. The space is being renegotiated by cyclists, they are challenging the space and its constructions, and co- creating it according to their wishes and needs.

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Appendices

Contents

Appendix 1, In-person observation template…………………………………………….. 57 Appendix 2, Observation 1, Preliminary Studies...……………………………………….. 58 Appendix 3, Observation 2, Traffic Count…..…………………………………………….. 59 Appendix 4, Observation 3, Pilot Study.…….…………………………………………….. 61 Appendix 5, Observation 4, Lunchtime.…….…………………………………………….. 63 Appendix 6, Observation 5, Morning……….…………….……………………………….. 67 Appendix 7, Observation 6i, Afternoon [CANCELLED]...……………………………….. 71 Appendix 8, Observation 6ii, Afternoon.…….……………………………………………. 73 Appendix 9, Time periods.…….……………………………………………………………. 76 Appendix 10, Collated results of the in-person observations…………………………. 77 Appendix 11, Issues and recommendations…….………………………..……………… 80 Appendix 12, Observiaire amendment and removals……………………….…………. 81

Appendix 1, In-person observation template

Appendix 2: Observation 1, Preliminary Studies

The purpose of this session was: partly to try out the method itself; partly to see what type of actions, behaviours, movements I could observe; and partly to start trying to find a location. I was joined by my supervisor at WSP, Fanny Larsson.

The observations were short, often just 5 to 10 minutes and took place over four locations on Södermalm, a large, densely populated island in the centre of Stockholm. The locations were chosen because we felt there would be high levels of interactions between pedestrians and cyclist. Simple notes were taken on paper, describing interesting or notable things that we saw, as well as the conditions and context around the location.

After the session we recorded reflections that would go on to inform the design of the study: the importance of a good quality camera; that filling out the observiaire would have to be done with video (it was much too long to do in-person); my chosen position should be able to read the faces of the observed cyclists; that there are certain ‘subtleties’ of behaviour that may not ‘fit’ within the observiaire, there needs to be space to collect these. Perhaps most importantly, we realised that the choice of location should not have too many things ‘going on’ - that is, a limited amount of transport modes and surrounding attractions.

I also noted certain commonalities amongst the cyclists observed, these would inform the next stages of the study and what would be studied exactly. These include: cyclists slowing or moving around for pedestrians but not stopping (often judging the speed and trajectory of pedestrians and working around that); use of the bell as a warning device; pedestrians using the space in ways it wasn’t designed for.

Appendix 3: Observation 2, Traffic Count

Note: Stockholms stad had not yet started releasing daily or weekly cycling flow figures as part of their response to the Covid-19 pandemic, hence the need for me to collect these figures myself (Stockholms stad, 2020a)

Although the observation location had been chosen by this point (this will be discussed below, the next stage of the study was delayed due to the Covid-19 pandemic as social, working and living conditions changed rapidly. Working from home was recommended, the transport network (SL) reduced services, certain risk groups were told to isolate and large gatherings were banned. At this point it was feared that a stricter lockdown was coming, similar to the rest of Europe, so I wanted to get the observations done as soon as possible. However, before we could carry them out a traffic count would be needed as it was not yet sure how the crisis had affected mobility patterns. It should be stressed that this is not an exact, proper traffic count, rather a rough estimate.

I started by finding the cycle flow figures (expressed as cyclists per day, or cpd) at certain points in the city centre on the Stockholms stad website (2020b). These went back a few years so I could compare previous years with this one. Then, I chose three locations (Munkbron, Stadshusbron and Skanstullsbron) which were key locations for cyclists as they connect various islands around the city centre. Both Stadshusbron and Munkbron be found on either side of the chosen observation location, Vasabron. I then chose a Wednesday with relatively good weather for the time of year - mixed sun and cloud, temperatures between 10 and 14 centigrade, overall good for cycling - and chose a time around the evening rush hour.

The count was calculated as follows. First, I took the data from both March and April 2016 through to 2019. This time period was chosen, partly because the data for Skanstullsbron only went back to 2016, and partly because previous data may be out of date due to the rapid expansion of cycling levels in recent years.

Second. To work out a base level of flow to compare the present day with a simple calculation was made. Presuming that all cycle traffic is between 7h and 22h I worked out an hourly average across those 15 hours. It goes without saying that this is not exact, or reliable but is rather a best guess or estimate, true accuracy was sacrificed to enable easy collection and comparison.

Third. At each location I counted for 10 minutes at a time before multiplying this number by 6 to reach an ‘hourly flow’. This is a technique recommended for public life observations by Gehl and Svarre, who state that ‘10 mins, once an hour is a good image of city life’ (2013, p25). For each observation I stood at a spot where I could easily see both traffic lanes without being in the way or too obvious. I counted using an app on my phone. The app was ‘Tally Counter’ from Pixel Research Labs Inc. and was free of charge.

There were significantly more cyclists on March 25th than in previous March’s. Over 200% increase in all cases. Even if you were to take March 25th as an April day there is a significant increase.

March Skanstullsbron Munkbron Stadshusbron Total

Past 20164 (cpd) 3050 3700 2900 9650

2017 (cpd) 3500 4400 3350 11250 2018 (cpd) 2100 2600 2000 6700 2019 (cpd) 3600 4400 3150 11150 Monthly Avg (3yrs) 3062.5 3775 2850 9687.5 p/hr 204 252 190 646 Present Time 16:47 17:08 17:24 10 min count 113 131 112 356 p/hr 6785 786 672 2136 % difference 232% 212% 254% 231%

April Skanstullsbron Munkbron Stadshusbron Total Past 2016 (cpd) 5150 6600 5050 16800

2017 (cpd) 5300 7200 5400 17900 2018 (cpd) 5600 7200 5550 18350 2019 (cpd) 5450 7550 5950 18950 Monthly Avg (3yrs) 5375 7137.5 5487.5 18000 p/hr 358 476 366 1200 Present Time 16:47 17:08 17:24 10 min count 113 131 112 356 p/hr 678 786 672 2136 % difference 89% 65% 84% 78%

4 Data for Stadsbron only goes back to 2016, so all averages have been taken from that date. 5 10 min count simply multiplied by 6.

Appendix 4: Observation 3, Pilot Study

This was the first observation at the chosen location, and where we could test a number of different aspects of the study. This was strongly recommended by my colleagues at WSP as it allows you to find issues with your data collection methods and find the best location to place yourself and the camera. As they put it, there are always unexpected things that will not be evident until you are at the place.

On this day we (Fanny joined me again) observed for 20 minutes, taking notes and making sure we had the optimum location for being able to see both sections of the bike path. Sure enough we had issues, for example the camera had to be further back than we would have liked so that it could fit everything we wanted into the shot; the sun was shining directly into the camera; and it was very cold, especially with the wind coming off the water!

Codes The following codes will be used as shorthand throughout each appendix with an Observation in.  Cy - cyclist  Pd - pedestrian  Lh/Rh - left hand/right hand  Nb/Sb - north bound/south bound  ZC - zebra crossing  F/M - female/male

Pre-conditions Weather  Sunny in the morning, mixed during the day with brief snow and hail showers.  Cold, between 0-3 degrees, with a light wind. Feels like -2 to -5. Smhi.se - accessed 30 March  Mostly clear, with a mix of sun and cloud, at times very bright.  Sun in from start till about 11 minutes in, then in and out until about 18 minutes when it is out for the rest of the recording.Sun towards the camera, meaning Sb Cy are turning into the sun when going R, across the ZC Time  Started recording at 17.15. Evening rush hour, usually busy. Road Conditions  Clear and dry, no obstructions. Other  Noise levels  Normal to quiet for a city centre. Roar from centralbron is quite loud, as is the occasional train crossing the same point. Loudest when vehicle traffic passes just in front or just behind the camera.  Covid 19  Advice at this time is the same as Observation 2, except gathering of over 50 are no longer allowed.

In-person Observations Specific happenings

Time Observation Direction

17.23 Man carrying box in one hand while cycling N

17.24 Cy singal left, with Cy behind her copying her immediately N

17.24 Bike coming from east going on bike lane N

17.25 Girl on e scoorter stops to text next to ZC N

17.26 Female pedestrian crossing from east to west where there is no zebra. W

17.29 Blue Cy rings bell multiple time as jogger was in the bike path (likely out S of shot)

17.30 Cy wait for F Pd with blue scarf as another Cy cuts them up instead S

17.31 Cy in green waits for ped, but doesn’t fully stop S

17.32 Cy with yellow bike rings his bell for 1 ped who wasn’t at the junction, S using the bell as a general warning

17.33 Cy comoing from E going on to bike lane N

17.40 Cy comes to complete stop, feet down, for a Pd S

17.43 F Cy looking opposite way of where she’s going S

General observations  Some people signal with their arm when turning, following the bike lane, and some do not  Is this influenced by those around them? Do people signal together?  Pedestrians Sb have to look 180 over their shoulders to look for cyclists or cars turning across, and many do, however runners rarely look  Are they in the same type flow as cyclists are - they don’t want to stop  Pds come to the ZC in a more steady flow, bikes comes in waves or clusters  Cyclists Sb are on the brakes anyway, due to downhill and sharp corner  Easier for them to stop?  Nb Cy are pedaling harder to get thru the junction, esp those on city bikes  Nb Cy also tend to cut into the Sb lane  Energy saving?  Sb peds v unsure if cyclists will stop, there is no siteline  Often use their peripheral vision to check for bikes  Cy v rarely fully stop for pedestrians

Appendix 5: Observation 4, Lunchtime

Before this observation I had finalised my observiaire, taking on board what had been learnt above, so that it took the form you will see in the Appendices now. These observations were made with Fanny and we actually observed for 75 minutes, 15 minutes over what we intended, however we both reflected that this was too long to keep full concentration for and agreed 60 minutes would be best for the next two sessions. Having two people is also helpful, it allows you to compare what you have seen and, if two incidents happen close to each other in time, to write each down separately.

Pre-conditions Weather  Sunny, clear. Slight breeze from the west. Between 6-8 degrees, feels like 3-5, warm in the sun. Sun is shining from the south, and so is in the eyes of Sb cyclists Time  Started recording at 11.15. Second video starts at 12.03. Lunchtime, when workers may be grabbing lunch/running errands. Maybe those distancing will be exercising at peak of light/warmth? Road Conditions  Dry, clear. No gravel/grit. Other  Noise levels  Normal  Covid 19  Advice at this time is same as Observation 3, except a ban on visits elderly homes has been introduced. I expect this will have little effect on traffic levels here.

In-person Observations 6 Specific happenings

Time Observation Direction

11.17 F Nb Pd sped up and jogged across ZC even though there was EP 1.05 no traffic around

11.18 M Cy on cargo bike, cut corner completely N EP 02.30

11.19 M Cy, courier, came wrong way up 1 way street (L of camera), N EP 03.35 took the road and cut across traffic lanes

11.23 Sb F Pd willing to stop briefly for a F Cy - eye contact made but N EP 07.05 nothing else - some sort of silent understanding between the two

11.24 M Cy, Foodora, realises he can’t stop for F Pd (Sb) in time and N EP 08.30 raises hand in apology - she slightly nods and smiles in understanding

11.25 M Cy signals L with LH, no other Cy or Pds around N EP

6 Note: EP, refers to myself, Edward Prichard; FL, to my supervisor from WSP, Fanny Larrson.

09.55

11.29 M Cy, following a F Cy, rings bell several times at a SB F Pd on S EP 13.50 her phone w/ hedaphones in, not looking out for cyclists. M Cy seems annoyed with F Pd, even tho she has RoW

11.31 F Cy, slows and weaves around 2x NB F/M peds, almost making S EP 15.40 a 90 degree turn

11.31 M Cy almost comes to a complete full stop for F Sb Pd S FL 15.45

11.34 2x Sb M/F elderly Pds slow to an almost stop for a Nb Cy, a Sb F N EP 18.35 runner overtakes them all

11.38 2x F Pds stop, one on kerb, other on the ZC, to let F Cy from E go N FL 22.15 onto the bike lane. Cy doesn’t end up crossing the ZC, but also doesn’t signal in any way.

11.39 M Cy, followed by another, brakes v heavily to let a F Sb Pd S EP 24.30 cross. Brakes so hard the back slips out (out of shot) (Racer bike). Pd looks back before she crosses ZC, sees this and waves hand in thanks.

11.40 2x Sb F Pd with prams (Strollers) stop to let Nb Cy through (had N & S FL 24.25 enough time and speed to stop). Meanwhile a Sb Cy slows to let the Pds cross.

11.43 F Sb Pd in blue coat (on phone) waits for 2x Nb 1x Sb Cy to pass N & S EP 27.25 - her RofW

11.45 M Sb Cy makes full stop. Many Pds at ZC: 2x Nb, 3x Sb, 1x Wb Sb FL 29.00

11.52 F Cy slightly slows down to allow Sb Pds to cross ZC. N FL 36.10

11.53 F Nb Pd with stroller stops to let Cy from E enter bike lane. Cy N FL 37.10 doesn’t signal.

11.55 2x Cy (Nb & Sb) and 3x Pds (2x Nb & 1x Sb jogger) at junction at N & S EP 39.30 the same time. Sb Cy near stops, touches floor with foot several times. Nb Pds cross, hesitantly. Jogger takes advantage of confusion and goes through without slowing. This plus Nb Cy approaching in wrong lane confuses Sb Cy more.

11.58 M Cy potentially speeding up to pass ZC before Sb Pd arrives S FL 42.25

12.01 2x NB Cys approach ZC quickly (10m apart maybe) and M Sb Pd N FL 45.40 barely stops, goes between cyclists. Has to speed up as he leaves the ZC to avoid the 2nd Cy.

12.03 F Cy comes to a full stop, letting 2x F/M SB Pds pass over the S FL 00.10 ZC.

12.06 M Sb Cy keeps rolling, looking like he expects to pass the ZC just S FL 02.25 before 2x Sb Pds. Makes a wide turn to make sure they have space needed.

12.11 SB Pd Runner switches from pavement to bike lane. No flat S FL 08.00 surface in the direction he wants to run so takes bike lane. Also, best way to get to N of GStan without reaching a light. Blocks 2 Cy further on up the path.

12.12 Sb M Cy slows and turns tightly as a Nb M Cy comes the other S EP 08.50 way.

12.12 F Cy makes a near full stop for 2x Nb Pds. S FL 09.00

12.13 2x M/F Sb Pds stop for 2x M/F Nb Cys. Cys also slow. No eye N EP 09.50 contact

12.17 Sb M Pd & M Cy slow to almost stop, hesitation from both but the S EP 13.55 Cy lets Pd go but cuts on to the pvmt to keep flow going.

12.20 1x M Sb Cy cuts across ZC as 1x F NB Pd is stepping onto it - no N & S FL 17.15 danger however. Then, 1x M Nb Cy reaches ZC same time as 2x Peds. 1x F Sb approaching, bends walk around the back of Cy, 1x M Nb already crossing goes straight ahead. Cy slows, still pedalling, then goes behind M Nb Pd.

12.23 Sb M Cy signals R with RH (M Cy behind him). Nb F Cy also N & S EP 20.00 signals, L with LH.

12.24 F Cy keeps on rolling past ZC between 2 Pds (plenty of space) S FL 20.20

12.26 M Nb Cy takes other lane to avoid Sb ped in ZC. N EP 22.30

12.27 M Cy signalling L with LH. N EP 23.25

12.28 F Nb Cy looks both ways, in an obvious way, with 2x Sb M&F Pds N EP 24.35 approaching crossing and 1x Nb F Pd coming up to the ZC. Keeps speed, slows a bit, carrys on through.

12.28 F Cy coming from S (L of camera) on pavement, joins the bike N FL 24.45 path heading Nb. In front is F Nb Pd, also in bike path. F Nb Cy comes from W and weaves between the two using opposite side of path.

General observations  EP  Possibly more cargo bikes than last time  Possibly more Nb Cy than Sb  Cars have v little influence on what goes on at the ZC  Cy and Pds mainly interested in each other

 Are people looking at body language not facial expressions? Reading body movements and shapes?  Sb bikes are more likely to stop  Because they’re already on the brakes?  Because they’re aware Pds aren’t able to easily see them and look for them  Although we are visible, and get suspicious/curious looks, the decision making process and judgement needed for the junction tends to distract people from our presence.  FL  Biking to the site and pulled up to make a full stop just short of the ZC. M Cy behind, cargo bike, was upset and shouted ‘You cannot just stop like that’ and weaved around.  Some suspicious look when recording.

Appendix 6: Observation 5, Morning

The day before, SL had actually requested people not to take public transport unless they had no other option (SVT, 2020). It is not clear the effect this had on the flow during this observation, however as we were looking for a high flow it’s not expected that this would affect the study negatively.

Pre-conditions Weather  Sunny, clear. Between 2-5 degrees. Feels like -1 - 1.  Light breeze from the west. Sun in eyes of Sb Cy from 08.10/15ish Time  Started recording at 07.30. Road Conditions  Dry, normal. Other  Noise levels  Above normal due to noise from the construction site behind.  Covid 19  Advice is largely the same as Observation 4, except that SL has requested people not to take public transport.

In-person Observations Specific happenings

Time Observation Direction

07.30 3x N Cy as F Pd walks up to ZC. 2 of the Cy look for eye contact N EP 00.40 (unsuccessfully)

07.31 M Cy slows down goes between 2 Pds (N&S) S EP 01.45

07.31 F Pd checks walk, to a brief stop, to allow 2x Cy to pass N EP 01.55

07.32 F Cy takes risk, passing just in front of a M Nb Pd - uses the other N EP 02.55 lane, v close to kerb - the pedestrian seems unperturbed. Neither looked at each other.

07.32 M Cy brakes for a little bit for F Pd crossing ZC. N FL 03.55

07.34 M Cy stops pedalling for a moment to let M Nb Pd pass. N FL 04.50

07.35 F Sb Cy comes to a near stop for M Sb Pb - at same time Nb Cy S&N EP 05.30 has to slow for them but crosses in front. Pd sees and looks at Nb Cy, but doesn’t realise Sb Cy is there.

07.38 3x M Nb bikes approach ZC whilst F Nb Pd is on it, Pd jogs to the Nb FL 08.35 end of the ZC (probably not needed).

07.39 2x MF S Cy + 1x M N Cy - all approach the corner at once, and all N&S EP 09.10 slow down to allow each other the space to take corner safely.

07.40 M Sb Cy slows down to almost stop to let M Nb Pd cross Zc S FL 09.50

07.40 1x M N Cy overtakes 3x other Cy on the inside of the corner N EP 10.25

07.41 2x MF Nb Cy avoid eye contact with 2x M Sb Pd who is crossing N EP 10.55 the ZC (2x on phone). F Cy weaves around, taking a wide line, M Cy slows more and moves behind the 2nd Pd.

07.42 F Nb Pd near stops for F Nb Cy at ZC - RoW w/ Pd N EP 12.15

07.43 M Nb Cy overtaking on the inside of the corner. Uses pavement. N FL 12.55

07.46 2x MF Nb Pd cross w/ confidence, 1x F N Cy stops pedalling and N EP 16.05 adjust

07.46 F Nb Cy stopping to pedal to let Pd through ZC, 1x M Nb Cy goes N EP 16.10 in front of Pd and takes wide curve.

07.52 M Sb Cy brakes slightly to let Nb Pd through ZC S FL 21.55

07.53 F Sb Cy signals with smile and wave of head for elderly F Nb Pd S&N EP 23.05 to cross (with sticks) - she makes eye contact to nod thanks. Cy stops, putting foot down. 2x MF Nb Cy also slow.

07.53 F pd stops to look properly before crossing ZC as 2x M Nb Cy N FL 23.20 pass

07.54 M on e-scooter stops to let Pd through N FL 24.05

07.55 4x Nb Cy don’t stop for Nb Pd - Pd has to slow their walk N FL 25.10

07.56 M Sb Cy stops to let other Nb Cy pass before leaving bike lane to S FL 25.55 car lane

07.58 M Sb Pd (w/ flat cap) stops as 2x M Nb Cy go past without N EP 28.30 stopping. 1x M Nb Cy slows for him. Pd nods and waves thanks and Cy nods in welcome.

07.58 2x F Nb Sb Pds stop at ZC as 2x F Nb Cy go through. 1x M Sb Cy S&N FL 28.35 stops to let others through. F Nb Pd waves in thanks.

07.59 F Pd stops to let 3x Nb Cy (2x F 1x M) pass first. Last F Cy should N FL 29.25 have stopped but cuts corner, allowing Pd to start crossing.

08.02 2x Nb MF Pds on ZC, 1x just stepping on, 1x stepping off. N EP 31.45

2x Nb MF Cy approach. 1st Cy cuts corner, in front of M Pd causing him to check his walk. 2nd slows and goes round the back of him.

08.02 2 Nb Cy stop pedalling to let F Sb Pd cross ZC - pd smiles in N FL 32.15 thanks (NOT VISIBLE ON VIDEO)

08.04 M Sb Cy slows and crosses on ZC to continue directly S after S FL 33.52 other Nb Cys have passed.

08.07 2x Nb Cy slow significantly for 2x M Nb Pd. N EP 37.35

08.07 F Sb Cy slows to near stop to let Pd cross as other Cy pass S FL XX anyway.

08.09 M Nb Cy close passed a M Nb Pd. Cuts corner into oncoming N EP 39.20 lane.

08.09 F Nb Cy makes a full stop for 3x Pd (MFM Sb) to cross ZC - queue N FL 39.30 forms behind (2x - 1 stops 1 slows)

08.10 2x M Nb Cy - 1st one is v unsure, slows alot, wobbles, the 2nd N EP 40.30 undertakes as 1st out his LH to indicate and swings that way.

08.12 F Sb Cy slows a little when approaching corner as 8x NbCy are S FL 42.25 coming the other way.

08.12 3x Nb Cy, signalling issue as 1st F Cy goes R & 2nd M Cy gets N EP 42.25 stuck behind. 1st F signals R and 2nd M signals L as 3rd M undertakes them both. 2nd M follows 3rd M.

08.13 M Sb Cy brakes significantly way before the ZC so 1x M Nb & 1x S EP 43.50 M Sb Pd have time to cross, and allows Cy to build up speed earlier.

08.15 4x Nb Cy as M Nb Pd approaches ZC. Jogs across, in between N FL 45.30 1st and 2nd Cy.

08.15 F Nb Pd with obvious limp comes to ZC, M Nb Cy speeds up to N EP 45.40 get through the junction before her.

08.22 M Nb Pd walks between 2x Cy - with confidence, Cy don’t seem N EP 05.00 phased either.

08.22 M Sb Pd crosses ZC as several Cy move around him. He seems N&S EP 05.35 confident, and comfortable with this.

08.27 F Nb Cy slows a bit, but F Nb Pd signals with hand for Cy to go N FL 09.35 first.

08.28 M Nb Cy slows for M Sb Pd, uses other lane but then cuts back to N EP 10.45 avoid an oncoming Sb Cy. General observations  EP  Nb Cy will cut corner, into the other lane, to avoid having to stop for Nb Pds

 More bikes at this time taking the Nb car lane, instead of the bike lane  If peds take the ZC ‘confidently’ and ‘reliably’ then Cys will move around them - the issues come when confusion and lack of confidence are shown. The Cys seem to be looking for predictability.  Perhaps the speed of decision making calls for this?  Might be easier to cross the ZC by avoiding interactions, as a Pd, than to look for eye contact/communications. Force the Cy’s to work out what you’re doing from your body language. Maybe this is how people talk to each other?  As observers, we are more noticeable to Nb Cy than Sb ones.  FL  Many Nb Cy’s are cutting into the inside of the corner.  Some of these are using this to overtake.  Sb Cy are already on their brakes most of the time and do not have a problem slowing down or stopping to let Pds through.

Appendix 7: Observation 6i, Afternoon [CANCELLED]

Pre-conditions Weather  Cloudy, overcast. Around 8 degrees. Feels like 4. Much windier, gusts got heavier and heavier until I had to stop at 14.30. Time  Started recording at 14.00, had to curtail at 14.30 due to weather. Road Conditions  Dry, clear. Other  Noise levels  Normal for the location.  Covid 19  Advice at this time is same as Observation 5.

In-person Observations Specific happenings

Time Observation Direction

14.00 F Nb Pd waves hand in thanks to SB Cy who has slowed down. S 00.00

14.01 Very unsteady F Nb Cy slows down as Sb Cy approaches. S&N 00.45

14.02 F Sb Cy slows a fair distance from the ZC to allow MF Nb to S 01.15 cross.

14.04 Cy coming S, turns L (E) over the car lanes - a Sb car lets him S&E 04.15 cross and Cy waves in thanks

14.05 M Nb cy signals L at ZC with no Cy or Pds nearby N 05.15

14.10 F Sb Cy uses pavement as 2x M Nb Cy come to the corner at the S&N 10.15 same time. The 1st of Nb Cy looked as if he wanted to cut the corner before he saw Sb Cy.

14.12 F Sb Cy slows to allow M Nb Pd to cross. S 12.15

14.1313.40 F Sb Cy slows to allow M Sb Pd to cross. S

14.14 I STRAIGHTEN THE CAMERA DUE TO WIND -

14.15 CAMERA NEARLY FALLS OVER - 15.20

14.18 2x F Sb Pds at ZC; 2x F Sb Cy. 1st goes through in front of Pds; S 18.40 2nd brakes and goes behind them.

14.19 2x MF Sb Pds stop at the ZC and allow Nb Cy to pass N 19.45

General observations  EP  Noticably quieter in terms of Pd and Cy traffic.  The wind started fine and manageable, but within 15 minutes became a problem. Around 14 mins in I had to straighten the camera because of it, at around 15 mins I had to catch the camera as it fell over! I struggled to keep it stood up with my body, and take notes at the same time. After another 15 minutes (luckily the low levels of cyclists meant missing observations wasn’t a fear) I decided to throw in the towel. Many cyclists were really struggling to cycle, and I thought it would affect their decision making - ensuring the results would not be comparable with previous sessions.

Appendix 8: Observation 6ii, Afternoon

Pre-conditions Weather  Sunny clear, warmest day of the year at 15 degrees. Occasional gusts from the W. Sun around the SE and in the Sb Pds and Cys. Time  Started recording at 14.15 - 15.15. Road Conditions  Dry, clear. Other  Noise levels  Normal for the location. No construction work noise.  Covid 19  Advice at this time is same as Observation 6i.

In-person Observations Specific happenings

Time Observation Direction

0.55 M Nb Cy weaves between Pds (1x F Sb; 2x F Nb) - Cy calm and N doesn’t communicate

1.05 2x M Nb Cy, 1st weaves around Sb M Pd and then gets confused - N shapes to head E then stops, goes back to Nb but doesn’t indicate or communicate this causing the 2nd Cy to slow and allow him to rejoin path

4.00 M Nb Pd waits for F Nb Cy, a faint nod and smile of thanks from Cy N

6.00 Older MF Sb Cy - M takes ZC heading S, the F stops without signalling S so M Cy must weave out of her way (a 2nd M Cy has to go around her) and gets off in the bike lane ( 3rd M Sb Cy has to take the other lane to avoid her). She tries to cross as a Pd w/ bike, 2 MF Nb Cy go through the ZC so she has to wait, delaying her.

9.00 Mf Sb Cy, 1st Cy slows down early and lets Sb F Pd cross and then S cuts corner onto the Pvmt for no real reason

11.05 F Sb Cy, slows for M Sb Pd to cross - Cy unsuccessfully looks for eye S contact

12.35 F Sb Cy coasts patiently behind a M Sb skater S

13.20 M Sb Cy (courier) jumps from bike lane onto the carriageway (out of S shot), avoiding the junction and carrying on S

13.35 M Sb Cy comes to near stop for 2x Nb Peds. Slows for 1st as he S approaches, then the 2nd reaches the ZC as he does - gestures for her to cross with his RH, hard to see if she does anything in reply. V nearly stops completely.

15.45 MSb cy heads S w/out signalling- small confusion with oncoming Nb S Cy, who Sb weaves around

18.10 2x MF Pds comes from the quay and cross the cycle path diagonally N without properly looking - some confusion from one of two Nb F Cy, F Pd run ahead to avoid the bikes, M Pd walks behind them. At the same time, a M Nb Pd stops at the ZC to use phone, letting the Cys go past

22.50 Sb M Cy heads S without signalling. S

24.50 Sb M Cy slows long before the ZC to let a Sb M Pd cross S

25.15 Sb M Cy slows long before ZC to let Nb Pd Cross S

26.20 Sb M Cy goes straight on (S) without signalling, leading to confusion S out of shot with a Pd using the ZC to the L of the camera.

26.30 3x M Sb cy slows for Sb M Pd. S

27.40 Sb F Cy slhows significantly (almost stop) to allow FM Sb Pds to cross, S Pds see at the last minute and hesitate before crossing - but there is no visible communication between them.

28.25 Sb M Cy cuts corner. S

29.25 M Nb Cy uses other lane to avoid 3x MFF Sb Pds on ZC. N Immediately after a M Nb Cy signals L.

29.50 2x MF Sb Cy (1st, F signalling with RH) slow for M Sb Pd S

30.10 Family of Sb Cy. F Cy tells her daughter to turn R, which she does, S then slows and signals for M Sb Pd to cross. Pd says thanks. M Cy behind her also slows.

31.30 M Sb Cy cuts corner with 2x N&Sb Pds on ZC S

32.25 M Sb Cy slows significantly on the brakes for MF Nb Pds S

33.55 F Sb Cy goes between 2x MF Sb Pd groups; M Cy following slows S significantly for the 2nd group and passes behind them as they’re on the ZC

34.55 2x Sb M Cy slow for 3x Sb MFM Pds S

40.50 Sb M walking in bike lane confidently, Sb Cy moves around him, using S the corner of the pavement.

43.50 Sb M cy slows for Sb M Pd (who’s distracted by me) - few seconds S later a Nb Pd checks his walk for a Nb Cy

45.20 M Nb Scooter, looking v ill with a mask on (had passed the other way N earlier in recording), approaches ZC quickly, with 2x Nb MF Pds on it. Further 2x Nb M Pds waiting to cross. This means he moves to wrong side of the bike lane, but there’s a SB M Cy approaching, the Cy has to

take the other lane as well to avoid him. The scooterist swerves back to his lane as another Sb Cy approaches.

47.05 Sb M Cy signals R with M Cy behind S

49.20 Nb M Cy speeds up to cross the ZC before 3x Sb MF Pds N

03.45 2x M Sb Cy approach ZC at same time as 2 groups of Sb Pds (2x M, S 1x M)- the 1st Cy close passes in front of the first group of Pds, the 2nd Cy cuts between them.

5.25 1x F Nb Cy join junction from E, wait for Sb F Cy to go first. N

5.50 Sb F Cy slows for Nb M Pd S

8.50 Sb F Pd with pram slows for Nb M Cy N

9.50 Sb F Cy slows for Nb M Pd S

09.55 Sb M Cy signal R, no one around. S

10.15 Sb M Cy slows significantly for 2x Sb Pds - Cy cuts corner to avoid S them and to avoid stopping

General observations  EP  More types of mobility around - skaters, scooters, rollerblader  People move a little slower (as noticed by Gehl, summer = slower moving speeds)  More Cy going to the S (left of shot)  More couriers around (corona effect?)  Higher flow than 6b  But, no consistency to the flow of Cys, occasional rushes, long periods of nothing; Peds seem to come at a more  Warmth and sun turns this spot into a recreation spot, not just a place to transit through - sitting on the Quay, stopping to talk on the phone (standing and sitting), people fishing

Appendix 9: Time Periods

As one of the aims of this thesis is to compare cyclist’s behaviour in different flows, I had to try and choose times which would produce three flows that were different enough that they could merit comparison. As there was no hourly data on flows I had to estimate. I chose: morning rush hour (Observation 5, 7.30-8.30), which is traditionally the highest flow of the day according to my colleagues at WSP; lunchtime (Observation 4, 11.15-12.15), which I hoped would provide a medium flow as people ran errands, fetched lunch etc; and mid- afternoon (Observation 6b, 14.15-15.15), which was supposed to provide a low flow. After collecting the data, I noticed that Observations 4 & 5 had similar flows, and that 6 was some way below. I also noticed that the cyclists were coming intermittently - the number of ‘cyclists per minute’ was not consistent throughout the hour of observation. To ensure a more even distribution of cph I pulled two twenty minute segments and one thirty minute segment from the videos.

The thirty minute segment had the lowest cph, whilst the two twenty minute segments had the highest cph, and a cph just short of the midpoint between the two, respectively. I originally had the lowest flow segment at twenty minutes, however this produced a sample of 51 cyclists which, when I had processed the data and turned it into tables and graphs I could see that some of the figures could be possibly be unreliable. For example, when comparing certain variables sometimes the amounts were less than five. So, in order to expand the sample size to a more reliable number of cyclists I added an extra ten minutes. As the ultimate figure that is to be compared is the cph and not the number of minutes observed I don’t see this being an issue, it did lead to a small increase of cph from 153 to 172. Although the medium flow is not perfectly in the middle, it was the closest I was able to reach with the data collected.

Flow Video No. of Cyclists Video length (m) Flow (cph)

Low 4a 54 20,00 162

4a 32 10,00 172

Medium 6b&c 101 20,00 303

High 5a 260 20,00 780

Total 447 60,00 447

Appendix 10: In-person observation, collated results

Once all the sessions had been completed, I compiled the observations and started to collate and categorise them – which is what you can see here.

I took each recorded happening and tried to find other happenings that were like it, using the time stamp and video as reference. For example, at 45.40 of video 4a I noted that a pedestrian sped up when crossing the zebra crossing. This could then go within a category of ‘pedestrian hurries to cross’. Within this I saw instances of when this happened due to the presence of a cyclist at the crossing, and once when there was no one around. This was then joined by other categories and put into wider groups, so this one went within ‘Ownership of the space and the ‘rights of way’’.

Collated results

Note: Pd = Pedestrian; Cy = Cyclist; ZC = Zebra crossing

Ownership of the space and ‘rights of way’  Some Pds will speed up when the cross the ZC  Sometimes to get out of the way of Cy  (4a:45.40, 5a:08.35, 5a: 45.30)  Sometimes for no real reason  (4a:1.05)  Is this a feeling of ‘unsuperiority’?  Do they see the space as not theirs, dangerous, that they need to escape it?  Some Pds willing to stop for Cy  (4a:7.05, 4a:7.05, 4a:8.30, 4a:18.35, 4a:24.25, 4a:27.25, 4b:09.50, 5a:12.15, 5a:28.35, 5a:29.25, 5b:09.35, 6a:19.45, 6b:04.00, 6b:06.00, 6b:18.10)  Or check their walks for Cys  (5a:01.55, 5a:23.20, 5a:31.45, 6b:43.50, 6c:08.50)  Cy ignore Right of Way for Pds  Sometimes they ignore the Pds Right of Way and continue over the ZC (though may slow, weave around them)  (4a:24.25, 4a:27.25, 4b:17.15, 5a:25.10, 5a:28.30, 5a:28.35, 5a:31.45, 5a:38.00, 5a: 45.30, 6a:18.40, 6b:0.55, 6b:01.05, 6b:06.00, 6b:31.30, 6b:33.55, 6b:43.50, 6c:03.45)  Sometimes they treat them as an annoyance  (4a:13.50)  Pds treating the space with confidence seems to force Cy into considering them more, they will move and adjust accordingly  (5a:16.05, 5b:05.00, 5b:05.35,6b:40.50)  Runners show similar behaviour to cyclists  Often ignoring others using the ZC and their agreements with each other (eg, if a Pd stops for a Cy or vice versa), often cross confidently taking ownership of the space,  (4a:18.35, 4a:39.30, 4b:08.00)

Flow  Cy cutting corner, when safe and sometimes when not  (4a:2.30, 5a:02.55, 5a:10.25, 5a:39.20, 6b:28.25, 6b:31.30)  Even onto pavement  (4b:13.55, 5a:12.55, 6a:10.15, 6b:09.00, 6b:40.50)

 Cy very rarely put their foot down  Will go through all sorts of different maneuvers not to stop completely  Slow down a little, just checking their speed a bit  (4a:36.10, 5a:03.55, 5a:04.50, 5a:16.05, 5a:16.10, 5a: 21.55, 5b:09.35, 6b:26.30, 6b:29.50, 6b:43.50, 6c:05.50, 6c:09.50)  Slow down much before ZC  (5a: 32.15, 5a:43.50, 6a:01.15, 6b:09.00, 6b:24.50, 6b:25.15)  Swing widely, going around the corner, or cut it  (4a:13.50, 4b:2.25, 4b:22.30, 5a:02.55, 5a:12.55, 5a:16.10, 5a:29.25, 5a:31.45, 5a:39.20, 5b:10.45, 6a:18.40, 6b:29.25, 6b:31.30, 6c:03.45, 6c:10.15)  Slow down to almost stop, so they just creep forward  (4a:15.45, 4a:24.00, 4b:09.00, 5a: 05.30, 5a:09.50, 5a:37.35, 5a:38.00, 6a:12.15, 6a:13.40, 6b:11.05, 6b:13.35, 6b:27.40, 6b:30.10, 6b:32.25, 6b:34.55)  Slow down close to ZC but still cross it as Pd is there  (4b:13.55, 4b:17.15, 4b:20.20, 4b:24.45, 5a: 01.45, 5a: 05.30, 5a:10.55, 5b:05.00, 5b:05.35, 5b:10.45, 6a:18.40, 6b:0.55, 6b:01.05, 6b:31.30, 6b:33.55, 6b:40.50, 6c:03.45, 6c:10.15)  Speed up to get there before the Pd  (4a:42.25, 5a:45.40, 6b:49.20 )  When they do stop, it’s because  many Pds at ZC  (4a:29.00, 4a:39.30, 5a:39.30)  Vulnerable road user crossing at ZC  (5a:23.05)

Communicating with and reading each other  Seems that cyclists will calculate a Pds path as they cross the ZC and change their behaviour accordingly, so that they avoid the Pd and conserve energy/keep their flow going  (4b:17.15, 4b:23.25, 5a:16.05, 5b:05.00)  Cy will sometimes signal  (4b:20.00, 5a:40.30, 6b:29.25, 6b:29.50, 6b:47.05)  Even with no around  (4a:9.55, 6a:05.15, 6c:09.55)  A behaviour taken over from driving? A wish to create a communicative space?  Cy will sometimes look for communication channels  by looking at the Pd  (5a:00.40, 6b:11.05)  By gesturing physically  (5a:23.05, 6b:13.35, 6b:30.10)  Both Pds and Cy will sometimes communicate that they are giving way or to give thanks for the other giving way  (4a:24.00, 4a:8.30, 5a:23.05, 5a:28.30, 5a:28.35, 5a: 32.15, 5b:09.35, 6a:00.00,  , 6b:30.10)  Cy thanks to a car:  (6a:04.15)  Cy will also react to each other  Often slowing as they both come to the corner at the same time to ensure both have space  (4b:08.50, 5a:09.10, 5a: 42.25, 6a:00.45, 6a:10.15)

Lack of communication, leading to confusion  (4b:13.55, 5a:40.30, 5a: 42.25, 6b:01.05, 6b:06.00, 6b:15.45, 6b:26.20, 6b:27.40)  Usually seen in Cy not signalling when approaching the ZC or junction  (4a:22.15, 4a:37.10, 5a:40.30, 5a: 42.25, 6b:01.05, 6b:06.00, 6b:15.45)  Also in Cy avoiding Pd communication with Pd  (4b:09.50, 5a:10.55)

Appendix 11: Issues and recommendations

With the in-person observations

Several issues arose during the observations that I won’t go into in too much detail here, however I will give the following pieces of advice (from which you should be able to deduce what issues arose): always check your equipment before you go, never presume they will fit together if you haven’t checked before; always check the weather before you go; if it’s any season but summer, bring fingerless gloves; bring a variety of extra pens, some don’t like the cold; before choosing a location to film from its often good to check where the sun position is (suncalc.net was invaluable); if recording several different times at the same spot, remember exactly where you placed the camera; and if you can, bring a second observer and communicate with each other as much as possible. Oh, and bring extra batteries, just like pens they don’t like the cold.

With the observiaire

I would strongly recommend any future researcher who wishes to use an observiaire as a tool to check, double check and triple check the whole process - from beginning to end. This means all the way to the data processing and presentation stage. I did not do this fully and so issues arose at a late stage when changing things was complicated and costly (in terms of time).

Of special importance is recognising which variables you will be able to answer just one option, and which you can answer multiple and sticking consistently to this. This includes across segments. This will help you really understand what you’re trying to present when the time comes to it.

Connected to this is the importance of ensuring real consistency when answering. Without realising it I was changing the way that I filled in the sheet as I went along. The longer I watched the videos, I started to perceive happenings and behaviours in different ways. This was reflected in the ways I recorded them. It is important that these potential changes are caught before they start to affect the data. Due to the inconsistency in some sections, I had to go back into the videos and change how I had recorded certain happenings.

Finally, when you are filling out the observiaire having a second screen is invaluable.

Appendix 12: Observiaire amendments and removals

Inconsistency in my own data reporting led to me having to remove the following section, No Communication, from the Social Interaction group, including No consequence, Leads to confusion/pd hesitation, and Not applicable. It became apparent when trying to process the data, I had unintentionally changed how I was recording halfway through. I took the

78 judgement that this section was mostly unimportant to the final results and removed it. It helped that I was still able to find the figure for No communication - i.e. how many cyclists attempt no form of communication at all.

I also had to amend the Physical Reaction group and its sections. As it was possible for the same cyclist to have multiple answers within a section, there were complications when combining and calculating the totals and percentages. The same cyclists were being counted twice in two different sections. In order to simplify this I did the following:  Separated the No change in speed section into  One No change in speed and weaves section, where I moved the data of the times that a cyclist didn’t slow or speed up, in the presence of a pedestrian, but did weave around them - also recording whether the pedestrian or cyclist crossed first.  And one No reaction section where I moved the Straight through data and split it into cases where the cyclist crossed first and when the pedestrian crossed first. It was confusing having non reactions not in their own section.  Separated the Slows Down group into Yes, pedestrian crosses first to Yes, cyclist crosses first and No. I moved the data around accordingly, and created some new variables - such as adding Weaves around and Straight through to Yes, pedestrian crosses first. This did not mean I had to record any new data, just move round existing data into new sections.

Ultimately this reorganisation was done to make the data easier to understand and visualise. It took a fair amount of time, a few days, to work out what was wrong and where it should move to and how to do that. I would like to stress the importance of properly road testing your observiaire before going ahead with the full study.

TRITA -ABE-MBT-20764