Morris_off-campus_main study

Edinburgh, Scotland

Pedestrian Traffic Analysis Efficiency Planning alden morris . suny-esf . BLA off-campus . summer ‘17

Cause & Effect

Have you ever gotten annoyed walking down the street by others moving too slow, cutting in front, or taking up an unreasonable amount of space?

What, then, is your next move?

Lets look into how and why your habits may be annoying others and complicating traffic.

Because now you’re the one moving too slow, cutting in front, or taking up an unreasonable amount of space for someone else.

The foundation of this study rests on the idea of cause and effect. That patterns exist, and have a lasting impact on those after them.

What

_the basics

Location Topic Type

Time Thesis Advisor

Edinburgh, Scotland User Experience, Efficiency, Urban Planning Systems Analysis, Research 6.23.17 - 10.13.17 Dr. Doug Johnston

scotland

Edinburgh

_the city

Edinburgh is the capital of Scotland. It contains a unique UNESCO world heritage site due to it not being an individual site or monument, but rather a larger area containing two towns, the Old Town and New Town. The two sites are also distinct from each other both aesthetically and in their current uses. The Old Town is Edinburgh’s original medieval settlement which predates the 12th century, but was well established at that point. With expansion, the New Town was designed as a suburban residential district in a drastically different style featuring Georgian and Neo-Classical architecture to accommodate an increasing population and increased wealth.

Due to the perched castle and historic ‘atmosphere’ of the city center where the towns are, Edinburgh has become a tourist destination.

The city is capitalizing on this opportunity fostering a tourist economy around the most profitable and unique attractions. This is especially visible through an excessive density of retail tourist shops featuring Scottish products in the old town and tightly packed restaurants and bars in the new town.

Edinburgh has also become the world’s leading Festival city. This is a contemporary addition to the city that draws millions of visitors each year and helps sustain a year-round tourist economy. There has been a steady growth in the size, visitor count, and influence the twelve city-wide festivals have on Edinburgh relating to its economy and cultural identity.

Originally built as a small medieval town with many historically protected buildings and land, it will be hard to expand infrastructure to accommodate increasing tourist projections. It will be more viable and cost effective to increase the efficiency of current systems.

Impact On Me

_what really matters

My first memory of Edinburgh was of being dazed from poor sleep, stepping out of the bus station into the rain, and surrounded by construction fencing (St. James demolition). At the same time, humbled by historic architecture and receiving my first glimpse into what makes Edinburgh a unique place to be. This two-sided memory is a reflection of its overlap between old and new, what was and what is to come.

A city with an almost exponential rate of change and potential, decisions are being made quickly to adapt. But how do you adapt a city that was planned for a time when cars were not in existence and population was a fraction of what it is now. Remember to take into account historic preservation, monitored by UNESCO, and design with minimal impact. And of course, be able to compete in a global market.

The answer is simple. Improve efficiency to minimize need for more extensive reconstruction.

PROJECT EXPLANATION

Step 1

THESIS / REASONING

INTEREST THEORY

Objective / Background This study targets pedestrian efficiency.

One of the most important aspects of this cities infrastructure.

The objective of this study is to start to understand pedestrian traffic efficiency:

What are the cause and effects of pedestrian movement patterns through space during times of conflict?

Relationships between footfall density (the amount of people occupying a space) and street characteristics, will show patterns in pedestrian right of ways, tendencies, and conflicts.

Six pedestrian locations within the Old and New Town portions of Edinburgh will be studied.

Environmental influences will be identified through mapping. Human influences will be identified from apparent patterns and suggested causes within collected data. These together will start to form basic generalizations for guidelines of pedestrian environmental design.

Personal Tendencies Human Tendencies

Mapping Pedestrian Activity

Locational Influence

mapping spaces

Pedestrian Cause / Effect

Do You Agree?

_examples

Walking throughout a city can range from a pleasant to stressful experience.

Density of users and design are two major factors in this assessment. When the comfortable density for a given path is exceeded, then slower pace and stops in movement affect user experience.

Obstructions and poor planning can break up pedestrian paths and create choke points affecting user movement. Design factors include path width, obstacles, intersections, and joining paths.

Users influence each other by following, passing, and cutting one-another off.

Approach

_how to start the study

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Location choice should be done with purpose. They should provide insight

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Data recording needs to be quick, insightful and adaptable. A lot should be

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Display of information should be understandable to those with and without

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onto a new and specific aspect of influence. However, they should also be comparable to all other sites in a way that can reinforce or dispute findings. Most importantly, they should be interesting. A place that grabs your attention by human instinct, and not by technicalities. If good design was technical, then there would be no use for human input by now.

understood from the necessity of doing little. Adaptability is key, for all new and exciting projects are promised to change when the one and only thing the developer didn’t plan for ends up happening.

design backgrounds. Forgoing peer acceptance, and understanding the importance of interdisciplinary work, one never knows who may provide the most helpful input. There comes a time when one realizes that the best things come to those who don’t think they need to impress others.

Finally, the results should provide some sort of useful information. Whether it supports or destroys the thesis, it answers a question. Otherwise, it has all been wasted time. Make your time count, and don’t squander an opportunity.

high st. - site6

Methods

_site locations

This study tracks static locations with direction of travel. The study sites are various two-foot width portion of sidewalks perpendicular to their adjoining street. Locations were chosen based on different spatial layouts, parts of the city, included obstructions, or for more in-depth comparison of one site to another. They are all located within the Old and New Town portions of Edinburgh which are the main tourist destinations in the city. Below are the reasons each site was chosen:

Site 1 (Princess St. – North Side – 1)

This site cuts through a bus shelter which takes up roughly one third of one of the busiest pedestrian paths in the tourist portion of the city (New Town). It is closely situated to major bus and train hubs, further increasing volume and variables to the street.

Site 2 (Princess St. – South Side Gardens)

This site cuts through a bus shelter and is within fifty feet of the biggest train hubs in Edinburgh, Waverly Station. It is a through-way for people traveling, as well as individuals passing from the Old Town to New Town. It is also situated next to the Waverly Mall, Princess St. Gardens and various outside food and drink venues.

Site 3 (High St. – East – Lower)

This site is along High St. (The Royal Mile), which is another main tourist strip that connects the Edinburgh Castle in the west to the Palace of Holyroodhouse in the East. It was chosen because it is at a major pedestrian intersection. There is also an obstacle, trash bin, located in the middle of the sidewalk. The objective was to see how pedestrians interacted/moved through a space with a sizable obstruction in the middle of the path on a busy street. This is the only site where data from both sides of the street was collected.

Site 4 (Leith St.)

This site was chosen because it is along a major construction project currently underway in the city. It is also on the outskirts of the Old/New Town borders. It was chosen as it is a different type of site from the others, because all pedestrians are only able to walk on one side of the street due to construction.

Site 5 (Princess St. – North Side – 2)

This site was chosen because it is roughly twenty feet away from site one and has the same characteristics. It is meant to allow for direct comparison of two sites to see if general findings can be applied to sites with similar characteristics. It cuts through a bus shelter, is along main transportation routes, and is in the New Town.

Site 6 (High St. – West – Higher)

This site is along High St. (Royal Mile) and was chosen due to its lack of obstructions. There are no major intersections, transportation drop-offs, or businesses within the immediate area.

It is also one of widest areas along the Royal Mile, allowing more space for movement and dispersion. It was meant as a control for the Royal Mile.

eith

New Town

51 2 Old Town

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West End South Side Marchmont and Meadows

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1000’

Step 2

DATA COLLECTION

THEORY FIELD SKETCHES

Methods

_overview

Street footfall density (amount of people in a street) and pedestrian location (where people are walking along a street) were the two critical pieces of information necessary to answer my thesis.

To summarize all methods: Two recordings (eight minute-long counts per set) of footfall density (amount of people in a street) were completed. This provided a baseline (comparable) for comparing individual site information, as well as comparing sites to one another.

Then, 100 sketches of where people were located in a street (individual or groups) and which way they were walking were completed. This provided the necessary information to understand how individuals and groups of people follow one another, and how their direction of travel affects opposing pedestrians (those walking the other way).

As there was a lot of testing in the beginning to structure more accurate results, the first several rounds of data collection were not considered into the final count. This was to maintain a certain level of quality for comparison.

Methods

_footfall density

When looking down the street you can generalize how crowded it is, for example, with the terms ‘not really’ or ‘packed’. The goal was to find a way to more accurately represent your suggestions.

Knowing street footfall density allows the comparison of how people walk in a street when there are not many people present versus the opposite in one site. A controlled and accurate way to record this among different street layouts allows comparison in many sites. It additionally creates a more comprehensive catalog of footfall density throughout the full day with more accurate averages due to a higher data set (more results).

The main considerations for footfall density was accuracy of count and time of count. Accuracy of count was adjusted half-way through the study. This was first addressed by taking the average of ten consecutive sets (one-minute count, seven second rest, repeat) at the beginning of the site visit. It was later adjusted to averaging eight consecutive sets (same rep/rest), however recording at both the start and finish of the visit. This change was made to account for changes in peak density and momentary flooding in traffic. It additionally allowed for more overall footfall counts. Pedestrians were counted by numbers of five. This allowed for ease of counter recording and allowed for flexibility during momentary floods of people. While other numbers were tested in the beginning, counts of five was determined to be the most reliable. Everyone that passed in front of me perpendicular to the street that took up space in the street was counted. This included adults, children, pets and strollers. Luggage was not counted.

Methods

_collecting data

You may react a certain way when you realize how crowded a street may be, whether it is intentional or subconscious. This includes moving over to the side of the path, find another way, or just not caring what’s in front of you and staying the course. The goal was to record these reactions.

Knowing all of the reactions at a given location, over time, allows the opportunity to draw conclusions of how one reaction affects another.

When there are enough reactions over a given time period, conclusions can be drawn for long term impacts. The more reactions to crowding that are gathered, the more reliable information becomes as there is more data to average.

The main considerations for pedestrian traffic tracking was accuracy in relation to location, direction, recording tactics and ability to compare data. This was all formed around the ability to accurately and efficiently record data. An online service (jotform) was used to record sets of twentyfive drawings coupled with basic site information. This was the most convenient option as only one template would have to be created for all of the site visits, and all recordings were automatically organized and backup up on cloud servers. The number of drawings per set was limited to twenty-five drawings due to mobile loading and data limitations. If too many were used, the connection would time out during the time of upload and all data would be lost. In order to accurately compare individual site visits, 100 drawings were collected per visit. The timer was set to 100 intervals of two seconds of observation followed by seven seconds of recording. Two seconds of observation allowed for one wave, or row, of pedestrians to pass. Due to changing densities of footfall, seven seconds was tested as the optimal amount of time necessary to accurately write down observations and reset for the next observation for up to footfall density of 100 people per minute. A shorthand for drawing was created to quickly and accurately plot locations and direction.

Drawings

_key

The screenshot below is what data collection looks like in the field on a 5.7-inch diagonal screen. There are 25 of these fields in each survey and four are completed at each of six Sites during every observation. A stylus is used for increased accuracy.

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1 possible fields The spaces in between the lines represent all of the possible locations where data can be collected using shorthand symbols.

2 street guide Each site has its own survey as the street layouts and observation spaces change. This particular one is of site 3 at High St. Both sides of the sreet are observed and there is a trash receptacle present.

3 drawing area Any sort of markings can occur within this space. None of the top settings are used except for the undo button if a mistake is made. A stylus is used for accuracy as this is approximately three inches wide in the field.

right side of sidewalk

left side of sidewalk

high street sidewalk at street trash receptacle right side of sidewalk

left side of sidewalk

Phone screenshot of one data collection field from the High St. location. Approxmately three fit on the screen at any point.

range of icons

Everything is in relation to ‘up’ being the top of the screen and perpendicular to street at site.

single person favoring right side, walking left

single person favoring left side, walking left

single person favoring right side, walking right

single person favoring left side, walking left

two people, walking left

two people, walking right

whole space taken up

circle on left or right whole space taken up

any icon - middle of that field

any icon - on left or right makes marking clear

only on side of walks shows people standing

no action or movement people can be standing

Step 3

DATA MANAGEMENT

FIELD SKETCHES DIGITAL SPREADSHEET

Plotting Data Sketches completed in the field then needed to be digitally represented in a way that would allow for accurate interpretation. Accurate and quantitatively backed generalizations could be formed about how pedestrians moved through space.

A general template using squares to represent the number of pedestrians was created in order to create cohesive representation. One square or half square in larger sites represented one person. The number of squares per site was determined by a general three feet per person width. Thus, a foursquare lane, where one person equals one square, approximately represents a street 12 feet wide.

People walking next to each other or in groups would add the appropriate number of squares to still represent one person per square. If there were more people than squares, then the squares would be darkened to represent two people per square. There were never more people than squares under those guidelines.

Although the layout of sites change, the general format stays the same, allowing for possible comparison between sites.

All markings in blue represent movement to the left, while all markings in yellow represent movement to the right (map to orient reader provided with every site). As mentioned, darker shades of blue represent two people in that particular location as opposed to only one. This is only used for high density counts, when there are more people and crowding occurred. Grey markings represent no movement of people or objects in that space.

This framework (rules to digitally graph the sketches) creates a spreadsheet style graphic, an example of which can be seen to the right.

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--- spreadsheet-style digital raw data ---

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)- 4:30pm

Representing Time As mentioned in the data gathering section, each sketch is a recording of all that occurred along a two foot strip of space in front of the recorder. A recording of all that is happening along a section line through the sidewalk.

Thus, there are significant gaps in time between each sketch, making it important to represent drawings in a way that makes that fact clear.

To recap, each block of data (100 sketches) is split up into four sets (25 sketches). The four sets have a time difference of five minutes between each set, thus cannot be compared to one another in a continuous string. However, patterns in each set (25) can be grouped into the whole block of data (100) because density and general time period remain constant, which is one of the main grounds of comparison for the whole project.

Individual sketches within one set are only seven seconds apart, and for reasons that will be explained in later sections, can be compared. However, they must be displayed in a way that breaks up each sketch to show they are seven seconds apart.

Off of those guidelines, the representation of all data needs to have the entire time block on one page, split up into four sets of twenty five. All marked for the time they represent.

Time moves to the right and is 25 spaces wide for a total of 100 sketches per spread (two pages). This covers roughly 28 minutes of data collection in total per page. Each space (divided by white lines) is equivalent to seven second intervals of pedestrian presence.

Theory of Influence From a common sense standpoint, think about where in a sidewalk you generally walk when there is nobody else present in the street. It is most likely in the middle or off center towards the right.

When there are crowds of people, and someone pushing through in front of you, what will you do? Most likely to follow them as that is the path of least resistance. Or, break away into either far side of the street where there is the highest likelihood of going around everyone.

This has been the most complicated and difficult aspect of this study to understand and analyze.

Several problems exist with trying to compare my methods in terms of the thesis. To reiterate in summary, the thesis of this study is to understand how the actions of one person affect others in the future.

The most accurate way to answer this would be to record a video of the whole street, watch interactions, and then interview everyone involved for their reasoning and personalities. This, however, is a very time consuming and a logistically unreasonable process.

The direct complication with my methods is that each snapshot of data has a significant time difference, seven seconds, and that a minimal portion of street, two foot width, is taken into consideration.

This entire study rests on a single theory that backs my argument. That theory is that ones actions have a lasting impact on others both in front and behind them. Furthermore, that humans follow patterns that can create guidelines applicable to other locations.

Step 4 VISUALIZATION

DIGITAL SPREADSHEET GRAPHIC REPRESENTATION

Connecting Data While spreadsheet-style data allows for quick and accurate analysis, a more visually pleasing format shows patterns more easily.

Three pieces of information are important to convey: 1. The Amount of People

Up until now, in each sketch, the density of people is shown as blocks. Now, those block widths are maintained, however the ends are smoothed out to a curved point. This creates a pointed oval shape instead of a box.

2. The Direction of People

The direction that people are moving is kept the same as two different colors (blue moving left, and orange moving right).

3. Connection of Amount/Density From One Sketch to the Next

There are two levels of connections that will be represented in this stage. The first is how an individual sketch relates to the one immediately before or after it. The second is how all of the sketches in one set create a combined flow of traffic, regardless of breaks in time.

The relation of one sketch to those next to it will be accomplished by connecting one oval to the next.

Ovals will only be connected if they are the same direction (color), directly following one another, and not too far away in terms of sidewalk location (where they will otherwise become a separate path).

As previously mentioned, one of the most compelling arguments against this study is the gaps of time in between each sketch (recording of pedestrians). Thus, a way to infer what may be happening in between each sketch would be to link how sketches relate from one to the next. The relation of all sketches in one set will be accomplished by drawing a continuous line through all of the ovals connecting them one to another in their respective direction (one line in orange, one line in blue). If the ovals break off into more than one path, then the main line splits to accommodate as many new paths as there are. If enough time passes when there are no pedestrians present, then there is a minimal relation of sketches over an immediate pattern of time.

This implies that changes in traffic are gradual and follow patterns, and not sporadic.

While the amount and direction of people are easy to understand, the continuous connection of sketches (lines) starts to complicate the understanding of these graphics.

The continuous line will now be referred to as the ‘line of influence’. It is represented as the darker red and blue lines. They can either be solid or dashed, four different thicknesses, or a combination of both.

While there is a general framework for what constitutes the line style (how it looks) in most locations, they may slightly change due to the layout of the individual site.

The following are general technical rules, while site-specific rules can be found in their respected sections: • Lines can be solid or dashed, with line widths of .25, .5, 1, or 3pts • Lines are generated by connecting the midpoints of bubble sets using a curvature line tool. The curvature tool decides the curve strength and is only edited at points when the line exceeds the width of the entire path (not very often).

• Solid lines represent closer/stronger connections, while dashed lines represent weak connections with low pedestrian density recorded infrequently.

• At any point, a line becomes dashed if the closest data points for one color are farther than two spaces apart (14 seconds apart). Work in the past. Locations of where individuals were influences where people behind them will follow. Thus, lines up to two spaces away from bubbles only follow behind people and not in front of them. Blue lines (people traveling left) leave trails to the right, and orange lines (people moving right) leave trails to the left.

• Every site location is split into two sections: the main paths and the outskirts. The main path represents the widest section of the path, where a majority of pedestrian will walk under no stress. This is always the same for every site. Outskirts change depending on the site. They are generally any space that cannot comfortably fit two people (a four-foot minimum) and is usually twenty-four inches or less in width. If there is a bus shelter, then the space behind the bus shelter (approximately eighteen-twenty-four inches wide) is counted as the outskirts. The narrow portion on the other side of a trash receptacle (approximately 18x24 inches wide) and street can also be counted as the outskirts.

• At points of high density when bubble colors are darker, line width is increased to 3pts (lines seem thicker than usual). This is an alternative to coloring the bubbles a different color.

--- spreadsheet-style data with graphic overlay ---

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--- only graphic overlay (format to be used for analysis ---

Step 5

IDENTIFYING PATTERNS

GRAPHIC REPRESENTATION ANALYSIS

Starting Point

_analysis

At this point, all of the necessary information to start drawing conclusions is present. There are a few questions to answer in order to move forward:

1. What am I looking for in order to address the original thesis?

2. What are the characteristics for times of conflict, the area in which analysis will be focused?

3. What in these specific areas should be understood?

4. How can this new information of specific areas be used in a broader scope?

5. How does this all address the original thesis?

step 1 1. What am I looking for in order to address the original thesis?

Thesis: What are the causes and effects of pedestrian movement patterns through space during times of conflict?

Breaking down the thesis into parts to be addressed:

1. Cause and Effect

A conclusion of reasoning for different chains of events based off of presented data. This is accomplished through all levels of interpretation.

2. Pedestrian Movement

This applies to the individual and those immediately in front of and behind them. This is taken into consideration within areas determined to be times of conflict.

3. Patterns Through Space

This applies to an extended length of time. Patterns will be identified from before and after times of conflict.

4. Times of Conflict

This applies to irregular instances in patterns of pedestrian movement. The parameters for what is irregular needs to be specified. These are the areas in which analysis will be focused.

step 2 2. What are the characteristics for times of conflict, the area in which analysis will be focused?

Times of conflict need to be instances that disrupt an optimal flow (movement) of pedestrians.

Under optimal flow, pedestrians, regardless of location, don’t interfere with one another’s movement, opposing or not. They follow those in front of them, away from opposing traffic. They may pass those slower than them while still providing space for opposing traffic. This implies that traffic moving both directions has a side of the sidewalk that they tend to prefer.

Lets relate this to vehicular traffic and call it the ‘right of way’.

The sidewalk can thus be separated into two equal sides, each direction of traffic having their own space. The right of way for both directions can be determined by what side of the sidewalk they are statistically more prone to occupy (where they are located more in sketches). By the rules of scientific study, those can be averaged due to them being in consistent intervals and by definition random.

Thus, when pedestrians are located in an area outside of their right of way, this must be a time of irregularity and not optimal for overall traffic. However, if there is no opposing traffic, then optimized movement might indeed be spread out across the whole sidewalk moving one direction. Another parameter needs to be present in order to account for that aspect and focus results.

step 2 cont.

Times when opposing directions collide could imply a time when traffic patterns are not optimal.

Because there are gaps in time between sketches, the presence of pedestrians in those gaps are being inferred. Direct collisions or speed of pedestrians are not observed, however general patterns of direction and location are. Within the parameters of this study’s methods, a collision of opposing lines (a cross of opposing lines) of influence could infer a potential collision of traffic patterns and thus a lack of optimal traffic flow. Because lines of influence fade in relevance over time, when there is a cross of lines, that means that traffic has not had enough time to return to regular patterns while their location is still relevant. This becomes one and/or the other’s fault. Whose fault it is can be determined by what direction of traffic is outside of their right of way causing the chain of events.

All instances of overlapping lines will be displayed as black circles.

This accounts for analyzing when people are outside of their right of way, but as mentioned in the original argument, what happens when one pedestrian passes another. This will be considered a complication of traffic, as it breaks away from the main optimal traffic flow into a new path. This creates more options for those behind them, and thus more decisions to be made, creating higher potential for collisions. This is regardless of if they are in their right of way or not. While pedestrians passing one another were not recorded, locations of those seemingly not walking together were. They are characterized by a space in between a minimum of two people. They appear as separate entities and divide the line of influence. Every instance of split paths is considered an instance of people passing one another.

All durations of split paths will be outlined by a black box surrounding the sidewalk.

step 3 3. What in these specific areas should be understood?

All information will be displayed in one of three conditions. The parameters of all three conditions remains constant regardless of site and their only difference is the length of time they consider. This method of analysis provides various scales of data (types of information).

Top of each section:

1. Line Splits This occurs at every black box (where paths split). All pedestrian behavior within the black box is mentioned in a cause-and-effect manner, how one line reacts to the opposing over time. This includes pedestrian location at start/finish, line movements, and overlaps. Analysis takes form as a back-andforth color-coded timeline of all occurrences within the box with instances specified by numbers that are displayed along the black box.

2. Line Overlaps This occurs at every black circle (when lines overlap). The only piece of information present here is whose fault the overlap is. The side of traffic that was not originally in its right of way is the one that is at fault.

Bottom of each section:

3. Section Narrative This occurs at every instance of a line split. It is a less analytical narrative of what occurs before and after lines split, and how it relates to the line split. General observations in patterns are also mentioned here if an example of them is present in the instant. Those are colored black, while information pertaining to a particular traffic way is in its respective color.

step 4 4. How can this new information of specific areas be used in a broader scope?

Overview: Specific data from within a block (100-sketch set of time) is now present. The next step is to see what patterns may or may not exist within a block and furthermore a site over many blocks.

This will be discussed in the following section.

DATA

GRAPHICS KEY site number and time of data collection

1_Princess St._4:00PM

Footfall total_ p average_46ppm number of460 people

= density of 36 sec.footfall long people on a street

27 sec. long

cumulative site data 50% majority [80%] of 30% 9% 11%

35ppm

min_

p = people 63 sec. long ppm = people per minute

10% majority [65%] of 25% red is on their right 37% side towards road.

28%

blue is on their right side towards buildings.

80ppm

max_

pedestrian location statistics for both traffic directions

36 sec. long ONE set -Line 25 sketches red starts in opposite way, blue moves collision over. Red crosses into right of way [1], (4 sets per causedblock) blue crosses as well [1]. Red diverges, by red occupying opposite way.

then comes together [2]. Blue anomaly in opposite way. Line collisions from traffic moving back into right of ways.

Others anomalies.

complicated traffic patterns

3

weak potential traffic complications

22 path collisions 2

site conditions at time of data collection

dataset id

ID#_1-1-1

weak potential path collisions

27 sec. long both directions occupy length of time for their own right of ways.

Red splits paths conflict to occupy majority of sidewalk [1], blue pushes to side [1].

[2]

analytical timeline of events

[1]

PLAN VIEW

[1]

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Tuesday_7.11.17 weather_sunny temp._16°C

graphic representation of sketches [1]

[2]

[1]

red momentarily occupies opposite way, and blue moves over to accommodate. Blue returns to right of way afterwards, except for a fluke midway that may be an individual passing between two red split paths.

Red tends towards their right of way, occupying both side and middle.

red takes over a majortiy of sidewalk while there is no opposing traffic.

narrative / reasoning for specific pedestrian movement

Site 1 Princess St. This site cuts through a bus shelter which takes up roughly one-third of one of the busiest pedestrian paths in the tourist portion of the city (New Town). It is closely situated to major bus and train hubs, further increasing volume and variables to the street.

Edinburgh

A1

1 ite

ut

A2

p

e c rin

. t s ss

ion c

sect

S

section line of data collection

blue right of way

red right of way

A1

A2 plan view of pedestrian lanes clockwise rotate

section view of pedestrian lanes

+7 sec.

+7 sec.

+7 sec.

+7 sec.

+7 sec.

time advances to the right

princess St.

bus stop

sidewalk

buildings

A1

section cut A2

1_Princess St._4:00PM Footfall

460p

46ppm

total_

35ppm

average_

min_

Tuesday_7.11.17 weather_sunny temp._16°C

80ppm

max_

27 sec. long

36 sec. long

63 sec. long

blue occupy several lanes [1], no reaction.

blue starts to fan out taking up more of the street [1], red moves away from right of way. Opposing traffic takes over road [1], blue stays in right of way. Line collisions caused by blue diverging from main line and red traffic changing paths.

blue converges, reducing opposite way occupancy [1], red presence minimum. Blue group fans out across the sidewalk [2], red tends towards right of way. Minimum use by opposing traffic in the beginning [1], however takes over sidewalk in the end [2], blue presence minimum. Line collisions caused by left traffic splitting and right traffic tending to occupy same space. Right traffic should move over to their right of way.

[1]

[2]

[1]

PLAN VIEW

[1]

[1] individuals not walking side by side capitalize on low footfall density, taking the chance to pass one another or avoid following.

Minimum impact.

groups space out with no opposing traffic, then move over to right of way when oncoming density increases. Traffic changes course to opposite side, not following those behind them, then moves over to their right of way.

[1]

[2]

with a gap in location of pedestrians, this might be caused by people who don’t know each other walking side by side at different paces with one passing the other. Oncoming traffic is forced to move over to accommodate, however revert to occupying centered and spaced lanes once opposing density diminishes.

45 sec. long

81 sec. long

red in opposite way [1], blue shifts away from right of way [1]. Blue splits up [2], red group shifts into right of way [2]. Blue diminishes and moves back to right of way [3], red group now occupies majority from right of way. Line collisions caused by right side occupying away from their right of way, causing left traffic to move over. As right traffics shifts towards their right of way, they overlap paths with opposing traffic doing the same.

Red high density groups occupy majority of sidewalk from opposite way [1], low density blue occupies gaps on both sides of sidewalk [1]. Red moves over to right of way in split paths [2], blue moves into their right of way, away from red [2]. Line collisions caused by red group not occupying right of way. Individual blues scatter among opportunity gaps in groups of red. Their scatter of pattern causes overlaps.

[2]

[3]

[1]

[2]

PLAN VIEW

[1]

[1]

[2]

blue traffic starts on their right of way and then increases in size, taking up more of the road. Residual individuals follow paths before them, but without the same density, soon revert to occupying their right of way away from opposing traffic. Red starts away from their side, possibly due to seeing the large group coming towards them and wanting to move over. Their own density increases, possibly from a tour group or family, and they move into their right of way.

[1]

[2]

blue are scattered among red crowds, occupying what space they can among opposing traffic. Large groups tend to move over less as they hold the majority over smaller groups and individuals. As red density decreases, they split up among the confusion of blue not following one another. Red shifts over to their right of way as it is now easier to navigate in smaller numbers, allowing for blue to revert to their right of way as well.

50% 30% 9% 11%

majority [80%] of blue is on their right side towards buildings.

10% majority [65%] of 25% red is on their right side towards road.

37% 28%

8

complicated traffic patterns

3

weak potential traffic complications

22 path collisions 2

Line collision caused by red occupying opposite way.

weak potential path collisions

36 sec. long

27 sec. long

red starts in opposite way, blue moves over. Red crosses into right of way [1], blue crosses as well [1]. Red diverges, then comes together [2]. Blue anomaly in opposite way. Line collisions from traffic moving back into right of ways.

Others anomalies.

both directions occupy their own right of ways. Red splits paths to occupy majority of sidewalk [1], blue pushes to side [1].

[2]

[1]

PLAN VIEW

[1]

[1]

[2]

[1]

red momentarily occupies opposite way, and blue moves over to accommodate. Blue returns to right of way afterwards, except for a fluke midway that may be an individual passing between two red split paths.

Red tends towards their right of way, occupying both side and middle.

red takes over a majority of sidewalk while there is no opposing traffic.

72 sec. long Line collisions caused by blue occupying opposite way.

red starts in middle, blue in opposite way. Blue moves further away from right of way [1], red moves towards right of way [1].

Both cross into their right of ways. Both then consistent. Line collisions caused by both sides crossing back into their right of way.

PLAN VIEW

[1]

[1] majority of traffic is closer to the road, in red right of way, with a person standing on the other side. Red pushes blue out of their right of way and the two cross back into their own right of ways. Blue is the fluke in this situation, and red takes back their side shortly after momentary blue occupation.

ID#_1-1-1

Wednesday_7.12.17 weather_Sunny temp._17°C

1_Princess St._2:00PM Footfall

335p

total_

Line collision caused by blue occupying opposite way.

33.5ppm

15ppm

average_

Line collisions [4] caused by red occupying opposite way.

65ppm

min_

Line collision caused by both occupying opposite way.

max_

27 sec. long

9 sec. long

blue starts in far side of right of way, red starts in middle right of way. Red moves closer to blue right of way as blue numbers decrease [1], no change with blue [1].

blue starts in far side of right of way, red starts split in middle and far right of way. Red drifts into blue right of way [1], no change with blue [1]. Line collision caused by red moving into blue right of way.

[1]

PLAN VIEW

[1]

[1]

[1]

overall low density and consistent pedestrian locations provide no complications with slight location drift and splitting paths.

one side, blue, remains consistent in their right of way while the other, red, moves over, not following those before them. Following this, there is no blue traffic present in majority of path. Red’s behavior might be caused by individuals seeing minimal oncoming traffic, thus providing more choices to occupy lanes at their preference.

54 sec. long Line collisions [2] caused by red occupying opposite way.

blue starts in middle of right of way, red starts in far opposite way. Red crosses over blue into middle of their right of way [1], no change in blue location, however split in paths [1]. Blue converges to their far right of way [2], red moves back to opposite way [2].

Line collisions caused by red crossing into their right of way, and then crossing back.

[2]

PLAN VIEW

[1]

[1]

[2]

red is following past pedestrians before the path complication, however switches over into their right of way creating a new potential pattern. One pedestrian then breaks this pattern later on by walking in opposite way. Blue keeps a consistent path in their right of way. Red complicates path in this situation.

63% 22% 11% 3%

majority [85%] of blue is on their right side towards buildings.

17% majority [72%] 35% of red is in the middle of the road.

37% 11%

5

complicated traffic patterns

5

weak potential traffic complications

19

path collisions

6

weak potential path collisions

63 sec. long Line collision caused by blue occupying opposite way.

blue starts on both sides, red starts in middle. New red moves into far opposite way and creates two split paths [1], blue remains in right of way, but also splits into middle. [1]. Line collisions caused by red going into blue right of way.

PLAN VIEW

[1]

[1] trend is that both follow general right of way, but at this point split into each other’s side. Red instigates, which may have caused blue to do as well to create space for oncoming red.

Locations of both become sporadic following this incident.

27 sec. long both start in far right of ways. Blue splits into two groups occupying both sides, with a gap in the middle [1], red responds by moving slightly to middle [1]. Blue split diminishes and returns to right of way [2], minimum red present.

[2]

PLAN VIEW

[1]

[1] with minimum opposing traffic, blue spreads out to take over sidewalk. Split paths represent two pairs who may not know each other, thus a gap between them. There is only a slight deviation in path by red, which may or may not suggest influence of opposing traffic.

Line collisions [2] caused by red occupying opposite way.

ID#_1-1-2

Friday_7.14.17 weather_M. Cloudy temp._17°C

1_Princess St._5:00PM Footfall

310p

total_

39ppm

20ppm

average_

min_

50ppm

max_

9 sec. long

27 sec. long

blue starts in right of way, red starts in opposite way. minor split, no affect.

blue starts in right of way, red not present. Blue splits to occupy their right of way and far opposite way [1], red occupies opposite way [1]. Line collision caused by red being in opposite way.

PLAN VIEW

[1]

[1] prior to and after this incident, red groups occupy a majority of the sidewalk. Following this incident, low density blue individual locations are scattered throughout the sidewalk. As pedestrians tend to occupy the middle of sidewalks while moving, blue may be pushed off to the sides due to lack of density to compete with red.

63 sec. long blue starts in right of way, red starts in opposite way. Red moves into blue right of way [1], blue moves to middle [1]. Red occupies both far sides and then converge into middle [2], blue in middle [2]. Red in far opposite way [3], blue in same space [3]. All line collisions caused by red not being in right of way.

[2]

Line collision caused by red occupying opposite way.

54 sec. long blue starts in right of way, red starts in opposite way. Red fans out into both right of ways [1], blue occupies middle [1]. Red stays in opposite way [2], blue not present. Line collisions caused by red not being in right of way.

[3]

[1]

PLAN VIEW

[1]

individual standing on sidewalk at road decreases sidewalk space. In the beginning blue is spread out across the sidewalk as there is no red present. Red then tends to stay in blue right of way with no blue present. Later on, blue moves through the middle, hence why red may be staying towards the edge of the sidewalk.

[1]

[2]

[3]

prior and after this incident, red groups tended to stay in the middle of the sidewalk and out of their right of way. When a color has majority occupancy, they control how the sidewalk is used. The opposing traffic try to stay out of their way. Blue fits where they can, but tend to their right of way.

[1]

[2]

Red had, for the most part, occupied the opposite way prior to this incident. They started back into their right of way, however those were the minority and the main path remained the opposite way. Red is majority, with almost no blue present, thus could just be walking where it is easiest for them.

42% 35% 12% 11%

majority [77%] of blue is on their right side towards buildings.

26% majority [55%] 39% of red is in the middle of the road.

16% 19%

7

complicated traffic patterns

7

weak potential traffic complications

17

path collisions

9

weak potential path collisions

90 sec. long

Line collision caused by both occupying opposite way.

blue starts in right of way, red starts in opposite way. Red moves over to middle and splits [1], blue not present. Blue in right of way, then moves to middle [1], red moves to opposite way [2]. Blue in right of way [2], red split in middle and right of way [3]. All collisions caused by red being in opposite way.

[2]

PLAN VIEW

[1]

[1]

[2]

[3]

both not present prior to incident. Red may be occupying entire sidewalk due to low density of opposing traffic. Once blue traffic increases, red slowly shifts to right of way, however not immediately (some stragglers). Blue occupies right of way, however shifts into available locations when opposing traffic comes.

18 sec. long both start in middle, however red split on either side of middle. Blue in middle of path [1], red on either side [1]. Line collision caused by red in opposite way.

Line collision caused by both occupying opposite way.

54 sec. long blue starts in right of way, red starts in opposite way. Red splits within opposite way [1], blue stays in middle of right of way [1]. Line collisions caused by red being in opposite way.

[1]

PLAN VIEW

[1]

[1] blue tends to occupy middle of path forcing traffic to split on either sides. Before and after, both colors tend to occupy the same areas. They take over each other paths and generally do not stay in their own right of way.

ID#_1-1-3

[1] blue is minimally present in this area, however holds majority density before and after. Reason for red in opposite way not clear. They are neither being pushed to the side or have opposing traffic incoming.

Monday_7.17.17 weather_Sunny temp._18°C

1_Princess St._12:00PM Footfall

235p

29ppm

total_

average_

35ppm

min_

35ppm

max_

72 sec. long

63 sec. long

blue starts in middle, red starts in opposite way. Obstruction present next to building in far blue far right of way. Blue splits into two paths into both right of ways [1], red in middle towards right of way [1]. Blue shifts to middle [2], red moves into opposite way [2].

Blue splits into right of way and middle [3], red in opposite way [3].

Collision 1 and 4 caused by red being in opposite way. Collision 2 and 3 caused by blue being in opposite way.

blue starts in right of way, red starts in middle. Red moves into right of way and stays there. Blue splits in right of way and middle. No collisions.

[2]

[3]

PLAN VIEW

[1]

[1]

[2]

[3]

both sides had equivalent densities coming in. Blue density increases and they take over road. With obstruction in top and high blue density, red goes to middle. Color doesn’t want to occupy opposing traffics right of way if they have high density, and if obstruction present will stay to the middle. As blue density decreases, they shift into middle and red occupies opposite way. Blue still holds majority, thus controlling sidewalk. Red stays to side.

PLAN VIEW

Line collisions [2] caused by blue occupying opposite way.

red pushes blue off to the side in the beginning, however as blue density increases both ways stay in their right of ways. Blue path splits, however no complications.

Line collision caused by both occupying opposite way.

38% 38% 14% 10%

majority [76%] of blue is on their right side towards buildings.

15% 33% 20% 33%

majority [53%] of red is in the middle and left side of the sidewalk towards the road.

3

complicated traffic patterns

3

weak potential traffic complications

11

path collisions

2

weak potential path collisions

90 sec. long both sides start in right of ways. Blue path splits in right of way [1], no red reaction. Single red in opposite way [1], blue moves to middle [2]. Blue shifts back into right of way [3], red starts shifting to opposite way [2].

Collisions caused by red being in opposite way.

[2]

[3]

PLAN VIEW

[1]

[1]

[2]

both sides in right of ways coming in, and keep pattern until one red fluke in far opposite way. Red path shifts into opposite way following that incident. Blue stays in right of way amidst red traffic actions.

PLAN VIEW

Line collision caused by red occupying opposite way.

ID#_1-1-4

Step 5a METHODS REVISION

UNCLEAR DATA NEW APPROACH

Regrouping The first round of representation, version1, led to an unclear and highly qualitative work-flow of how data would be interpreted. The heavy use of text explanation did not provide a consistent way of interpreting datasets against each other.

A new approach using a centralized diagram-based database was created. As opposed to text analysis, which can provide a wide range of interpretations, these 78 diagrams represent every possible flow of traffic. They are furthermore grouped into different categories from 3 (in right of way, in middle, in opposite way) up to the individual 78 in which data can be broken down into once applied to the gathered datasets.

As shown in the visual on the adjacent sheet, the data from each side of the sidewalk is now separate providing easier comparison. Every point also aligns to an exact 7 second mark allowing precise comparisons. This exact alignment is why it may seem as if there is if some diagrams do not precisely align with what their action represents.

Situations in which one way walks outside of it’s right-ofway are still highlighted (bars encompassing more than one box) and are still the focus of analysis.

1_Princess St._4:00PM

ID#_1-1-1

Step 6 ANALYSIS

GRAPHIC REPRESENTATION UNDERSTANDING DATA

Comparisons Any situation in which one way of pedestrian trafffic crosses over into the opposing side is now crossexamined against each other. This includes two steps before and after (14 seconds) the occurance to determine how the crossover situation might have been started and its lasting impact.

A horizontal tree network diagram is constructed to align movement and points at which paths split.

This leads to a cummulative visual of all of the pedestrian tendencies and patterns that may or may not exist.

While the new methods are a much improved and efficient system, it has greatly slowed the completion of this project due to the amount of time that was spent on the previous method. This document will become the first of two documents of this project. Part two will include cummulative analysis and its application to another location.

The final portion of this draft includes the raw data yet to be analyzed from sites 2-6.

While it is hard to comprehend the data, it provides a glance at how pedestrian traffic behaves in different street layouts.

It will be completed for a final deliverable to be submitted as an honors thesis.

part 2 raw data site2-6

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END