Traversing the Labyrinth: A Comprehensive Analysis of Pedestrian Traffic in Venice

An Interactive Qualifying Project report proposal submitted to the faculty of WORCESTER POLYTECHNIC INSTITUTE

in partial fulfillment of the requirements for the Degree of Bachelor of Science.

Submitted on October 14, 2011 by: Chelsea Fogarty Geordie Folinas

Steven Greco Cassandra Stacy

Project Advisors: Professor Fabio Carrera, Ph.D. Professor Frederick Bianchi, D.A. Project Information: ve11-mobi@wpi.edu https://sites.google.com/site/ve11mobi/

Sponsors: Venice Project Center

Venice Department of Mobility

In Collaboration With: Santa Fe Complex

Redfish Group

1

AuthorshipThis Interactive Qualifying Project was completed with contributions from each team member.

2

TableofContentsAuthorship .......................................................................................................................................................... 1 

Table of Contents .............................................................................................................................................. 2 

List of Figures ..................................................................................................................................................... 5 

List of Tables ...................................................................................................................................................... 6 

Introduction ........................................................................................................................................................ 7 

Background ....................................................................................................................................................... 10 

2.1 The Architectural Framework of Venice ........................................................................................... 10 

2.1.1 Origins of the City ......................................................................................................................... 10 

2.1.2 Design of the City .......................................................................................................................... 11 

2.1.3 The Canals ....................................................................................................................................... 11 

2.1.4 The Streets ...................................................................................................................................... 12 

2.2 Tourism in Venice ................................................................................................................................. 12 

2.3 Mobility in Venice ................................................................................................................................. 14 

2.3.1 Watercraft in Venice ...................................................................................................................... 14 

2.3.2 Nautical Congestion ...................................................................................................................... 15 

2.3.3 Pedestrian Mobility ........................................................................................................................ 16 

2.3.4 Venetian Bridges ............................................................................................................................ 16 

2.4 Environmental Impacts on Mobility .................................................................................................. 17 

2.5 Venetian Traffic Models ....................................................................................................................... 18 

2.5.1 Past Models ..................................................................................................................................... 18 

2.5.2 Modeling Tools .............................................................................................................................. 19 

Methodology ..................................................................................................................................................... 21 

3.1 Quantifying Pedestrian Agents ............................................................................................................ 22 

3.1.1 Focus Area and Key Counting Locations .................................................................................. 22 

3

3.1.2 Assigning Agent Types and Identifying Each Type’s Characteristics .................................... 22 

3.1.3 Counting Tools and Devices ........................................................................................................ 23 

3.1.4 Time Brackets for Performing Field Counts ............................................................................. 24 

3.1.5 Counting Methods at Key Locations .......................................................................................... 25 

3.2 Determining Video Surveillance Feasibility ....................................................................................... 25 

3.2.1 Video Verification Methods ......................................................................................................... 25 

3.2.2 Verification Analysis ...................................................................................................................... 26 

3.3 Analyzing and Visualizing Collected Data ......................................................................................... 26 

3.3.1 Formatting ....................................................................................................................................... 26 

3.3.2 Field Forms ..................................................................................................................................... 27 

3.3.3 Pedestrian Modeling Techniques ................................................................................................. 27 

3.3.4 Census Tracts .................................................................................................................................. 28 

3.4 Publicizing Data ..................................................................................................................................... 28 

3.4.1 Venipedia ......................................................................................................................................... 28 

3.4.2 Deliverables ..................................................................................................................................... 28 

3.4.3 Furthering Models .......................................................................................................................... 29 

Bibliography ...................................................................................................................................................... 30 

Appendices ........................................................................................................................................................ 32 

Appendix 1: Pedestrian Agent Types Flow Chart .................................................................................. 32 

Appendix 2: Census Data Graphic ........................................................................................................... 33 

Appendix 3: GIS Cloud Map Layers ......................................................................................................... 33 

3.1 Hotels Layer ....................................................................................................................................... 33 

3.2 Schools Layer ..................................................................................................................................... 34 

3.3 Museums Layer .................................................................................................................................. 34 

3.4 Churches Layer .................................................................................................................................. 35 

3.5 Tourist Sites Layer............................................................................................................................. 36 

4

Appendix 4: Database Form ...................................................................................................................... 37 

Appendix 5: Field Forms ............................................................................................................................ 38 

5.1 Venetian Field Form ......................................................................................................................... 38 

5.2 Tourist Field Form ............................................................................................................................ 38 

Appendix 6: Establishment Data Form ................................................................................................... 40 

Appendix 7: B Term Schedule ................................................................................................................... 41 

Appendix 8: Budget ..................................................................................................................................... 43 

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ListofFiguresFigure 18: Area of Study Map ........................................................................................................................ 21 

Figure 19 - Mechanical Counter .................................................................................................................... 23 

Figure 24: Flow Cart of Pedestrian Agent Types ........................................................................................ 32 

Figure 25: Hotel Locations in San Marco .................................................................................................... 33 

Figure 26: School Locations in Venice ......................................................................................................... 34 

Figure 27: Museum Locations in Venice ...................................................................................................... 34 

Figure 28: Church Locations in Venice ........................................................................................................ 35 

Figure 29: Church Locations in San Marco ................................................................................................. 35 

Figure 30: Major Tourist Sites in Venice ...................................................................................................... 36 

Figure 31: Mobility October Schedule .......................................................................................................... 41 

Figure 32: Mobility November Schedule ...................................................................................................... 41 

Figure 33: Mobility December Schedule ...................................................................................................... 42 

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ListofTablesTable 1: Pedestrian Agent Type Characteristics .......................................................................................... 22 

Table 2: Time Brackets for Manual Counts ................................................................................................. 24 

Table 3: On Site Manual Pedestrian Counting Template .......................................................................... 27 

Table 4: Video Surveillance Data Collection Template .............................................................................. 27 

Table 5: Venetian Resident Density by Age and District (From 2001 Census Data) ............................ 33 

Table 6: Venetian Field Form for Manual Counts ...................................................................................... 38 

Table 7: Tourist Field Form for Manual Counts ......................................................................................... 38 

Table 8: Form for Institution Information .................................................................................................. 40 

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IntroductionCities worldwide adopt a bad reputation for their mobility issues. Many travelers avoid city traffic to

save time on their trip. Those who cannot avoid traveling through cities must plan ahead

accordingly. Mobility is the freedom to move about, and when mobility is impeded, people are

forced to interrupt their routes and pace and accommodate for their lost time. Battling traffic wastes

pedestrian time, and municipal authorities spend millions of dollars on regulating traffic with

approaches such as police control, road construction, and regulation laws. In the 90 largest urban

cities in America, 41 hours were spent per traveler in traffic in the year 20071.This could be the result

of overwhelming traffic density, traffic accidents, and other various obstacles.

In an attempt to better increase mobility, urban districts adopted public transit systems in the form

of buses, underground subways, trams, trains, and even boats. These systems can transport large

amounts of travelers and ease the congestion that results from high usage of private transportation.

Other key traffic management tools include stoplights at busy intersections, speed limits to prevent

hindrances from accidents, and separate lanes for directional management. For example, in Vienna,

Austria, designated lanes are utilized to safely integrate bike and pedestrian traffic on sidewalks2. By

creating structuralized means for transportation, cities are able to increase mobility and moderate

congestion.

The framework of canals and narrow streets that makes up the city of Venice has prevented the

invasion of automobile traffic, but has consequently made water transport and travel on foot the

two main modes of transportation, thus creating a need for similar traffic congestion solutions that

apply more to Venice’s more unique situation. Built on a lagoon, properly titled Laguna Veneta,

Venice is made up of 117 small islands with 150 canals and 409 bridges across the Canal Grande, the

main channel through Venice3. The branch canals range from 10 to 30 feet in width, and the

intricate network of streets are mainly made up of mere lanes of no more than seven feet wide; the

widest don’t exceed twenty feet4. It is with such a limited infrastructure, unique from any other city

in the world, which makes congestion in Venice even more problematic. The city has a dire need for

regulation applications that will alleviate the strain that traffic brings to the city.

1(Traffic Congestion Factoids 2009) 2(Lopez 2006) 3(Centre 2010) 4(Morgan 1782)

8

One of the greatest reasons that traffic is such an issue in Venice is tourism. However, since the end

of the 18th century, the Venetian economy has heavily relied on tourism, and it is a necessary burden

on the city. With a native population of approximately 61 thousand people5, the amount of tourists

flowing through the city on any given day outnumbers the locals in up to a 5:2 ratio6. While the city’s

economy is very firmly bound to tourism and its related industries, these visitors have contributed to

many problems for Venice and its inhabitants. The infrastructure is believed to be in danger of

giving way to the mass amounts of traffic. Some streets and canals are more readily accessible than

others at different times of the day, and mobility becomes increasingly hindered by people with baby

carriages and handicapped people in wheel chairs.

The issue of mobility in Venice is one that has been addressed by the Venetian government in a few

different ways. The Azienda del Consorzio Trasporti Veneziano, or ACTV, is a public water–bus

transit system that facilitates the flow of water traffic by centralizing water travel through 20 routes

on the canals. There are also multiple surveillance systems in place, including the Automatic and

Remote Grand Canal Observation System (ARGOS), Hydra, and Security and Facility Expertise

(SaFE). These observational systems are used to implement speed limit laws, and monitor

pedestrians and boats for crime. Our sponsors have developed these systems and implement them

daily in Venice. ARGOS gives the vigili urbani (the Venetian police) the opportunity to routinely

dispatch officers to control traffic and make arrests on the Grand Canal, and Hydra and SaFE allow

authorities to monitor the Venetian ports for potential crime7. In addition to the observational

systems, our sponsors have developed a model for displaying boat traffic in the canals using data

gathered from ARGOS and Hydra. Called the Venice Table, the model is an interactive program

that displays the movements of boats through certain checkpoints on the canal.

The sponsors of this project have completed a sufficient amount of research, and the systems are

being run in an effective manner. There are some holes in the data and execution, however, and

limitations to the observational systems. Individuals in Venice run all of the systems, so there is no

automated system to collect and archive data, costing many man-hours. This also has great potential

to lead to human observational error. The data collection methods should also be fully automated to

ensure that data is continuously being collected. The data is currently being collected manually, in

5(Italy n.d.) 6(Amilcar, et al. 2009) 7(Bloisi, et al. 2009)

9

intervals of minutes at a time, and only in the tourist off-season. The scattered datasets create

difficulty in presenting the data in the modeling systems. Having counts taken only once a year by

the WPI Venice Interactive Qualifying Project groups or the Venetian Center of Mobility does not

take into account how peak tourist times, weather, seasons, events, times of the day, and other

aspects affect pedestrian counts. An efficient, comprehensive model would be one that contains

sufficient amount of data from year-round. Other significant improvements that need to be made

are in the agent identification feature. Agent identification would consist of recognizing the

difference between a Venetian and a tourist. It is important to study the difference in agents because

each different type has its own behavior and will go to different points of attraction, and each one

will have its own mobility stream. While a tourist may drift to a museum or a shopping center, a

Venetian will want to go to straight to and from work or home.

This gap in data collection is where the Venice 2011 Mobility team comes into play. There is

virtually no data or research present on Venice pedestrian traffic. This has provided Team Mobility

with the unique opportunity to pioneer data acquisition into pedestrian mobility streams. We will

collect pedestrian traffic data in Venice with a distinction between agent types, namely Venetians

and tourists. Using this data we will verify the accuracy of any past and future models. Through

analytical processes we will then be able to make suggestions for future autonomous continuous data

collection that can feed into an eventual integrated pedestrian model.

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BackgroundVenice is composed of canals and narrow streets, which makes it a one-of-a-kind city to travel

through. Though the historic city occupies merely three square miles of land, traveling quickly and

efficiently can be a challenge due to a web-work of walkways, overcrowding, areas and events that

attract tourists, an inconvenient water bus schedule, and severe weather conditions. For the

uninformed, moving through Venice can be an unnecessary crusade.2.1 THE ARCHITECTURAL FRAMEWORK OF VENICE

In order to understand the significance of using agent-based modeling of mobility in Venice, it is

important to study its infrastructure and its origins, and how its status as a major tourist attraction

came to be. The city was not meant to hold as many people as it sometimes does. Because of

Venice’s physical limitations, it has a difficult time accommodating for the congestion issues that

result from overpopulation.

2.1.1 Origins of the City

Venice is a city frozen in time. Its peculiar situation and magnificent architecture render it unique

and peerless even in its decadence. How a city can be afloat in the sea and still be habitable and

beautiful is marvelous. Interestingly enough, Venice originated in an “expedient of desperation” and

became great by “accident of position8.”

The city began as a collection of inhospitable islands in the Venetian lagoon, along the western shore

of the Adriatic Sea. The invasions of the Lombards into northern Italy in AD 568 drove many

mainland Italians onto a group of islands of the lagoon, which were originally the homes of traveling

fisherman and salt workers9. Because the canals and rivers were not easy to navigate and the lands

were unwelcoming, the islands provided excellent protection against possible naval attack. The

influx of population resulted in a profound change in social composition in the lagoon as

settlements took form, and many noble family factions began to campaign for rule. After decades of

political strife among various settlements vying for supremacy, the islands were placed under the

authority of the Italian king Pippin in order to free the islands from Byzantine control10.

8(Morgan 1782) 9(Cessi, Cosgrove and Foot, Italy 2011) 10(Cessi, Cosgrove and Foot, Italy 2011)

Comment [C1]: Opinion

11

As this power struggle was taking place, trade was rapidly developing and increased private wealth

led to gradual internal stability. By the late 9th century, the group of Rialto islands was officially

transformed into civitas Venetiarum, the city of Venice11.

2.1.2 Design of the City

What once was a group of islands with wooden houses resting on poles staked into unstable clay soil

gradually morphed into an elegant and romantic city. The buildings had to be strategically placed,

taking into account the special environmental conditions of Venice. Weight had to be properly

distributed so that there were never too many areas of stress12. Because the city could not expand

outward, it expanded up. It was also less expensive to build another floor than to buy more land.

Buildings were built close together, and very tall. The ground floor usually housed businesses, while

the upper floors provided homes for families.

As the city grew and its economy became prosperous, the structures reflected the transformation.

The principal buildings in Venice were constructed of marble or light stone, and the remaining were

of brick covered with mastic for adhesion13. The architecture and design possesses characteristics of

permanence and timelessness that is unsurpassable.

2.1.3 The Canals

The employment of a network of canals in place of streets was more a matter of necessity than of

choice. The current canals undeniably circumscribe the original islands, as well as suggest their

position, the rest of the water area having been recovered by erecting walls composed of granite

along the line of these canals, which laid the foundation for the buildings14.

The branch canals off of the Grand Canal are some fifteen feet wide, and are often crooked and

short in length. The Grand Canal is one of the major water transportation corridors in the city; it

stretches down the center of the city in a backwards S-shaped course and is approximately 2 miles in

length, 30 to 70 meters wide15. The sides are lined with palaces and buildings reflecting the Gothic,

Romanesque, and Renaissance grandeur from its early development.

11(Cessi, Cosgrove and Foot, Italy 2011) 12(How Were Houses in Ancient Venice Designed and Why? n.d.) 13(How Were Houses in Ancient Venice Designed and Why? n.d.) 14(Morgan 1782) 15(Cessi, Cosgrove and Foot, Italy 2011)

Comment [C2]: Opinion

Comment [C3]: Opinion

Comment [C4]: Maybe make into a couple different sentences? It’s difficult to understand.

12

2.1.4 The Streets

There are 2,194 streets, each one as unique as its canals, which make up the labyrinth that is the city

of Venice16. They too are narrow, short, and crooked, and they penetrate every part of the city. Most

of them are just passages about seven feet wide, with the widest of streets not more than twenty-five

feet17. Some terminate abruptly and turn at sharp angles. Every street is covered with pavement, and

on each side are gutter stones to pass surface water or rain into conduits underneath18. While the

picture of these streets sounds uninviting, the close proximity is relieved by the numerous squares

that intersect them. There are 294 squares scattered throughout the city19. The streets cross the

canals by means of 409 bridges, consisting of a single arch, with a roadway graded into low steps,

connecting every bit of land in Venice20.

2.2 TOURISM IN VENICE

The Queen of the Adriatic has been attracting foreigners for centuries, and according to Riganti and

Nijkamp, the city can be considered a mature tourist destination, for it is one that witnesses negative

environmental impacts caused by tourist congestion more frequently than other destinations21. The

magnitude of tourists that visit Venice has a huge negative impact on the city. The resulting

congestion causes mobility impairments throughout the city, and especially at top tourist locations

and during peak tourist times.

The concentration of tourists is a problem that Venetians have been attempting to alleviate for a

very long time. There are a number of specific locations throughout the city that are typically visited

by tourists, which creates congestion both en route to the destination and at the attraction itself.

The Piazza San Marco, or St. Mark’s square, is a popular tourist stop, where one can visit St. Mark’s

Basilica and bell tower. Another is the Ponte di Rialto (Rialto Bridge), a large bridge connecting one

side of the Grand Canal to the other with shops along it. These destinations, as well as many other

spots in Venice, are the cause of the large amount of pedestrian traffic that regularly occurs.

Beyond the draw of the city itself, there many events held in Venice that attract a high number of

tourists annually. The Carnevale di Venezia, or Carnival of Venice, takes place in February every year,

16(Morgan 1782) 17(Morgan 1782) 18(Morgan 1782) 19(Morgan 1782) 20(Morgan 1782) 21 (Riganti and Nijkamp 2008)

13

and marks the beginning of Lent. A huge amount of tourists travels to Venice to witness the

Venetian beauty and culture displayed throughout the Carnevale and to attend the various events held

during it, such as La Biennale (a contemporary art festival highlighting architecture, independent

films, and paintings, among other things) and the Vogalonga (a boat race through the Venetian

lagoon)22. Events such as the Carnevale lead to an extremely high tourist volume, which in turn

causes mobility impediments for pedestrians attempting to travel from one place to another in an

efficient manner.

The sheer magnitude of visitors to the city creates issues within the infrastructure and community.

Traveling around world was once reserved for only the rich or influential, but it is now a viable

experience for a majority of people. This evolution towards “mass tourism” is one that is clearly

seen in Venice, where there has been a significant influx of tourists over the years23. The carrying

capacity of Venice, or “the maximum number of visitors the attraction can handle at a given time

without either damaging its physical structure or reducing the quality of the visitors’ experience” has

been determined to be approximately 30,000 tourists per day24. This capacity is regularly surpassed,

and that leads to the ultimate issue of Venetian traffic congestion.

It is said that Venice is becoming a European Disneyworld, or a museum city, where the tourists

outnumber the natives: “[w]ith its thirteen million or more annual visitors and a local population of

only around sixty-five thousand, historic Venice has the highest ratio of tourists to locals of any city

in the world.”25 This overcrowding effect impairs and changes many aspects of life in Venice, not

the least of which is commuting to and from work or attempting to traverse the city for another

purpose.

All of the factors described above: popular tourist spots, large events, and the city itself, cause an

increase in tourists visiting Venice every year. The mobility impairment created by this group of

people is severe, and must be addressed. The inability to traverse across the city lengthens work

commutes for the employed and school commutes for students, which can create tardiness and

ultimately impact an individual’s success in the future.

22(Carnevale di Venezia 2012 2009) 23(Zanini, Lando and Bellio 2008) 24(Van der Borg, Tourism and Urban Development: The Case of Venice, Italy 1992) 25(Davis and Marvin 2004)

Comment [C5]: Change wording or cite

Comment [C6]: Don’t need to make it personal

14

2.3 MOBILITY IN VENICE

Due to its unique location, the city required extensive draining and dredging to provide more land to

further the development of Venetian infrastructure. These operations led to the development of the

first canals, and a rather unique system for the city’s mobility26. Transportation in the city exists in

three main entities: the canals, bridges across them, and an arrangement of walkways. This network

of more than 200 canals became a staple for the transport of goods throughout the city as well an

excellent form of transportation.

2.3.1 Watercraft in Venice

Transportation and distribution of goods via the canal network would be impossible without the use

of watercraft. Throughout history, all major cargo shipments and heavy transport is done by boat.

For example, gondolas are iconic boats of Venice which were once used by the wealthy for

transportation27. These boats are keel-less and used almost exclusively for tourism in this day and

age28. Gondolas became far less popular with the development of steam powered vessels, called

vaporetti, in 1881. These vessels are still the dominant form of nautical transportation in the city.

Venetian ferries, called traghetti, also are a more popular form of transportation in Venice, and there

are now seven of these ferry crossings across the Grand Canal29. These ferries, which are much like

gondolas by design, operate at certain points between bridges on the Grand Canal and shuttle

pedestrians across for just 50 cents30.

Larger boats are used in Venice for cargo shipments, as well as for sea trade throughout the

Mediterranean. Due to this demand for large ships, and a lacking of local resources, many Venetians

became expert shipbuilders31. During the Medieval Era, Venice became one of the mightiest cities

because of this drive for mercantilism. Venice was a major port along many trade routes which

connected Europe to other continents such as Asia through the use of the Mediterranean Sea32.

Venice also had a very well equipped navy, which had the ability to build one war galley per day33.

26 (Howard and Quill 2002) 27 (Cessi and Foot, Venice 2011) 28 (Cessi and Foot, Venice 2011) 29 (Drake 2008) 30 (Drake 2008) 31 (Davis and Marvin 2004) 32 (Davis and Marvin 2004) 33 (Davis and Marvin 2004)

Comment [C7]: Put this before tourism because mobility is talked about in that section, but not introduced

Comment [C8]: Take out gondolas – only talk about traghetti and other public transportation

Comment [C9]: History first? Before the types of boats?

15

These galleys were handcrafted in shipyards called squeri where all types of traditional boats were

crafted, including traghetti.

2.3.2 Nautical Congestion

Private boats are less common in Venice than watercraft used for shipping cargo and public

transportation. This is largely due to the existence of taxi boats and a lack of space for extended

docking. Taxis in Venice are multipurpose boats which not only transport clients to their desired

destination but will also serve as a means of transportation for goods when not serving pedestrians.

There are also other vessels which have scheduled routes throughout the city which can be used to

move people between specified stops.

These forms of public transportation are one of the leading causes of boat traffic in Venice. Both

taxis and gondolas have random travel routes, depending on their clients’ demands, and therefore

become difficult to obtain data on. For example, gondolas typically serve as sightseeing vessels for

tourists and will typically slow down and make stops near points of interest34. These stops can cause

a large amount of traffic and adversely affect mobility. The traffic patterns of taxis and gondolas are

difficult to predict and their destinations are random, therefore their traffic patterns do not

significantly influence overall mobility in Venice.

Traghetti, due the fixed locations of boarding and unloading, are a relatively predictable form of

public transport via water. Previously, these boats were used as transportation between the islands of

the Venetian Lagoon, but with the development of motorized watercraft traghetti exist now

exclusively for crossing the Grand Canal. With only two bridges serving as a means of crossing the

Grand Canal and enter or exit the San Marco district, traghetti serve a vital role in assisting pedestrian

mobility in this area.

Cargo boats, on the other hand, have routes that generally do not change and are predictable.

Shipments of goods cause about 36 percent of all boat traffic in Venice35. Many of these shipments

occur in the morning; this is because the purpose of most of the shipments is to restock supply and

food stores36. In recent years, Interdisciplinary Qualifying Projects have been done by teams of

Worcester Polytechnic Institute students analyzing and suggesting modifications to cargo shipment

34 (Chiu, Jagannath and Nodine 2002) 35 (Fiorin and Miani 1995) 36 (Fiorin and Miani 1995)

Comment [C10]: Take out. If there’s information that is pertinent to the project, put it in a different section

16

methods in order to decrease congestion37. Originally the cargo was shipped and grouped by type of

goods, and required multiple boats to travel to the same locations. These teams proposed

modifications which would make cargo shipments through the city cause less congestion. The

proposal included having all cargo boats first report to a warehouse near the mainland, reorganize

and coordinate the cargo based on destination, rather than by item38. This proposal proved to be

successful, and resulted in a reduction of about 90 percent of cargo related traffic39.

2.3.3 Pedestrian Mobility

The other prominent form of transportation in the City of Venice utilizes an array of walkways and

bridges. The problems associated with these walkways are derived from how the city was

constructed, which led to limited space, and an increasing number of tourists which visit the city. As

the city was being constructed, walkways were built to facilitate trade and commerce in the city. Due

to the significant space constrictions associated with construction on an archipelago, many buildings

were constructed to the edge of the property, leaving little space for these additional walkways. This

fact has left many of the walkways narrow, some spanning only about a meter across40.

The stark narrowness of the walkways contributes to much of the pedestrian related traffic which

occurs in the city, but it is not the only factor involved. The layout of the walkways has been

compared to that of a labyrinth as a result of many canals being paved over to broaden the network

of walkways and alleviate traffic demands41. Pedestrian traffic demands have been growing

perpetually since the1950’s due to the overwhelming influx of tourists42. The combination of a large

population of tourists new to the area and a confusing layout intensifies the effects of pedestrian

congestion.

2.3.4 Venetian Bridges

The different islands of the archipelago are interconnected by an array of over four hundred

bridges43. These bridges are crucial to the infrastructure of Venice, and have become recognizable as

37 (Duffy 2001) 38 (Duffy 2001) 39 (C. Catanese, et al. 2008) 40 (Davis and Marvin 2004) 41 (Davis and Marvin 2004) 42 (Van der Borg and Russo, Towards Sustainable Tourism in Venice 2001) 43 (Davis and Marvin 2004)

17

indispensable monuments of the city which are utilized on a daily basis44. Four of the most well-

known bridges traverse the Grand Canal, the most notable of which is the Ponte di Rialto.

The Ponte di Rialto was constructed in 1588, but initially had two predecessors. In 1175 a bridge was

constructed using boats for floatation to span the canal, called a pontoon bridge, in the same

location as the Ponte di Rialto45. This bridge was ultimately replaced in 1265 by a fixed bridge which

later collapsed46. The Ponte di Rialto remained the only location to cross the Grand Canal until 185447.

Today, pedestrians can cross the Grand Canal by using one of the four bridges which now exist, in

addition to the seven different traghetti locations.

2.4 ENVIRONMENTAL IMPACTS ON MOBILITY

Venice’s unique structure, while a wonderful sight, is also slowly degrading. The city’s environment

is “… suffering from a general hydrogeological imbalance which is dramatically evident in the

erosion of the lagoon morphology and in the number of exceptional high water events” in Venice48.

This has been a problem for many years, and the occurrence of tides high enough to flood, called

acqua alta, has been increasing at an alarming rate: from four to five times per ten years at the turn of

the 20th century to at least thirty times per ten years today49. When water overtakes the walkways,

pedestrian traffic flow is slowed and the area in which pedestrians can travel is limited, creating

severe congestion.

Acqua alta is also a contributor to the erosion that is impacting the city so severely. The situation is

so dire that there have been many WPI Venice Interactive Qualifying Projects dedicated to the

subject of canal wall erosion and possible solutions to the problem. One regulation Venice

implements is in the form of the ARGOS system: enforcing speed limits causes motorboats to

create a lesser wake, which in turn causes less erosion of canal walls. If the erosion trend continues,

however, Venice will be in danger of completely succumbing to the sea, causing an impossible living

situation and the loss of an incredible culture.

44 (Contesso 2011) 45 (Contesso 2011) 46 (Contesso 2011) 47 (Contesso 2011) 48(Rameiri, et al. 1998) 49(Rameiri, et al. 1998)

Comment [C11]: What are the other three? Might as well name them.

Comment [C12]: Opinion

Comment [C13]: Is ARGOS introduced earlier in the paper?

Comment [C14]: Opinion and has nothing to do with the project

18

2.5 VENETIAN TRAFFIC MODELS

Looking into future applications of data collection, the creation of an integrated pedestrian traffic

model is necessary to provide an easy means of extracting useful information. Though the

development of such a comprehensive model is out of reach for this year’s Mobility team given the

time and fund limitations, it is important to understand pedestrian models so that data collection can

be tailored to provide the models with information that is useful to its creation.

The modeling approach that fits the needs of the Venice traffic model is referred to as agent based

modeling, and more specifically, autonomous agent based modeling. This type of modeling allows

for individual governing of agents, which lets each agent uniquely interact with the environment

based on programmed predispositions and reactions. In modeling of traffic, each agent will be

assigned a specific start and end location. Though the beginning and end are predefined, the method

of transportation and the path taken vary based on the interactions between the agent and its

surroundings, including other agents. In terms of Venice, agent based modeling allows for the

important distinction between tourists and locals in pedestrian mobility stream models. The accuracy

of such a model is proportional to the agents’ ability to mimic the real life counterpart. Hence it is

important to collect data that can speak to the various biases of agents.

2.5.1 Past Models

Since the beginning of the Venice Project Site, there have been several Interactive Qualifying Project

teams that have done work that helped further traffic models. In 2008 a team created a pedestrian

model using NetLogo, an agent based modeling environment50. The model focused on Campo San

Filippo e Giacomo due to project time and resource constraints. This spot was chosen because it

was identified as a hotspot, or high traffic area. The model accounted for Venetian and tourist

agents and dictated their speed based upon data collected during the IQP. The model only portrayed

traffic during Wednesday at 1300 hours due to data limitations. The data collected by the team

during the IQP was inputted to the program. This data was collected and recorded visually using

three cameras set up strategically around the hotspot51. Though the model created was limited and

didn’t accurately portray congestion, it still demonstrates the necessity of an experienced

programmer in creating a model, and demonstrates one accurate data collection technique. The

50 (C. Catanese, et al. 2008) 51 (C. Catanese, et al. 2008)

Comment [C15]: Make sure to tie everything back to our project specifically. The past models don’t matter if they don’t apply to our project

Comment [C16]: I don’t know. Weird sentence structure and is it necessary?

Comment [C17]: Define agents

19

importance of recording visual data should not be underestimated. It is crucial to confirming and

checking past data collection.

There was also a traffic model created in 2010 that detailed boat traffic in the city. This project was

called Venice Table. The programming aspect was spearheaded by RedFish group and the Santa Fe

Complex, with the Venice Mobility team providing the data for the model along with several

government agencies. To allow for a comprehensive model of canal traffic, 23 observation points

were used for data collection. In order to determine when each boat turns in the model, the data that

was utilized included which canals boats entered from and returned to, the time of day, and each

boat’s license plate number52. Control of the model was designed to be interactive and intuitive. To

allow for the intuitive nature of the Venice Table, the model was built on an interactive gaming

software program.

2.5.2 Modeling Tools

Traffic models are very useful tool for understanding and improving mobility streams.

Unfortunately, the creation of good models takes a lot of time, expertise, and data. The

implementation of an autonomous data collection system will allow the collection of data with

minimal human interaction. There are several tools present that can make this type of continuous

autonomous data collection a possibility. One of those tools is Open CV, which is a software

approach that uses video to autonomously recognize, track, and record traffic and distinguish

physical differences, as well as velocity.

2.5.3 How Models Read Data

Over the years, Venice has had countless groups, individuals, and governments study it and collect a

wide array of data relevant to traffic. The question therefore becomes “How is this data formatted

so that it can be inputted into a model?” The agent based models have proved useful in the past and

will continue to be a method of data presentation. Agents, in our case pedestrians, will interact with

the environment, Venice, developed in the model. The environment itself is made up of two main

components; edges and nodes. Edges are the borders and boundaries that define the fields in which

the pedestrian agent types move. Nodes, on the other hand, are not physical or visible entities in the

final 2D model. They help to define how the pedestrians will move. For instance a specific

pedestrian, depending on the constraints that are programmed into a model, will move from a node

52 (VeniceTable: Interactive Traffic Simulation Table 2010)

Comment [C18]: Potentially opinion?

Comment [C19]: My senior year English teacher would say that this is a colloquialism…

Comment [C20]: Connect this to our project

Comment [C21]:

Comment [C22]: Word choice?

20

‘A’ to another node ‘B’. For the Venice models, these nodes are typically placed at traffic ‘choke

points’ like bridges. For instance, a bridge spanning a canal in an east to west direction might have a

node ‘A’ on its east side and another node ‘B’ on its west side. Movement defined as ‘AB’ would

indicate a pedestrian moving from ‘A’ to ‘B,’ or one traveling west across the bridge. Movement

defined as ‘BA’ would indicate the opposite: a pedestrian traveling east across the same bridge.

Therefore data is organized by the number and type of pedestrian, as well as their node movement

at choke points.

Nodes can also help define sources (points where pedestrians originate) and sinks (points where

pedestrians are attracted). How agent types are programmed will determine their ‘source-sink

interaction’. In Venice, sources and sinks can be split up into two categories based on the types of

pedestrians. Locals tend to originate from residential areas and will generally flow to places of

employment or learning. In this case, this would mean that their homes are the sources and their

places of work and schools are the sinks. At the end of the day, this would be reversed and the

sources and sinks would switch. Tourists tend to originate from hotels, bus terminals, and the train

station, and are attracted to places like museums, shops, and the “tourist triangle”. In the case of say

a museum, two nodes would still have to be used in order to define movement ‘in’ or ‘out’ of the

museum. The museum would then be defined visually on the model so the movement in and out of

the building doesn’t look like pedestrians disappearing and reappearing at a point inside the model.

Data on sources and sinks can either be collected by hand like has been done at bridges or can be

extracted from already available data related to, in this case, attendance at museums or even perhaps

counted from a security camera at the front door.

The concept of ‘disappearing’ and ‘reappearing’ comes into play another way when modeling

pedestrian traffic in Venice. Walking is not the sole form of transportation in the city, and as a result

many people will use multiple forms of transportation throughout a day. If there is not any

integration between pedestrian traffic and boat traffic in the model, then when a pedestrian ‘gets on’

a traghetto or a water taxi in the model it will look as if someone just disappeared from the middle

of Venice and reappeared somewhere else. To combat this, data can be collected that reflects the

number of pedestrians that are getting on and off at each boat stop. Nodes can then be used at each

stop in the model to define movement on or off boats. A truly comprehensive Venice traffic model

would completely integrate the boat and pedestrian traffic models into one seeing as the various

forms of transportation are not independent of one another.

21

MethodologyOur project mission is to collect pedestrian traffic data for the end goal of developing an agent-

based modeling system that collects and archives data to effectively predict the behavior of

pedestrian mobility streams in Venice.

Project Objectives:

1. To quantify pre-determined pedestrian types at key locations

2. To determine the feasibility of using camera surveillance systems to collect pedestrian traffic

data by verifying video feed counts with manual counts

3. To organize the pedestrian traffic data collected into a format capable of helping develop a

pedestrian agent based model

4. To publicize pedestrian traffic data in a visually intuitive format on an online source

The project will occur over the 2011 fall semester, with preparatory work during A term and on site

work throughout B term. The project will be limited to gathering data concerning pedestrian

congestion, taking into account only the predetermined agent typology.

Figure 1: Area of Study Map

22

3.1 QUANTIFYING PEDESTRIAN AGENTS

To accomplish the project objectives, Team Mobility must effectively count pedestrians. To do this,

we must take manual counts at key locations, identify between Venetians and tourists using

identifying characteristics, and implement specific counting methods.

3.1.1 Focus Area and Key Counting Locations

The 2010 Venice Mobility team previously analyzed congestion in the San Marco district, so our

team plans on expanding the data collected in San Marco by focusing on different locations within

the district. We will also be considering key tourist locations and traghetto stops. The specific

locations that will be analyzed for our project will be evaluated and determined upon arrival in

Venice so we can gain first-hand knowledge of where the worst congestion locations are.

3.1.2 Assigning Agent Types and Identifying Each Type’s Characteristics

Following in suit with previous years’ methodologies, the 2011 Mobility Team will be maintain the

same agent types. This will provide congruency in the data sets from different years, which will allow

for the possibility of combining multiple data streams in models produced in future endeavors.

Pedestrian traffic agents will continue to be categorized under tourist and local typesets. Locals have

been found to move faster on average as well as follow more direct paths. They also tend to walk

alone or in smaller groups. Tourist agent types have been shown in past data sets to move slower

and in larger groups53. The summary of type characteristics can be seen in Table 1.

Table 1: Pedestrian Agent Type Characteristics

Tourist Venetian Has camera in hand or is taking pictures Lacks clear tourist indicators Has map Travels quickly and directly across bridgeLooks lost, refers to street/bridge signs to orient self

May stop and greet other pedestrians, usually in Italian, indicating residence

Looks up at scenery May have stroller, dog, shopping cart

Each type has provided a unique element to pedestrian traffic in historical Venice. Much of the

locally caused traffic stems from commuting between primarily residential zones and primarily

commercial and business zones. Tourist traffic, on the other hand, tends to focus on specific sites

and has daily peaks and drops. These tourist attractors, as well as the local start and end locations,

53 (C. Catanese, et al. 2008)

23

can be referred to as sources and sinks when translating our data for model production. Our

project’s area of study will focus in a few of these identified sources and sinks. We will be utilizing

existing maps to determine where residential zones are, as well as hotels, schools, and other hotspot

locations. Also, there are existing surveillance videos which can contribute additional data via

manual counts.

Visual determination of agents while collecting data on site will be done using the visual recognition

methodology from last year’s mobility team. According to their research, their agent determining

methodology was found to be statistically accurate and therefore there is no need to recreate another

methodology when there is already an effective one in use. The established methodology is based

largely on visual markers such as behavior and clothing.

3.1.3 Counting Tools and Devices

In order to accurately quantify the flux of pedestrians at bottleneck

locations we will utilize two types of counting methods which will allow us

to quickly count a large number of pedestrians. Firstly, we will pair off into

teams of two and utilize handheld mechanical counters. Each person in the

team will focus on pedestrians moving in a certain direction and

distinguish between Venetians and Tourists based on behavior and walking

speed. Each team member will have a watch to keep track of time, a

counter in each hand to count the two types of pedestrians, and a

notebook to store all of our collected data.

The second method for data collection will involve a TI Calculator program which will allow for the

simultaneous counting of two agent types, each in two directions. There are a few benefits to using

this calculator program over manually counting with the clickers. Some of these benefits include the

ability to have just one team member work at each key location, the ability to do counts at twice as

many locations simultaneously, and also have data in a digital form which is already organized into

tables.

There are also benefits to using to using the manual counters as well. By using the mechanical

counters we will have no data loss from unforeseen calculator problems. Some of these problems

may occur due to hardware limitations. For example, the TI-84+ series calculator has about 24kB of

usable RAM, and only a 15 MHz processor. These hardware specifications may cause delays in data

Figure 2 - Mechanical Counter

24

acquisition and retention after a large number of pedestrians have been counted. Both methods will

be used and the TI Calculator program’s feasibility will be determined.

3.1.4 Time Brackets for Performing Field Counts

Our team anticipated that pedestrian mobility in Venice will differ at different times of day and days

of the week. Venice will experience more traffic in the morning due to Venetians going to work or

school and tourists will be embarking towards their tourist destinations. We will also assume that

Venetians will leave their homes much earlier in the morning than tourists and thus compose much

of the mobility streams throughout the city. Tourists moving about Venice will dominate the

afternoon hours, while Venetians remain in their place of work or school.

In addition to agent behavior being unique at different times of day, we expect them to be different

on each day of the week. For example, the weekdays will consist of many Venetians traveling to

work or school, but those Venetians will probably have a more leisurely destination on Saturday,

when they have time off from work. On Sundays, Venetians are very likely to be heading to church

in the morning.

For these reasons, it is necessary to bracket time intervals that appear to have homogenous traffic

streams. In order to provide consistency with the data collected from the VE10 team, we will

continue to employ the same time brackets and collect counts in the same fifteen minute time

intervals. The following table shows the time brackets that we intend to use to collect manual counts

for a given day:

Table 2: Time Brackets for Manual Counts

Bracket Name Start Time End Time

Early Morning 7:00 9:00

Morning 9:00 11:00

Mid-Day 11:00 13:00

Afternoon 13:00 17:00

Evening 17:00 19:00

The previous year’s results demonstrate relatively stable results within each time bracket. Therefore,

we will proceed under the same time constraints, conducting manual counts at different locations

25

and on different days of the week to collect as much data on volume and behavioral flow as possible

in a seven-week time span.

3.1.5 Counting Methods at Key Locations

By holding one mechanical clicker in each hand, we are able to collect two types of data

simultaneously: the number of tourists crossing and the number of Venetians crossing in one

direction. In order to determine the bi-directional flux of pedestrians across a bridge, we will require

teams of two at each location. The method for counting pedestrians includes each of the two team

members standing at the top of the bridge, facing in opposite directions, and record one click using

the appropriate hand to count the number of individuals crossing the bridge. These counts will be

performed for 15 minute sessions, and will be recorded at the end of each session.

If the weather is poor (raining, flooding), the Mobility team will not be conducting manual counts in

order to avoid discrepancies in the data. We will count only during ideal conditions, which will

provide us with the most accurate pedestrian traffic information.

3.2 DETERMINING VIDEO SURVEILLANCE FEASIBILITY

Using video surveillance technology will allow for manual counts to be collected without a person

having to be on site. Our team will conduct counts using video clips recorded during the on-field

manual counts and compare the two datasets to determine if using cameras as a means for collecting

data is a practical method.

3.2.1 Video Verification Methods

To determine the feasibility of using a video surveillance system as a pedestrian tabulator and data

collector for a pedestrian model, our team will employ manual counts. When a field count location

is determined, two video cameras will be set up with a view of all pedestrians passing through the

location, with one camera facing each direction. While the cameras are recording, our team will

conduct manual counts for the predetermined time brackets. Once the field counts are complete,

the video feed will be reviewed by the team and the pedestrians will be recounted to determine the

accuracy of the video counting method. If the reviewed camera feed counts and the team’s manual

counts are statistically similar, then the video method is feasible. If the counts are dissimilar, another

method should be employed.

26

3.2.2 Verification Analysis

Once the video is recorded and the field count time interval is completed, the data will be analyzed.

Each team of two will watch the other team’s direction to ensure that the video counting

methodology is accurate. For example, if pair A is taking field counts for direction A and pair B is

taking counts for direction B, then pair A will watch the video from direction B and pair B will

watch that of direction A. This will provide a fresh viewpoint for every feed and an accurate

method for data analysis. If the manual field counts are considered the “actual” counts and the

counts from the video feed are considered “experimental” counts, then we will be able to calculate

the percent error between the actual and experimental data, therefore determining the feasibility of

the video method.

3.3 ANALYZING AND VISUALIZING COLLECTED DATA

We will be using field forms and other data collection forms to properly format our pedestrian data

to accommodate RedFish Group’s modeling preferences. We will also implement census tracts to

further our traffic datasets and to complement agent analysis.

3.3.1 Formatting

To ensure that the agent-based model our team is contributing to is performing as anticipated, our

team must come up with a usable format for tabulating data for the programming capabilities of our

collaborators. However, we must also take into account the visual limitations of the counters on

field when collecting large amounts of data at once. It is important not to miss any individual while

on field to ensure the least amount of error. The previous team performed preliminary field

counting to determine the limit of one counter, and found that one counter was capable of

recording one direction of flow while distinguishing between Venetian and tourist without being

overwhelmed. Their team decided that two counters per location, one per direction, were necessary

to reduce the risk of data loss. If a certain time or location is anticipated to have unusually high

traffic volumes, the decision will be made as to whether or not more than two counters should be

stationed to that location. Additionally, to verify the efficiency of our model and the accuracy of our

on location counts, we will use the same form for our video recording counts.

The counts made by each individual would then be collaborated at the end of the time bracket and

collected in excel spreadsheets to be submitted to our collaborators and integrated into the

27

pedestrian model. This data will also be converted into a format visible to GIS Cloud for still-time

visualizations. Refer to the following section 3.3.2 for the details on the data collection forms.

3.3.2 Field Forms

To collect all of the data in an organized manner for the utilization of our collaborators, a field

spreadsheet template was created. This will be used to collect the number of persons that cross

through a specific station by type of agent, and in which direction of travel. Refer to Appendix 5 for

an example of a field form. The same template will be used to collect counts through video clips.

This field form will then be used to tabulate data in a form suitable for our collaborators to integrate

into an agent-based model. Table 3 shows the columns that will be filled out for collection of all on-

field data.

Table 3: On Site Manual Pedestrian Counting Template

Date: Location: Recorder: Time Traveling To Traveling From Count

To collect data such as the number of students enrolled in a school on location, or how many

people buy tickets to a certain museum, or even how many Venetians attend a specific church, we

will use a survey guideline in the field. Key information from these sites would be attendance and

hours of operation. If we knew the capacity of specific establishments, we could better model agent

interaction with the environment. The information collected will then be inputted into a spreadsheet

for use in GIS map layers and for the use of our collaborators. Table 4 below provides the intended

information we would hope to acquire from these institutions.

Table 4: Video Surveillance Data Collection Template

Date Time Establishment ID

Location Estimated Attendance

Capacity Hours of Operation

3.3.3 Pedestrian Modeling Techniques

Though the 2011 Mobility Team lacks the experience to create a NetLogo model based on the data

collected, the data will feed models created by the RedFish Group and other organizations. Aside

from a working model, the data will also work into several GIS cloud layers. The manual counts will

be able to show tourist: Venetian concentrations at collection points and will also allow us to create

28

a ‘heat map’ that shows population density at certain points in time. Once these are overlaid on the

GIS map, they can be compared to other layers to show correlation. The population density heat

map layer, viewed in conjunction with source and sink layers (e.g. schools, hotels, and museums) will

show the causes of the changes of population density throughout a day.

3.3.4 Census Tracts

Collaborating census data for our region of study is critical for supplementing our agent analysis. To

better understand pedestrian behavior, the origins and endpoints of each agent must be detailed.

The census layers of the GIS map will complement Venetian data that our team collects by

providing a picture of the residence distribution of the Venetian pedestrian agents. For example,

Figure 21 shows the amount of adults from ages twenty to sixty-four who live in particular regions

in the San Marco area.

These different age brackets will help us understand the destinations of these different agent types.

Agents under twenty years of age would likely leave their homes to go to a school in proximity to

their residency. Census tract layers can also provide the location and amount of employed Venetians

in a region. Figure 22 shows an example of the employment source location distributions in San

Marco.

3.4 PUBLICIZING DATA

Once the data is collected, analyzed, and formatted using the techniques outlined above, we will

publish our findings for public viewing through the following means.

3.4.1 Venipedia

Venipedia is an online source created and maintained by Venice IQP project groups. It is the

“Venice Wikipedia” and contains articles on myriads of topics specific to Venice. Our project group

will contribute to Venipedia by creating new pages concerning the end results of the project. The

new pages will cover our organized data of the main research topics and the visual aids we create.

This allows public access to the information, and can be expounded upon by future groups.

3.4.2 Deliverables

A major component of the Venice projects is deliverables, or visual and interactive aids that aptly

summarize the findings of a project. Our deliverable will be an interactive layered GIS cloud map of

the city of Venice, with different “layers,” or data sets, that can be displayed on or hidden from the

map. The layers will consist of agent type and direction of travel, beginning and ending locations,

29

schools and places of employment, residential and commercial zones, tourist hotspots, hotels,

traghetti stops, and other key locations. Ideally, this visual aid will allow the public to see the

relationship between agent types and congestion locations and reconsider their route across Venice,

taking into account the most congested areas as seen on the deliverable map.

3.4.3 Furthering Models

An objective of our project is to collect and format data in such a way as to further the development

of agent based modeling systems. We will do this by complying with the correct data format for the

models as specified by RedFish Group. We must compile all of our data, sort it into the specific

format, and edit it to include the correct dataset for RedFish’s purpose. Ultimately, this will enable

the company to develop a model for pedestrian congestion, taking into account traffic flow and

congested locations.

30

BibliographyAmilcar, Marcus, Amy Bourgeois, Savonne Setalsingh, and Matthew Tassinari. Mobility in the Floating City: A Study of Pedestrian and Water Transportation. Interactive Qualifying Project Report, Worcester: Worcester Polytechnic Institute: Venice Project Center, 2009.

Bloisi, D., L. Iocchi, P. Remagnino, and N. Monekosso. "ARGOS-A Video Surveillance System for Boat Traffic Monitoring in Venice." International Journal of Pattern Recognition and Artificial Intelligence, 2009: 1407-1502.

Carnevale di Venezia 2012. 2009. http://www.carnevale.venezia.it/ (accessed September 18, 2011).

Catanese, Chris, Danise Chou, Bethany Lagrant, and Rudy Pinkham. Floating Around Venice: Developing Mobility Management Tools and Methodologies in Venice. Interactive Qualifying Project Final Report, Worcester: Worcester Polytechnic Institute: Venice Project Center, 2008.

Catanese, Christopher D., Danice Yequay Chou, Bethany J. Lagrant, and Rudy E. Pinkham. "Floating Around Venice: Developing Mobility Management Tool." 2008.

Centre, Flight. "Italy: A Unique Work of Art." Footprints, 2010.

Cessi, Roberto, and John Foot. "Venice." Britannica Academic Edition. 2011. http://www.britannica.com/EBchecked/topic/625298/Venice/24379/Canal-boats-and-bridges (accessed September 16, 2011).

Cessi, Roberto, Denis Cosgrove, and John Foot. Italy. 2011. http://www.britannica.com/EBchecked/topic/625298/Venice (accessed September 16, 2011).

Chiu, David, Anand Jagannath, and Emily Nodine. "The moto ondoso index: Assessing the effects of boat traffic in the canals of Venice." 2002.

Contesso, Lia. Venice Bridges. 2011. (accessed September 19, 2011).

Davis, Robert C., and Garry R. Marvin. Venice, the Tourist Maze: A Cultural Critique of the World's Most Touristed City. Berkeley: University of California Press, 2004.

Drake, Cathryn. "Venice crossings: A traghetto tour reveals the city's other side." Wall Street Journal, 2008: sec World News.

Duffy, J. "Re-Engineering the City of Venice’s Cargo System for the Consorzio Trasportatori Veneziani Riuniti." 2001.

Fiorin, Franco, and Giorgio Miani. "Development Plans for Urban Public Transport." Edited by Rinio Bruttomesso and Marta Moretti. Cities on water and transport, 1995: 100-107.

31

How Stuff Works: Geography of Venice. 2011. http://geography.howstuffworks.com/europe/geography-of-venice.htm (accessed September 18, 2011).

How Were Houses in Ancient Venice Designed and Why? http://answers.yourdictionary.com/entertainment-arts/architecture/how-were-houses-in-ancient-venice-designed-and-why.html (accessed September 7, 2011).

Howard, Deborah, and S Quill. The Architectural History of Venice. Singapore: B.T. Batsford, Ltd., 2002.

Italy. https://www.cia.gov/library/publications/the-world-factbook/geos/it.html (accessed September 15, 2011).

Lopez, Angela. "Assessment of the Measure to Ease Pedestrian Congestion." Association for European Transport, 2006.

Morgan, L. H. "The City of the Sea." Harper's New Monthly Magazine, 1782: 481.

Rameiri, E., V. Cogo, Mattei, and F.E.E. "Indicators of Sustainable Development for the City and the Lagoon of Venice." (Fondazione Eni Enrico Mattei) 1998.

Riganti, Patrizia, and Peter Nijkamp. "Congestion in Popular Tourist Areas: A Multi-Attribute Experimental Choice Analysis of Willingness-to-Wait in Amsterdam." Tourism Economics, 2008: 1-15.

Traffic Congestion Factoids. March 2009. http://www.fhwa.dot.gov/congestion/factoids.html (accessed September 14, 2011).

Van der Borg, Jan. "Tourism and Urban Development: The Case of Venice, Italy." Tourism Recreation Research 17, no. 2 (1992): 46-56.

Van der Borg, Jan, and A. P. Russo. "Towards Sustainable Tourism in Venice." Sustainable Venice: Suggestions for the Future, 2001: 159-193.

VeniceTable: Interactive Traffic Simulation Table. 2010. http://redfish.com/SFComplex/projects/veniceTable.html (accessed September 5, 2011).

Zanini, Francesco, Fabio Lando, and Manuel Bellio. "Effects of Tourism on Venice: Commercial Changes over 30 Years." Working Papers, 2008.

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AppendicesAPPENDIX 1: PEDESTRIAN AGENT TYPES FLOW CHART

Figure 3: Flow Cart of Pedestrian Agent Types

33

APPENDIX 2: CENSUS DATA GRAPHIC

Table 5: Venetian Resident Density by Age and District (From 2001 Census Data)

APPENDIX 3: GIS CLOUD MAP LAYERS

3.1 Hotels Layer

Figure 4: Hotel Locations in San Marco

34

3.2 Schools Layer

Figure 5: School Locations in Venice

3.3 Museums Layer

Figure 6: Museum Locations in Venice

35

3.4 Churches Layer

Figure 7: Church Locations in Venice

Figure 8: Church Locations in San Marco

36

3.5 Tourist Sites Layer

Figure 9: Major Tourist Sites in Venice

37

APPENDIX 4: DATABASE FORM

Date Time Location ID

Venetians Traveling A

to B

Venetians

Traveling B to A

Total

Venetians

Tourists

Traveling A to B

Tourists

Traveling B to A

Total

Tourists

38

APPENDIX 5: FIELD FORMS

5.1 Venetian Field Form

Table 6: Venetian Field Form for Manual Counts

Date: Location: Recorder:Time Traveling To Traveling From Count7:00 7:00 7:15 7:15 7:30 7:30 7:45 7:45 8:00 8:00 ------ 16:00 16:00 16:15 16:15 16:30 16:30 16:45 16:45 17:00 17:00

A B A B A B A B A B --- B A B A B A B A B A

B A B A B A B A B A --- A B A B A B A B A B

5.2 Tourist Field Form

Table 7: Tourist Field Form for Manual Counts

Date: Location: Recorder:Time Traveling To Traveling From Count7:00 7:00 7:15 7:15 7:30 7:30 7:45 7:45 8:00 8:00 ------ 16:00

A B A B A B A B A B --- B

B A B A B A B A B A --- A

39

16:00 16:15 16:15 16:30 16:30 16:45 16:45 17:00 17:00

A B A B A B A B A

B A B A B A B A B

40

APPENDIX 6: ESTABLISHMENT DATA FORM

Table 8: Form for Institution Information

Date Time Establishment ID

Location Estimated Attendance

Capacity Hours of Operation

41

APPENDIX 7: B TERM SCHEDULE

Figure 10: Mobility October Schedule

Figure 11: Mobility November Schedule

42

Figure 12: Mobility December Schedule

43

APPENDIX 8: BUDGET

Team Mobility Budget – Fall Semester 2011 Item Price/Item Quantity Total Price Price/Team MemberManual Clickers $5.00 10 $50.00 $12.50Binder $12.00 1 $12.00 $3.00Clipboards $4.00 4 $16.00 $4.00 $83.00 $20.75