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IntroductionCities worldwide adopt a negative reputation for their mobility issues. Many travelers avoid city
traffic to save time on their trip, and 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. Mobility issues are
even more perceptible in Venice because the only modes of transportation are by foot through
complicated walkways and over narrow bridges, and by boat.
Figure 1 A map of the framework of Venice's islets, canals and walkways.
The city is made up of 121 islets connected by 435 bridges1, with no room to expand. The branch
canals range from 10 to 30 feet in width, and the intricate network of walkways are made up of
streets of no more than seven feet wide; the widest don’t exceed twenty feet2. In 2008, the City
Council Tourist Department released its annual report, claiming that, in 2007, 5,875,370 people
visited historic Venice3. 16% were Italians, the rest were foreigners. This figure has doubled since
1http://www.comune.venezia.it/flex/cm/pages/ServeBLOB.php/L/EN/IDPagina/117 2(Morgan 1782) 3 http://www.aguideinvenice.com/en/venice‐case‐8‐Report‐on‐tourism‐in‐Venice‐December‐2008.html
the 1980s. As illustrated in Figure ##, tourism is consistently increasing in Venice, but the
infrastructure is limited to the amount of pedestrians it can contain.
Locations that cause holdups in traffic are called bottlenecks. Bridges are evident locations where
traffic jams frequently occur. Alongside bridges, pedestrians in limited amounts can get from island
to island using the gondola di traghetti or the Azienda del Consorzio Trasporti Veneziano (ACTV), the
public boat transportation system. These forms of boat transport have helped alleviate a portion of
the overcrowding at bridges as well as facilitate the flow of water traffic by centralizing water travel
through 20 routes on the canals, as seen in Figure ##. However, at certain times of the day, waiting
for space on these two types of boat transportation slows pedestrian movement down.
Figure 2 A map of the ACTV public transportation system.
On various occasions, such as the Carnival and other festivals, traffic can become so severe that
pedestrians come to a standstill. During these instances, the city must take reactionary measures to
alleviate congested areas. These reactionary measures include calling upon the police last-minute to
go on site and direct traffic flow, or temporarily making walkways unidirectional. By the time
officials can get to their stations, the traffic is already at a severe state; and when pedestrians are not
informed of changes in accessibility, their routes must be amended unexpectedly. If there were a
preventative measure installed so that city officials could predict traffic behavior, then traffic can be
dealt with before it reaches an extreme state and events and transport can operate more smoothly.
Figure 3 At some instances, streets can become so crowded that traffic is at a standstill
The Venice Mobility Teams have for the past several years been working with the Department of
Transportation and Mobility, collecting qualitative pedestrian data with the intention of creating a
computer model to be used as the method for preventing traffic issues. There have been some holes
in the data and execution, however. Individuals are responsible for collecting data on-site, risking the
chance for human observational error. Data is collected in intervals of time and only in the tourist
off-season when Worcester Polytechnic Institute Interdisciplinary Qualifying Project groups are on
location. Also, the data that has been collected in the past disappears with time because there is no
central database for archiving data. In order to create a comprehensive pedestrian computer model,
there should be an automated data collection method so that data is continuously collected and
archived in a public online resource.
The city has several observational systems installed that would be advantageous for the purpose of
preventing traffic issues. These surveillance systems are the Automatic and Remote Grand Canal
Observation System (ARGOS), Hydra, and Security and Facility Expertise (SaFE) and they are
placed in strategic locations throughout Venice that give them the ability to allow data to be
collected not necessarily in real-time, but off of video clips that can be played back. Currently, these
observational systems are used to implement speed limit laws, and monitor pedestrians and boats for
crime. 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 crime4. If these cameras, as well as other
cameras that could be installed in the future at other tactical locations, we used to collect traffic data,
4(Bloisi, et al. 2009)
the data could be collected at all times of day and all year round. Clips could also be rewound and
slowed down, to make sure that observational counts were collected as accurately as possible.
Figure 4 With the ARGOS system, live images are stitched together to generate a view of the Grand Canal. Observations are used from a multi-step Kalman filter to track targets over time5
Another key advantage that video surveillance has is that it can be paired with computer software
that distinguishes between different types of pedestrians, which are referred to as agents for the
purpose of the computer model. The benefits of this identification feature in data collection is that
each agent type will have its own behavior and walking speed and will go to different points of
attraction. In Venice, pedestrians can be broken down into two simple agent categories—Venetians
and tourists. For example, tourists are more likely to have a random walking pattern, being attracted
to museums and hotels and shopping centers, while Venetians are more likely to have a structured
pattern to and from home or work. In order for the model to accurately predict the flow of traffic, it
must be able to illustrate the differences in walking patterns between locals and tourists.
5 http://www.dis.uniroma1.it/~bloisi/segmentation/segmentation.html#ARGOS_Project
Establishing a framework for the collection of data and developing the database for the computer
model is where the Venice 2011 Mobility team comes into play. A structured methodology for
collecting and archiving data has been instituted that can be executed by future traffic improvement
teams. Additionally, this methodology has been executed at key bottleneck locations throughout the
San Marco district for the continued development of this system. This data was integrated into the
beginnings of an agent-based computer model designed by the Mobility team’s collaborators, along
with data compiled from various sources provided by the municipality of Venice, that is to be
continuously added upon. The end goal of this project is to have a pedestrian agent-based
automated model that will predict the flow of traffic efficiently for the benefit of alleviating traffic
throughout the streets of Venice.
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 complex web-work of walkways, overcrowding in areas and
events that attract tourists, a disconcerting water bus schedule with many different routes and times,
and severe weather conditions where flooding can occur, forcing pedestrians to have to walk on
platforms, further narrowing the plane of mobility. For the uninformed, moving through Venice can
be an unnecessary crusade.2.1 THE ARCHITECTURAL FRAMEWORK OF VENICE
Venice is a very small, yet multifaceted city that has changed its role many times over the years. Now
known as a “museum city”, it was not originally meant to be an attraction for people all over the
world. The city was not meant supposed to hold as many people as it fequently does. Because of
Venice’s physical limitations, it has a difficult time accommodating for the congestion issues that
result from the mass influx of tourist.
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 position6.”
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 workers7. 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
population of the new Venice revolutionized the balance of forces throughout Italy. All facets of
society from the mainland were preserved along with their various rights and social roles. Among
them were the leading members of their ecclesiastical hierarchy.
6(Morgan 1782) 7(Cessi, Cosgrove and Foot, Italy 2011)
Comment [FB1]: There is a problem with the organization of the paper…you start this section with a discussion of Venice and it’s geography etc…. then you lead into a statement about the problems with congestion….then…you go back to describing Venice and its lagoons, etc….I can’t follow the development of ideas in the paper….think about the organization…..
Waves of refugees continued to flow onto the islands as the Lombards gradually took more territory
from the Byzantines until AD 639 when the fall of Oderzo solidified the collapse of the Byzantine
defense system8. This was a key moment in the emergence of maritime Venice.
Venice was still loyal to the Byzantine government, and therefore all public administration was still
carried out in its name, yet the continuing war against the Lombards eventually brought strain to the
government’s control of the city. The pressure of wartime life increased the Venetian’s inclination
towards independence. The outbreak of religious conflict between Rome and Byzantium around 726
created serious clashes in Italy. Venetian troops joined forces with the Pope and took a stand against
the authority of the exarch, electing the first doge, Duke Orso, while still remaining under the
Byzantine Empire. It was not until the collapse of the empire in 751 that independence was
accelerated.
While Venice was dealing with political strife and continuous turnovers of power, it was also taking
advantage of the opportunities offered by the sea and commerce. Trades passing through the city
included dyes, leathers, spices, and many other goods. The lagoon province was the bridge between
the European west, and the Islamic and Byzantine territories in the east. By the first half of the
sixteenth century, Venice was the “great metropolis” that it is well-known for today. It hosted a
variety of activities, trade continued on a large scale, and people came from all over the world.
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 of stone. 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 stress9. Population and manufactures
grew exponentially, and 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
8 (Ortalli 1999)
9(How Were Houses in Ancient Venice Designed and Why? n.d.)
of brick covered with mastic for adhesion10. Palaces and houses were built and rebuilt overtime,
along with churches, monasteries, and bell towers. The shape and direction of the canals were
changed and bridges, road systems and boat transportation were integrated. Various architectural
styles such as the famous Gothic, Roman, Byzantine and Renaissance techniques were blended
together. 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 circumscribe the original islands, while the rest of the water area has been
recovered by erecting walls composed of granite along the line of these canals, which lay the
foundation for the adjacent buildings11.
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 wide12. The sides are lined with palaces and buildings reflecting the Gothic,
Romanesque, and Renaissance grandeur from its early development.
10(How Were Houses in Ancient Venice Designed and Why? n.d.) 11(Morgan 1782) 12(Cessi, Cosgrove and Foot, Italy 2011)
Figure 5: A Canal Near the Arsenale
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 Venice13. They too are narrow, short, and crooked, and they penetrate every part of the city. Most
of them are passages about seven feet wide, with the widest of streets not more than twenty-five
feet14. 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 underneath15. 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 city16. 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 Venice17.
2.4 ENVIRONMENTAL IMPACTS ON MOBILITY
Venice’s unique infrastructure is slowly degrading from the severity of the environmental impacts it
sustains. 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 Venice18. This has been a problem for centuries, and the occurrence of tides high
13(Morgan 1782) 14(Morgan 1782) 15(Morgan 1782) 16(Morgan 1782) 17(Morgan 1782) 18(Rameiri, et al. 1998)
Figure 6: A Standard Street in Venice
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 today19.
2.4.1 Acqua Alta
The phenomenon of acqua alta occurs when there are southeast winds and a high tide at the same
time, which causes the waves to spill over the canal walls into the city streets20 . When water
overtakes the walkways, pedestrian traffic flow is slowed and the area in which pedestrians can travel
is limited, creating severe congestion. Sidewalks become flooded when there is a tide 100 or more
centimeters above the average sea level. Platforms raised 120 centimeters off of the ground, called
passerelle, are placed strategically along flooded pathways to enable pedestrians to walk above the
water. While this is a helpful and necessary strategy for staying dry, it has a severe impact on the
walkers’ mobility. The passerelle are narrow and create a difficult passing situation. The cramped space
makes the walking rate slow and creates pedestrian congestion.
St. Mark’s Square, a popular tourist destination, is one of the lowest sections of the city, and as a
result is flooded with every acqua alta. The passerelle are placed throughout the square and leading to
other tourist destinations, and many tourists travel upon them. Since the platforms are “just barely
wide enough for two-way traffic,” a tourist taking pictures or an older person walking slowly can
cause a large section of the walkway to become congested21. If the tides rise higher than 120
centimeters, the passerelle are at risk of floating off of their supports. When this happens, walkways
are completely hindered and only those with rainboots can walk through the city without wetting
their feet.
2.4.2 Canal Wall Damage
Acqua alta is also a contributor to the erosion that is impacting the city so severely. The other large
cause of erosion is the wakes caused by motor boats. As water collides with canal walls, it erodes the
mortar that acts as an adhesive between the bricks and stone, and the wall becomes “more
susceptible to the destructive stresses and forces” of the tides and wakes22. When the erosion
becomes dangerous for pedestrians or the infrastructure, the walls must be repaired. Construction is
necessary, but impairs mobility because the materials and space required for restoration overtake
19(Rameiri, et al. 1998) 20 (Davis and Marvin 2004) 21 (Davis and Marvin 2004) 22 (Black, et al. 2008)
parts of the walkways. This causes backups down the walkways and has an overall negative effect
on congestion.
2.3 TOURISM IN VENICE
The Queen of the Adriatic has been attracting foreigners for centuries. Considered a “heritage” city,
it in itself is an attraction, where tourism dominates.23 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.
2.3.1 Popular Tourist Sites and Events
The concentration of tourists is a problem that Venetians have been attempting to control 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,
and marks the beginning of Lent. A huge amount of tourists travel 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)24. 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.
2.3.2 Magnitude of Tourists
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
23 http://ec.europa.eu/environment/iczm/pdf/tcca_material.pdf 24(Carnevale di Venezia 2012 2009)
seen in Venice, where there has been a significant influx of tourists over the years25. For two-thirds
of the year, the number of visitors surpasses the socio-economic carrying capacity, which was
determined by Costa and Canestrelli to be 25,000 visitors per day. This ultimately results in the
regular issue of traffic congestion26. This congestion can be seen at tourist sites and on bridges,
where the limited space often creates crowds of people trying to push through to their destination.
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.”27 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.
2.2 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 mobility28. 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.
2.2.1 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
transportation29. These boats are keel-less and used almost exclusively for tourism in this day and
25(Zanini, Lando and Bellio 2008) 26 http://ec.europa.eu/environment/iczm/pdf/tcca_material.pdf 27(Davis and Marvin 2004) 28 (Howard and Quill 2002) 29 (Cessi and Foot, Venice 2011)
age30. 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, are unglorified gondolas which are another popular form of
transportation in Venice, and there are now seven of these ferry crossings across the Grand Canal31.
These ferries operate at certain points between bridges on the Grand Canal and shuttle pedestrians
across for just 50 cents32.
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 shipbuilders33. 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 Sea34.
Venice also had a very well equipped navy, which had the ability to build one war galley per day35.
These galleys were handcrafted in shipyards called squeri where all types of traditional boats were
crafted.
2.2.2 Water-Based Public Transportation
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 interests36. These stops can cause
a large amount of traffic and affect mobility. The traffic patterns of taxis and gondolas are difficult 30 (Cessi and Foot, Venice 2011) 31 (Drake 2008) 32 (Drake 2008) 33 (Davis and Marvin 2004) 34 (Davis and Marvin 2004) 35 (Davis and Marvin 2004) 36 (Chiu, Jagannath and Nodine 2002)
to predict and their destinations are random, therefore their traffic patterns do not significantly
influence overall mobility in Venice.
2.2.3 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 across37.
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 demands 38 . Pedestrian traffic demands have been growing
perpetually since the1950’s due to the overwhelming influx of tourists39. The combination of a large
population of tourists new to the area and a confusing layout intensifies the effects of pedestrian
congestion.
2.2.4 Venetian Bridges
The different islands of the archipelago are interconnected by an array of over four hundred
bridges40. These bridges are crucial to the infrastructure of Venice, and have become recognizable as
indispensable monuments of the city which are utilized on a daily basis41. Four of the most well-
known bridges in Venice traverse the Grand Canal, including the Ponte di Rialto, Ponte dell’Accademia,
Ponte degli Scalzi, and the most recent addition, the Ponte della Costituzione.
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
37 (Davis and Marvin 2004) 38 (Davis and Marvin 2004) 39 (Van der Borg and Russo, Towards Sustainable Tourism in Venice 2001) 40 (Davis and Marvin 2004) 41 (Contesso 2011)
location as the Ponte di Rialto42. This bridge was ultimately replaced in 1265 by a fixed bridge which
later collapsed43. The Ponte di Rialto remained the only location to cross the Grand Canal until 185444.
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.
2.5 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 environment45. 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
42 (Contesso 2011) 43 (Contesso 2011) 44 (Contesso 2011) 45 (C. Catanese, et al. 2008)
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 hotspot46. 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
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 number47. 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 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 collect and analyze
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
46 (C. Catanese, et al. 2008) 47 (VeniceTable: Interactive Traffic Simulation Table 2010)
Comment [FB2]: reference
Comment [FB3]: reference
Comment [FB4]: This section is good…however, you may want to expand your discussion of models to include a more comprehensive overview with more terminology and examples of methods drawn from industry standard software….look at the following link for more information…http://www.linuxjournal.com/content/distributed-agent-based-modeling
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
‘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 a
museum, two nodes would still have to be used to define movement ‘in’ and ‘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, as it has been done previously at bridges, or
extracted from readily available information related to attendance at museums. Another method is
counting pedestrians from a security camera video feed of the front door.
The concept of ‘disappearing’ and ‘reappearing’ occurs when modeling pedestrian traffic in Venice.
Walking is not the sole form of transportation in the city, and many people use multiple forms of
transportation throughout a day. If there is no integration between pedestrian traffic and boat traffic
Comment [FB5]: Maybe a graphic or illustration would help clarify the concepts….
Comment [FB6]: This is a completely different topic….I would expand this discussion, but place it somewhere else……..
in the model, then when a pedestrian ‘gets on’ a traghetto or a water taxi in the model it will look as
if someone disappeared from their original position 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 because the various forms of transportation are not independent of one another.
MethodologyThe mission of this project was 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 pedestrian traffic at key locations
2. To analyze the feasibility of using video based pedestrian traffic counting techniques
3. To organize the pedestrian traffic data 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
This project focused on pedestrian movement throughout the district of San Marco in Venice, Italy.
A methodology was developed for accurately counting pedestrians, and the feasibility of using video
feeds to count pedestrians was investigated. The data that was collected was integrated into an agent-
based model developed by the team’s collaborators. Using real time pedestrian counts ensures that
the walkers in the model have appropriate timing and destinations. Employing the methodologies
that have been developed during this project in future years for the other five districts of Venice will
ensure a greater understanding of pedestrian movement in the city.
The project occurred from August to December of 2011, with preparatory work during the first 8-
week term and on site work throughout the latter 8 weeks. The project was limited to gathering data
concerning pedestrian congestion, taking into account only the predetermined agent typology. To
accomplish this, pedestrians were quantified based on direction of movement and whether the
pedestrian was a local or tourist.
Figure 7: Area of Study Map
3.1 QUANTIFYING PEDESTRIAN AGENTS
To accomplish the project objectives, Team Mobility counted pedestrians at key locations in the area
of study. This data was then collected and integrated into a computer model for traffic analysis. To
do this, a specific counting method was developed to conduct manual counts based on direction of
flow and pedestrian type at key connection points around San Marco. This counting method is to be
used by future teams in order to ensure consistent data sets.
3.1.1 Focus Area and Key Counting Locations
The 2010 Venice Mobility team previously analyzed congestion in the San Marco district at ten
bridge locations, as seen in Figure ##48. However, the 2011 Mobility team focused on different
counting locations, also known as nodes, for the purpose of creating a distinct location for the
starting point of the computer model within the San Marco district. The Accademia bridge was the
only bridge in common between the two collection years.
48 Amilicar, Marcus, Amy Bourgeois, Savonne Setalsingh, and Matthew Tassinari. Mobility in the Floating City: A Study of
Pedestrian Transportation. Worcester: Worcester Polytechnic Institute, 2010.
Figure 8: Map of the Ten Counting Locations Used by the B’10 Team
After evaluating a map of the area, the counting locations were determined to take place at the six
bridges that connect the two sections of land divided by the Rio San Luca, Rio del Barcaroli, and Rio
San Moisè. It was concluded that, because Ponte dell’Accademia is the only bridge on the Grand
Canal that leads into the western part of the San Marco district, it should also be analyzed by the
team. Counts were also performed at the four traghetto stops in the district along the Grand Canal.
These eleven counting locations covered all locations for pedestrians on foot into and out of the
western half of the San Marco district. The complete list of bridges and traghetto stops are referenced
in Table ##, and the map of each of these is seen in Figure ##.
Table 1: Bridges and Traghetto Stops in the Study Area
Study Area Bridges Study Area Traghetto Stops
Ponte del Teatro Riva del Carbòn – Fondamente del Vin
Ponte de San Paternian Sant’ Angelo – San Tomà
Ponte de la Cortesia San Samuele – Ca’Rezzónico
Ponte dei Barcaroli o del Cuoridoro Campo del Traghetto – Calle Lanza
Ponte de Piscina
Ponte San Moisè
Ponte dell’Accademia
Figure 9: Google Map of Traghetto Locations and Bridges Locations. Blue Anchors Symbolize Traghetti Stops and Red and Yellow Marker Pairs Symbolize Bridge Locations
3.1.2 Distinguishing Between Agent Types
A useful feature of the pedestrian model is the distinction between pedestrian agent types, such as
Venetians and tourists, because each type of pedestrian behaves differently. Venetians have a
structured schedule that occurs daily. During the workweek, Venetian pedestrians leave their
residence to go to the market, work, or school. The route traveled by locals is usually predetermined
to account for the shortest path and time. Tourists are often random in their routes, and travel in a
“wandering” pattern. Major tourist sites are often destinations, but they may stop at a shop or
restaurant on the way. As a result, tourist movement is less structured. In order to reflect this
different behavior in the agent-based computer model, it was important to collect data based on the
type of pedestrian.
The individuals that were on-site conducting the counts distinguished pedestrians mainly based on
visual cues. As previously mentioned, Venetians had more of a direct route, so their pace was
steadier, while tourists had more of a random behavior. They often walked with pets or pulled
Comment [CF7]: Remove nodes and put numbers to reflect 2010
dollies; and businessmen and women or employees were dressed in business attire. Tourists were
singled out by whether or not they were holding cameras, or if they were in tourist groups led by a
guide. They were more likely to wear leisurely clothing. A complete list of the classifications used is
in Table ##.
Tourists Venetians
“Wandering” walking pattern More direct walking pattern
Carries a camera or takes pictures Business or uniform attire
Led by a tour guide Briefcase or cart
Speaks in another language Walking a pet
Window shops
Looking at a map
3.1.3 Counting Method
In order to accurately quantify the flux of pedestrians at bottleneck locations the team utilized a
specific counting method, which allowed a quick and efficient method of counting a large number of
pedestrians. Once the peak times were discovered (when pedestrian mobility is at its heaviest),
manual counts were conducted in the field based on direction of flow.
Individuals were stationed at each bridge in clear view of pedestrian flow, with mechanical counters
in each hand. Each clicker represented a direction of flow. For example, the clicker in the
individual’s left hand represented pedestrians moving away from the counter, and the clicker in the
individual’s right hand represented pedestrians moving towards the counter. For fifteen-minute
intervals, the individual would click for each pedestrian that crossed the bridge and in which
direction he or she moved. Each individual determined a node on the bridge, and clicked for each
person to cross that node. For consistency, children being carried by their parent or in carriages, and
dogs and other pets were not counted.
Figure 10: Example of Counting Based on Direction on Bridge 6
At the end of each fifteen minute interval, the number read on the clicker was recorded into a field
form (see Appendix ##) which was later placed into spreadsheets to be submitted for integration
into the agent-based computer model.
If flow at the peak time was determined to be too heavy for one individual to count, then two
individuals were stationed at that location and each individual counted only one direction of flow.
This ensured the accuracy of the data collected.
To determine the volume of tourists utilizing a specific bridge on any given day, three project
members counted tourists while one project member counted total flow for 15-minute intervals for
two-hour blocks during the peak volume time. The tourist counts were averaged to account for
outliers (if one team member identified a significantly larger or smaller number of tourists) and
recorded in database forms. A percentage of tourist attendance at each bridge was calculated by
dividing the average by the total number of pedestrians. These percentages were applied to the rest
of the bridge data collected by the 2011 Mobility Team and can be seen in Table/Figure ##.
The same method for counting based on direction was used for counting at traghetti stops. A clicker
in each hand represented the direction of traffic traveling into or out of the study area. The time and
count was recorded each time a boat docked and departed. The field form for traghetti counts can be
viewed in Appendix ##.
The 2010 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 was anticipated to have unusually high traffic volumes, the decision was made as to whether
or not more than two counters would be stationed at that location. Additionally, to verify the
efficiency of the 2011 model and the accuracy of the on location counts, this year’s Mobility team
employed same form for our video recording counts which are discussed further in Section 3.2.
The counts made by each individual were then collaborated at the end of the time bracket and
collected in Excel spreadsheets that were submitted to the collaborators at Santa Fe Complex and
integrated into the pedestrian computer model. This data was also converted into a format visible on
GIS Cloud for still-time visualizations. Refer to the following section ### for the details on the
data collection forms.
3.1.4 Field Forms
To collect all of the data in an organized manner for the utilization of the collaborators, a field
spreadsheet template was created. This was used to collect the number of persons that cross through
a specific node by type of agent, and in which direction of travel. Refer to Appendix ## for an
example of a field form. The same spreadsheet template was used to collect counts through video
clips that are discussed in Section 3.2. Table ## shows the columns that were filled out for
collection of all on-field data.
Table 2: On Site Manual Pedestrian Counting Template
Date: Location: Recorder:
Time Traveling To Traveling From Count Number of Tourists
Number of Venetians
3.1.5 Schedule for Performing Field Counts
For the purpose of having consistent data for a comprehensive computer model of pedestrian flow,
the team counted at specific times of day. After determining the peak volume times of and which
bridges contained the majority of traffic (as seen in section ###), it was decided that these times
would be the best to conduct counts for the model. While data from all times of day would be most
ideal, due to the time limitation of seven weeks, the team sought the most crucial data for the
framework of the model. Refer to section ## for recommendations on other schedule choices.
The team decided that the best time to conduct counts was late afternoon into the early evening,
when most people were retiring home from work or most tourists were ending their days or going to
dinner. Therefore, a weekly schedule for counting was devised, as seen in Table ##.
Table 3: Schedule for Bridge Counts
Bridge Weekday Weekend
Ponte de la Cortesia 15:30 – 18:30 15:30 – 18:30
Ponte San Moise 15:30 – 18:30 15:30 – 18:30
Ponte dell’Academia 15:30 – 18:30 15:30 – 18:30
Traghetto stops ran on strict operation schedules that had to be worked around, so time brackets for
these counts were developed in order to cover all hours of operation for each stop. Table ## shows
the operational hours for each traghetti stop.
Table 4: Schedule for Traghetto Stops
Traghetti Stop Monday – Saturday Sunday
Riva del Carbon – Fondamente del Vin 8:00 – 13:00 8:00 – 13:00
Sant’Angelo – San Toma 7:30 – 20:00 8:30 – 19:30
San Samuele – Ca’ Rezzonico 8:30 – 13:30 Closed
Campo del Traghetto – Calle Lanza 9:00 – 18:00 9:00 – 18:00
The Campo del Traghetto to Calle Lanza traghetto was closed for work while the team was taking
counts, therefore, no was collected for that stop.