Introduction Cities 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 1
http://www.comune.venezia.it/flex/cm/pages/ServeBLOB.php/L/EN/IDPagina/117
2(Morgan
3
1782)
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_ProjectÂ
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.
Background Venice 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 7(Cessi,
1782) 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.
Figure 5: A Canal Near the Arsenale
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.) 1782) 12(Cessi, Cosgrove and Foot, Italy 2011) 11(Morgan
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 city 16 . 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.
Figure 6: A Standard Street in Venice
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) 1782) 15(Morgan 1782) 16(Morgan 1782) 17(Morgan 1782) 18(Rameiri, et al. 1998) 14(Morgan
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 streets 20 . 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 congested 21 . 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 wakes 22 . 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) (Davis and Marvin 2004) 21 (Davis and Marvin 2004) 22 (Black, et al. 2008) 20
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,
26
Lando and Bellio 2008)
http://ec.europa.eu/environment/iczm/pdf/tcca_material.pdf
27(Davis
and Marvin 2004) (Howard and Quill 2002) 29 (Cessi and Foot, Venice 2011) 28
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 (Cessi and Foot, Venice 2011) (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) 30 31
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 wellknown 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
(Davis and Marvin 2004) (Davis and Marvin 2004) 39 (Van der Borg and Russo, Towards Sustainable Tourism in Venice 2001) 40 (Davis and Marvin 2004) 41 (Contesso 2011) 37 38
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 (Contesso 2011) (Contesso 2011) 44 (Contesso 2011) 45 (C. Catanese, et al. 2008) 42 43
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
Comment [FB2]: reference
Complex, with the Venice Mobility team providing the data for the model along with several
Comment [FB3]: reference
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 47
(C. Catanese, et al. 2008) (VeniceTable: Interactive Traffic Simulation Table 2010)
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/co ntent/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
Comment [FB5]: Maybe a graphic or illustration would help clarify the concepts….
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 [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.
Methodology The 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 agentbased 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 8week 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
Comment [CF7]: Remove nodes and put numbers to reflect 2010
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
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:
Time
Traveling To
Recorder: 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.