1. Traversing the Labyrinth:
A Comprehensive Analysis of Pedestrian Traffic in Venice
Chelsea Fogarty Steven Greco
Chemical Engineering ‘13 Biomedical Engineering ‘13
Geordie Folinas Cassandra Stacy
Mechanical Engineering ‘13 Environmental Engineering ‘13
2. Sponsored by: In collaboration with:
• City of Venice • Cody Smith, Santa Fe Complex
• Department of Mobility and • RedFish Group
Transportation
Advisors:
Professor Fabio Carrera, Ph.D.
Professor Frederick Bianchi, D.A.
3. Mobility Infrastructure
• Walkways averaging 2 meters wide
• 294 squares
• 433 bridges
• Limited infrastructure
– Hold capacity of 25,000 visitors per day
– 157.85 km of walkways
4. A greater influx of
tourists is
beginning to affect
pedestrian mobility.
5. Tourism in Venice Throughout the Years
In 2010:
● 20,000,000 annual tourists
● 55,000 daily tourists
Determined from information received from the City of Venice Statistics Office.
6. Projected Tourism Trends
40,000,000
35,000,000
30,000,000
Number of Tourists
25,000,000
Overnight Tourists
20,000,000 Day Trips
Total Tourists
15,000,000
Expon. (Total Tourists)
10,000,000
5,000,000
0
1940 1960 1980 2000 2020 2040 2060
7. Effects on Venice
• Degrades Quality of Life
• Strains Infrastructure
• Safety & Security Compromised
9. Outliers Become Everyday Occurrences
Population levels during the
summer months and
holidays could become the
norm for everyday life in
Venice…
10. Managing Pedestrian Traffic
• Used on Holidays One way bridges
• Largely Reactive
Deploying police
Temporary bridges
Barriers
Separate queues
Seasonal Actv lines
Close Piazzale Roma
to incoming cars
11. Managing Pedestrian Traffic
• Will need to be used
more frequently
• As peaks become
the norm so too will
preventive measures
• Need a way to
determine when and
where peaks will form
12. Solution: Pedestrian Model
• Traffic Predictions
• Allow for Preventive
Measures
• Interactive
Traffic Model centered about Study Area
47. 5000
Study Area Total Day Ridership Comparison 2009
4500 4330
4000
3500
Number of Passengers
3000
2500 Full Day Disembarkment
2243
2087 2116 Full Day Boarding
2000
Totals Full Day
1500
1153 1131
963
1000
608
523
500
0
Sant'Angelo Santa Maria del Giglio San Samuele
53. Riva del Carbon Arrivals
20
Carbon
18
16
Number of Passengers/Boat
14
12
Hours of
Operation: 10
8:00-13:00
8
Closed on
Sunday
6
4
2
Dates:
7/11/2011 0
8/11/2011 8:00 8:43 9:26 10:09 10:52 11:34 12:17 13:00
54. Riva del Carbon Departures
20
Carbon
18
16
Number of Passengers/Boat
14
12
Hours of
Operation: 10
8:00-13:00
8
Closed on
Sunday
6
4
2
Dates:
7/11/2011 0
8/11/2011 8:00 8:43 9:26 10:09 10:52 11:34 12:17 13:00
55. Riva del Carbon Total
Carbon
Departing
170
Hours of 34%
Operation
(Ore): Arriving
8:00-13:00
335
Closed on
66%
Sunday
Number of Crossings: 96
Average Number on Boat: 5.26
60. Sant'Angelo Total
Sant’Angelo
Departing
488
Hours of
Operation:
39%
7:30-20:00
Sunday: Arriving
8:30-19:30 779
61%
Number of Crossings: 157
Average Number on Boat: 8.07
63. San Samuele Arrivals
20
San Samuele
18
16
Number of Passengers/Boat
14
12
Hours of
Operation: 10
8:30-13:30
Closed on 8
Sunday
6
4
2
Dates:
7/11/2011 0
8/11/2011 8:30 9:04 9:38 10:12 10:45 11:19 11:53 12:27 13:01 13:35
64. San Samuele Departures
20
San Samuele
18
16
Number of Passengers /Boat
14
12
Hours of
Operation: 10
8:30-13:30
Closed on 8
Sunday
6
4
2
Dates:
7/11/2011 0
8/11/2011 8:30 9:04 9:38 10:12 10:45 11:19 11:53 12:27 13:01 13:35
65. San Samuele Total
San Samuele
Departing
76
Hours of 34%
Operation:
8:30-13:30
Closed on
Sunday Arriving
147
66%
Number of Crossings: 79
Average Number on Boat: 2.90
68. Calle Lanza
No data because the stop was out of service.
Non ci sono dati perché la stazione era fuori servizio.
69. Sant’Angelo Riva del Carbon
- -
San Toma Fondamente del Vin
Campo del Traghetto
-
San Samuele Calle Lanza
-
Ca’ Rezzonico
70. 1400
Total Traghetti Passengers Per Day
1267 Study Area Comparison
Study Area 1200
Number or Passengers 1000
800 779
Arrivals
Arrivi
Departures
Partenze
Totale per Day
Total per giorno
600
505 488
400
335
223
200 170
147
76
0
Carbon Sant'Angelo San Samuele
92. PO NTI
Ponte de la Cortesia
Ponte San Moisè
Ponte dell’Accademia
93. 1000
Study Area Comparison Ponte de la Cortesia
900
Averaged Day
Total Flow Ponte San Moisè
Study Area
800
Ponte dell'Accademia
700
600
500
# of Pedestrians/15 minutes
400
300
200
100
0
94. Study Area Comparison
Highest Number of Pedestrians
Entering Study Area Exiting Study Area Total Flow
Study Area
905
547
468
433
358
298
232
198 201
14:30 12:00 12:00 14:30 14:30 14:30 16:00 17:00 17:15
Ponte de la Cortesia Ponte San Moisè Ponte dell'Accademia
95. COLLECT & COMPILE RAW DATA
PO NTI
Available Data
Ideal Additional Data
113. Recommendations
• Graduate from
• Development of a archaic, sporadic, expensive data
collection
Fully Functional • Use software counting to improve data
collection
Computer Model • One time cost
for all of Venice • Perpetual collection
• Couple current networks with new
cameras set at key locations
• Develop mobile app
• Improve quality of life for
Venetians & Tourists
• Provide data for computer model
• Implement Turnstiles with iMob
• 30% - 100%
• Guarantee profits
• Works in every other major city in
the world
114. Thank You!
Team Mobility
Chelsea Fogarty
Geordie Folinas
Steven Greco
Cassandra Stacy
ve11-mobi@wpi.edu
sites.google.com/site/ve11mobi
Editor's Notes
Cassandra
CS
2,194 walkways averaging 2 meters wide
Daily Tourists 2010: 54,87775% increase by 2040: ~35,000,000
Strains transportation and wears out physical infrastructureOnly 2 million Venetians throughout history, and 24 million tourists a year – huge wear on the physical infrastructure, all of those people walking over the same bridges/roads every day
Traffic makes normal travel impossible - Safety Concerns. Outliers now becoming the norm.Can’t plan for – Reactionary instead of proactiveSays to like show a graph that the summers a peak time because like at that time I’m explaingwhats becoming a norm cuz I want to talk about the tourist forcastAdd graph so that I remember to add it later comprendecuz I will forget
Put pictures of police, One Way Bridges, temporary bridges, etc.
A model would provide users with accurate pedestrian traffic predictionsWould allow for preventative measuresUses limited data to provide a comprehensive picture of future trafficApplying what has been done with automobiles to pedestrians
Model will Predict Traffic and fill in data gapsThis information can provide information proactively for dispatching local authorities, creating pedestrian barriers and one ways, and if available to the general populous could allow individuals to reroute themselves to help alleviate traffic congestion
RECAP
15:00-18:00 total (holiday and non-holiday) weekday average into study area
15:00-18:00 total (holiday and non-holiday) weekday average out of study area
