1. Venetian Mobility on Land and Sea(Mobilita’ pedonale a Venezia) Chris Aloisio Jason Gabriel Kara Greenfield Alex Kelly

2. Contenuti Mission Rationale Previous Venice Mobility Studies Goals Pedestrian Counts Boat Traffic Data Analysis Computer Model Results Conclusions J

3. I NostriObbiettivi To develop a comprehensive and interactive Mobility Model for travel in the city of Venice, by studying the movement of all people through the city. J

4. Le dimensionidell’areapedonalediVenezia Central Park New York City, NY, USA Downtown Boston, MA, USA

5. Unicita’ dellamobilita’ veneziana Walking and boats are only forms of mobility K

6. Uniqueness of Venetian Mobility Small changes in public land use has a big impact on pedestrian flow K

7. StudiPassati San Filippo e Giacomo – “Moving Around Venice” – 2008 Only small areas of Venice have been studied No pedestrian data for the whole city C

8. Previous Venice Mobility Studies Autonomous Agent Boat Model – RedFish Group – 2008 No information about pedestrians on boats Pedestrian and boat data in separate models http://vimeo.com/7918318 C

9. Il NostroModello Pedestrian Counts Boat Data Special Event Studies Venice Maps & Census Data Model Large-Scale City Planning Local City Planning Emergency Preparedness C

10. Residenze e LuoghidiLavoro Business Density Population Density K

11. Modelloschematico K

12. Fermate ACTV K

13. Modelloschematico K

14. Ponti K

15. Modelloschematico K

16. Il NostroModelloPedonale Pedestrian Counts Boat Data Special Event Studies Venice Maps & Census Data Model Large-Scale City Planning Local City Planning Emergency Preparedness J

17. Conteggisu 29 Ponti Ponte dellaPaglia Ponte deiBareteri Ponte del Lovo Ponte dellaCostituzione Ponte dellaMadoneta Ponte de Cannaregio de la Guglie Ponte delleSechere Ponte deiScalzi Ponte de Rialto Ponte de L'Accademia Ponte della Veneta Marina de le Codene Ponte Nuovo di San Felice Ponte dellaCanonica Ponte SantiApostali Ponte del Forno Ponte S. Margherita Ponte Foscari Ponte dellaFrescada Ponte Giovanni Andrea de la Croce Ponte deiFrati Ponte de San Vio Ponte delleOstreghe Ponte Sansovino Ponte del Mondo Novo Ponte del Vin Ponte della Pieta‘ Ponte del Sepolcro Ponte Ca' diDio Ponte de RuugaGiuffa J

18. Strumentiusati Calculator Camera J

19. Conteggitramitecalcolatoritascabili Used programmable calculators with custom software to count pedestrians at bridges Counted 624.743 Pedestrians In 6 Weeks J

20. RisultatideiConteggi Ponte dei Scalzi Ponte della Costituzione Ponte de Rialto Ponte della Canonica Ponte del Sepolcro Ponte de L'Accademia Ponte Sansovino J

21. Ponte de L'Accademia– Pedestrian Analysis Dinner Businesses Open Stores Open Businesses Close Stores Close Lunch J

22. Collected Pedestrian Data Ponte dei Scalzi Ponte della Costituzione Ponte de Rialto Ponte della Canonica Ponte del Sepolcro Ponte de L'Accademia Ponte Sansovino J

23. Ponte di Rialto – Pedestrian Analysis Dinner Businesses Open Stores Open Businesses Close Stores Close Lunch J

24. Rialto and Accademia Dinner Businesses Open Stores Open Businesses Close Stores Close Lunch J

25. Tools for Data Collection Calculator Camera A

26. DistinzionetraVeneziani e Turisti Recorded videos at each bridge to determine ratio of Venetians to tourists A

28. Impairments?

29. Equipment?A

30. Turisti e Veneziani Ponte dei Scalzi Ponte della Costituzione Ponte de Rialto Ponte della Canonica Ponte del Sepolcro Ponte de L'Accademia Ponte Sansovino V T A

31. Proposed Mobility Model Bridge Counts Boat Data Special Event Studies Venice Maps & Census Data Model Large-Scale City Planning Local City Planning Emergency Preparedness A

32. TrasportiPubblici Used existing boat schedules for boat paths Solicited boat data from ACTV Included in computer model Model shows pedestrians entering/exiting Vaporetti A

33. Il Nostromodellopedonale Bridge Counts Boat Data Special Event Studies Venice Maps & Census Data Model Large-Scale City Planning Local City Planning Emergency Preparedness C

34. ApplicazioniSpecifiche Counted at San Michele on All Souls Day and Salute Church at Festa Della Salute Time-lapse videos of St. Mark’s Square and Festadella Madonna della Salute C

35. Festadella Madonna della Salute 0730 1630 0930 0830 1030 1130 1230 1330 1430 1530 C

36. Piazza San Marco Largest open public area in Venice One of the most popular tourist attractors Often hosts highly attended events J

37. Pedestrian Analysis – Piazza San Marco Venetian Tourist J

38. Proposed Mobility Model Bridge Counts Boat Data Special Event Studies Venice Maps & Census Data Model Large-Scale City Planning Local City Planning Emergency Preparedness K

39. AgentiIntelligenti Each agent moves independently Search for a target destination K

40. DestinazioniTuristiche K

41. DestinazionideiVeneziani K

42. Demonstration of Model C

43. Proposed Mobility Model Bridge Counts Boat Data Special Event Studies Venice Maps & Census Data Model Large-Scale City Planning Local City Planning Emergency Preparedness C

44. SupportoallaPianificazione Obstructions in common-use space A

45. Proposed Mobility Model Bridge Counts Boat Data Special Event Studies Venice Maps & Census Data Model Large-Scale City Planning Local City Planning Emergency Preparedness A

46. OttimizzazionedeiFlussiPedonali Closing streets, walkways, and canals A

47. Proposed Mobility Model Bridge Counts Boat Data Special Event Studies Venice Maps & Census Data Model Large-Scale City Planning Emergency Preparedness Local City Planning K

48. Evacuazionedi Piazza San Marco Current evacuation model Uses sight-lines Does not consider multiple agent-types Integrate data from San Marco to make model more “intelligent” K

49. SupportoallaPianificazione Predictions for Venetian city planners Street closures Canal closures Emergencyevacuations Situations thatcan’t be tested in Venice K

50. Conclusioni Venice is perfect for studying pedestrians Model of pedestrians and boats did not exist Collected pedestrian data throughout Venice Acquired data about ACTV boat traffic Created first interactive integrated mobility model Used “Autonomous Agents” in model to predict the impact of unusual situations J

51. Venice Mobility 2009 Chris Aloisio Jason Gabriel Kara Greenfield Alex Kelly Domande?