Shortest Urban Paths or Shortcuts to Happiness?
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The document discusses the importance of designing urban routes that enhance happiness and emotional well-being, rather than just efficiency. It details a methodology for generating paths in cities based on qualitative emotional scores, emphasizing the value of beautiful and quiet paths over the shortest ones. The study demonstrates that suggested paths can be both aesthetically pleasing and only slightly longer than traditional shortest paths, highlighting a potential shift in urban planning practices.
![Building the paths
" Build a graph linking all
adjacent cell
" Eppsteins algorithm for
ef鍖cient k-shortest paths
between source and
destination
" Select the path with the
highest average
[happiness,beauty,quiet]
scores](https://image.slidesharecdn.com/schifanella-chasm14-140624223947-phpapp02/85/Shortest-Urban-Paths-or-Shortcuts-to-Happiness-23-320.jpg)
Shortest Urban Paths or Shortcuts to Happiness?
- 1. Shortest Urban Paths or Shortcuts to Happiness? Daniele Quercia Rossano Schifanella Luca Maria Aiello
- 2. Motivations Urbanization: smart and ef鍖cient cities are crucial for sustainability
- 3. Motivations Future cities solely engineered for ef鍖ciency might not be good places to live in*. * Smart Cities, Anthony Townsend
- 4. Motivations Livable cities are those that make their dwellers happy* * Happy City, Charles Montgomery
- 5. The Major of Happy (Enrique Pe単alosa, Bogot叩, 2007)
- 6. Motivations Urban spaces and, in general, architecture are related to the perception of emotions.
- 7. A case study When providing directions to a place, web and mobile mapping services are all able to suggest the shortest route.
- 9. A case study At times, we do not necessarily take the fastest route but might enjoy alternatives that offer beautiful urban sceneries.
- 11. Our proposal Automatically generate routes that are not only short but also emotionally pleasant.
- 12. Methodology 1. Quantitative measures of location perceptions
- 13. UrbanGems " Collection of a ground truth on collective perception of the city of London " Crowdsourcing Quiet, Beauty, Happiness " Online web game (urbangems.org)
- 15. Methodology 2. Map a city with emotional scores
- 17. 則р Walkable cell of 200x200 meters 則р urbangems value for each emotional dimension 0.3
- 21. Building the paths " Build a graph linking all adjacent cells
- 22. Building the paths " Build a graph linking all adjacent cell " Eppsteins algorithm for ef鍖cient k-shortest paths between source and destination
- 23. Building the paths " Build a graph linking all adjacent cell " Eppsteins algorithm for ef鍖cient k-shortest paths between source and destination " Select the path with the highest average [happiness,beauty,quiet] scores
- 24. 1 2500 5000 Explored m paths 0 0.1 0.2 0.3 rank Beauty Quiet Happiness 1 2500 5000 Explored m paths 0 0.05 0.1 0.15 length
- 26. How do we evaluate this? 1. Validation: Is our proposal able to recommend paths that are pleasant? 2. Length trade-off: Are pleasant paths considerably longer than shortest 3. User assessment: survey
- 27. Validation " Twenty nodes that correspond to popular landmarks and cover the entire central part. " Shortest path as a baseline " 30% more beautiful (and are happier as well) " 26% quieter " 30% happier (and are also more beautiful)
- 29. Length trade-off On average, the recommended paths are only 12% longer (compared to 70% of previous work)
- 30. 0 1 2 3 4 5 6 Distance to destination 0 0.1 0.2 0.3 0.4 0.5 0.6 length
- 31. Survey " Path from Euston Square and Tate Modern " 3 situations (happy, quiet, beauty scenarios) " 4 paths to vote on a Likert scale (paths are unlabeled) " 30 participants
- 32. Shortest Beauty Quiet Happy 0 0.5 1 1.5 2 2.5 3 3.5 4 MedianLikertResponse Beauty Quiet Happy Situation: Path variations
- 33. To sum up " Shortest path performs worst " Our participants readily associate the path to the intended quality of quiet, beauty, or happiness.
- 34. To sum up (via comments) " Peaceful, historical, and distinctive are good urban qualities " Busy is the most frequently mentioned negative quality. " No consensus on contrasting qualities (e.g., historical/ charming vs. busy) or experience drastic changes over time (e.g., busy during the week, and lovely in the weekend).
- 35. Can we apply the same model to other cities? 1) the experience of Boston 2) the experience of Berlin (work in progress)
- 36. Generalization Can we predict beauty scores out of Flickr metadata?
- 37. Method " 7M geo-referenced Flickr pictures in London " For each cell: " number of pictures (density), number of views, of favorites, of comments, and of tags received by those pictures " Tags (LIWC dictionary, 72 categories)
- 38. Method " Extract features that are signi鍖cantly correlated with beauty scores " Density, posemo, negemo, swear, anx (anxiety), sad, and anger " Linear regression whose dependent variable is the beauty score
- 40. Evaluation (same framework!) " Beautiful paths are, on average, 35% more beautiful than the shortest paths. " Survey with 54 participants " Flickr beauty performs the best (3賊1)
- 41. Berlin ≒ Integration in the of鍖cial mobile app of the F棚te de la Musique 2014
- 42. Conclusion " We proposed and validated a method to incorporate emotions in routes recommendation. " Still some open points and possible directions: " Personalization " Limited spatial representation " Limited contextual representation " Beyond route recommendations