Yannan_iRun_082714
•
0 likes•292 views
A running route recommendation system I made during the Insight Fellow NYC 2014 Summer Session
Recommended
More Related Content
Viewers also liked
Recently uploaded
Recently uploaded (20)
Yannan_iRun_082714
- 2. Here is the problem Sometimes, I want to take a run from Lab to Home
- 3. Here is the problem Sometimes, I want to take a run from Lab to Home But I want to run different miles on different days
- 4. Here is the problem Sometimes, I want to take a run from Lab to Home But I want to run different miles on different days I want to run different routes on different days
- 5. Here is the problem Sometimes, I want to take a run from Lab to Home But I want to run different miles on different days I want to run different routes on different days How to find routes with targeted distances?
- 8. Building a graph of Cambridge and Boston
- 9. Data Clean Up: Original Map
- 10. Data Clean Up: Remove un-runnable area
- 11. Data Clean Up: Remove isolated islands
- 12. Data Clean Up: Remove spikes
- 13. Data Clean Up: Combine parallel roads
- 14. Data Clean Up: Remove redundant nodes
- 15. Original Map
- 16. After Data Clean Up 103,365 nodes, and 225,766 edges 17,480 nodes, and 49,354 edges 5min 30s for path search ~ 5-fold reduction
- 17. Path Finding Algorithm: My home My Lab Starting Address: my Lab Starting Address: my Home Desired Distance: 3km
- 18. Path Finding Algorithm: Dijkstra’s Algorithm finding one shortest path My home My Lab Shortest Path Length 1131m
- 19. Score • Penalize difference in desired distance and actual distance • Penalize turns / loops / zigzags • Penalize repetitive route
- 20. Path Finding Algorithm: Monte Carlo heuristic perturbation of route penalty score = 4.99 path length = 1131m My home My Lab
- 21. Path Finding Algorithm: Monte Carlo accept improvements penalty score = 2.95 path length = 1875m My home My Lab
- 22. Path Finding Algorithm: Monte Carlo only accept deterioration with low probability penalty score = 39.32 path length = 8064m My home My Lab
- 23. Path Finding Algorithm: Monte Carlo best route after 1000 iterations penalty score = 0.495 path length = 2985m My home My Lab
- 24. Path Finding Algorithm: Monte Carlo best route after another 1000 iterations penalty score = 0.251 path length = 3202m My home My Lab
- 25. Summary • Build a route recommendation system for runners • Recommend different routes for given running distances • Customized running score • Can be easily generalized for other purposes
- 28. Thank You!