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LA Grub Grabber (LAGG)

LA Grub Grabber (LAGG). David Benoff David Peterson. Advanced GIS Urban Planning UCLA June 6 2011. Contents. Quick review of the “state of the art” Website functionality: what it does Live example Behind the scenes: how we did it Contribution to Transportation Planning

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LA Grub Grabber (LAGG)

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  1. LA Grub Grabber(LAGG) David Benoff David Peterson Advanced GIS Urban Planning UCLA June 6 2011

  2. Contents • Quick review of the “state of the art” • Website functionality: what it does • Live example • Behind the scenes: how we did it • Contribution to Transportation Planning • Questions

  3. Go Metro

  4. Go Metro • Good: • Restaurants along bus and rail lines • Not so Good: • Sparse • No real crowd sourcing • Static – updates made (if at all) by Metro staff • Limited dining selection

  5. Google Search: Restaurant

  6. Google Search: Restaurant • Good: • For almost everything… • Not so Good: • Finding restaurants within a radius • Can’t define walking radius • Transit options are decent, but what if I want to know how the restaurants around each stop on my route? (can do it, but really clunky) • No Parking information

  7. Yelp

  8. Yelp • Good: • Walking distance, driving distance function • Integration with Google Maps • “select area” function with map is good • Not so Good: • For “how to get there” (no transit options listsed or driving directions , but this exists for the mobile app)

  9. What’s different about LAGG?

  10. LAGG

  11. LAGG: Find Yourself Enter your location or Click on the Map to find restaurants within a ¼ - Mile radius

  12. LAGG: Go there - BUS Find all bus routes within a ¼ - mile radius of your location

  13. LAGG: Go there - BUS Find other relevant restaurants on other bus route within a ¼ mile walking distance and 30 minute distance

  14. LAGG: Go there - DRIVE View all LA City – owned parking lots • Friends driving to meet you • You need to drive to get to a transit stop

  15. LAGG: Be Choosy Choose zip codes with high/low restaurant density

  16. LAGG: Share Share a restaurant you like via Google Forms

  17. LAGG – Live!

  18. Behind the Scenes – Metro Bus Network Algorithm (custom function) • Transformed Metro GTFS data into the table structures we needed andcreated Fusion Tables services to provide trip planning functionality. • We use lat/lon to look up stops within max walk distance • Get departure times and trip IDs for nearby stops within time threshold • Find arrival times and stop IDs within the time threshold for theassociated trip IDs • This gives us a set of stops that are reachable within the max timethreshold, with a variable walk distance around each up to the maxtime, or max walk distance (whichever is lower).  We add a marker foreach stop.

  19. Behind the Scenes – Restaurant Finding Algorithm (custom function) • Easy way: Do a radius search for each stop.  But this is very slow. • So we compute a bounding box for the stops and do a singlecategory/box search on CityGrid, giving us a large result set. • We then iterate through each CityGrid result and see whether it iswithin the max walk radius of any of the stops.  If so we find theshortest path (walk + bus) to the location and then check whether the total trip time is within the threshold. • If the location is within the max trip time threshold and max walkdistance, we add it to the map.

  20. Behind the Scenes – Google Fusion Tables (custom function) • Restaurant density by zip code, number of restaurants by zip code, and LA City Parking Lots all hosted on Fusion Tables • We query fusion tables and bring the various layers onto the map

  21. Behind the Scenes – Google Forms • We create a Google Form and embed it on the site. • Once entered the form places a marker on the map

  22. Contribution to Transportation Planning More efficient trip-making • Destination Constraint: • Choosing the right mode for the destination • Example: Should I walk, drive, or take a bus? • Modal Constraint: • Choosing the destination based on the mode available • Example: I don’t have a car, but is there a bus?

  23. Contribution to Transportation Planning More efficient trip-making • Choosing high/low density restaurant “zones” (1/4-mile, or zip code) • Understanding the possibilities of the trip • Example: If I don’t like the restaurant I picked, do I have to travel far to find another one, or are there many in the “zone”?

  24. Happy Eating! Questions?

  25. Appendix • Project: topic, description, and functionalities • Who is it for, why is it useful, how are you implementing it • Relevancy to planning or related field • Diagrams: flowcharts, sketches and/or wireframes that describe the site’s planning process and functional flow • Team:  Description of roles and what each team member did • Evaluation:  what worked, what did not, what would you do if you had more time, what is the future of the project (if any) • Documentation: define the technical requirements: • User interaction • Custom functions • Custom layers

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