The analytics underlying onTimeTravlr.com

1. ononTimeTravlrTimeTravlr
Simon GélinasSimon Gélinas
Because everyone loves getting stuck in trafficBecause everyone loves getting stuck in traffic

2. 173 million taxi entries173 million taxi entries (~30gb) - Chris Whong FOIL(~30gb) - Chris Whong FOIL
Traffic data for ~1500 street segmentsTraffic data for ~1500 street segments - NYC open data- NYC open data
Raw data on
Google BigQuery
Clean up
Extract patterns
Anomaly detection

3. Traffic Data:Traffic Data: Finding the underlying patternsFinding the underlying patterns
using singular value decomposition (SVD)using singular value decomposition (SVD)
RoadID#
Extremely strong within-week
correlation!
Mon
Tue
Wed
Thu
Fri
Sat
Sun
Mon - Tue - Wed - Thu - Fri - Sat - Sun

4. Reconstructed Geodata - TimeseriesReconstructed Geodata - Timeseries
Fast and accurate solution for websiteFast and accurate solution for website
Google map prediction

5. Scientific work published in: Nature (2013), Science (2014), Nature Materials (2014)
Simon GélinasSimon Gélinas

6. Aggregated seasonal trendsAggregated seasonal trends

7. Traffic speed vs car densityTraffic speed vs car density
not very linear!not very linear!
Few cars → lots of cars
Fast→Slow

8. Traffic Data:Traffic Data: Position of Road ID #Position of Road ID #
Road ID #
Mon
Tue
Wed
Thu
Fri
Sat
Sun

14. TEMPLATE: main pointTEMPLATE: main point
some detailssome details