Staten Island residents face significant problems in terrible delays in the express bus routes. The average durations of some of the trips such as X109 can be upwards of 3 hours with a variability (standard deviation) of +/- 1 hour. This brings significant hardship to the people of Staten Island. Lets use actual data to understand the problem and inspire a solution.
What was done
Understand the problem using real data and identify key observations. THe slides in the link below and the cartodb maps below would provide the details.
This map talks to the number of people who get off the bus in specific stops. The more intense the color, the more people who get off. https://kskk02.cartodb.com/viz/39312cd8-e30c-11e5-a504-0ecd1babdde5/public_map
This map overlays 3 different dimensions of information in a single map. 1) Census bus commuter population density 2) Bus routes 3) Degree of ridership as defined as Ons + Offs represented by the thickness of the bus route. (Note that another subtle dimension is the degree of overlapping routes as represented by the intensity of the route color since the more intense, the more overlap in routes) https://kskk02.cartodb.com/viz/0c783a30-e2fb-11e5-8842-0e787de82d45/public_map
How I built it
Cartodb with tons of real public data that was merged to find these observations.
Challenges I ran into
Merging the data, filtering the data. Understanding the domain and what the data was telling me.