2. Where to run?
● Solution: An app designing personalized
routes based on home address!
● Current recommendations: not
personalized; not based on home
address
4. Data source: streets data + features data
● OpenStreetMap: street network
4032 streets for running
● Boston Crime Incident Reports
18199 crime incidents with time
data in the last 3 years
5. Data source: streets data + features data
● OpenStreetMap: street network
4032 streets for running
● Boston Crime Incident Reports
Morning Evening
6. Challenge: balance between the performance and the efficiency
● Alternative way:
intermediate destinations
…...
● An exhaustive search: too many
routes for a long distance!
7. Incorporate cost functions to find the optimum path
● Example: Re-treading routes
Crime (based on time)
+
Preference to path?
+
Length
+
Re-treading?
More re-
treading
Less re-
treading
● Features in cost function
12. Cost function used
d: distance of the way segment
N: number of events
S: user’s sensitivity
F: scaling factor
cr: crime
re: re-treading
Editor's Notes
As safety is the major concern, crime is firstly incorporated. The data is classified into 4 groups based on time of the day, to estimate the safety of running route based on time chosen.
Equilateral triangle with side length related to input distance
