Slides contains how AI is making Uber service better

1. By Prashant Poudel

2. What is uber?

3. Food Delivery
Ride Sharing
Cargo Shipping
Package Delivery
What is uber?

4. Garrett Camp
2007
Started in
Travis Kalanick
93M
Monthly active users worldwide
600Cities
80Countries
5B+Rides

6. Why use AI?

7. Why use AI?
ETA (Minimize Time of Arrival)
Effective Pricing
Better Customer Service
Route optimization
Uber Pool

8. Predicting ETAs

9. Predicting ETAs
To bring reliable transportation to
everyone, everywhere.
Reliable ► Predicted ETA = Actual ETA

10. Predicted ETA
Map Data
Actual ETA
Predicting ETAs
Error

11. Map Data
Actual ETA
Predicting ETAs
Routing
Traffic
Machine Learning
Predicted ETA

12. Routing
Routing Algorithms
Large scale, low-latency serving

13. Problem Statement
Compute route from origin to
destination with least cost.
And estimate time taken to traverse the
route.

14. Graph Representation

15. Dijkstra’s Algorithm
Nlogn

16. Partitioning Algorithm
N’logn’ N’logn’ N’logn’

17. Map Data
Actual ETA
Predicting ETAs
Routing
Traffic
Machine Learning
Predicted ETA

18. Traffic
Traffic = f (Traversal information on road
segments)
Traversal = f (time, weather,….)
More traversal ► accurate traffic

19. GPS data on road segment
Real time speeds
SpeedAB = AB/(TA - TB)
Traffic Modeling
A
B

20. Traffic in Routing
High traffic Medium traffic Low traffic

21. Traffic in Routing
High traffic Medium traffic Low traffic
How long is (RT) real-
time traffic valid?
How do we combine
historical data with RT
traffic?

22. Map Data
Actual ETA
Predicting ETAs
Routing
Traffic
Machine Learning
Predicted ETA

23. Machine Learning
Calculate more realistic ETAs
Machine learning captures variability
in Region, Time, Trip type, Driver
Behavior etc.

24. Map Data
Actual ETA
Predicting ETAs
Routing
Traffic
Machine Learning
Predicted ETA

25. Self-Driving Vehicles with Uber

26. Self-Driving Vehicles
with Uber
Perception
Prediction
Motion Planning

28. Perception

29. Prediction

32. Self-Driving & Future

33. Self-Driving &
Future
Prevention of car crashes
Traffic efficiency
Better access & mode of
transportation
Environment friendly
(Positive)

34. Self-Driving &
Future (Negative)
Security Issue
Job losses
Initial Cost
Machine Error

35. Thank You