1. Mining Regular Routes from GPS Data for Ridesharing Recommendations Wen He, Deyi Li, Tianlei Zhang, Lifeng An, Mu Guo, and Guisheng Chen Tsinghua University Chinese Institute of Electronic System Engineering August 12, 2012

2. Regular Route A regular route is a complete route which often happen at a similar time Commute route pick up children each day … 2

3. Outline Introduction Architecture Details of solution Experiments results Conclusion 3

4. Background Traffic congestion has become a worldwide problem Low vehicle occupancy RideSharing becomes an attractive way to relieve traffic pressure 4

5. Challenges in Ridesharing Complexity “Stranger danger” Reliability 5 driver rider

6. Our Work Mining Regular Routes from GPS Data for Ridesharing Recommendations Common method Complexity “Stranger danger” Reliability Our method Automatic matching Traveled regularly for a period of time More information from GPS logs 6 Vs.

7. Challenges Uncertainty in time property Start at different time Complexity in traffic condition Multiple transportation mode Private driving Public transportation Uncertainty in route sequence GPS signal drift Obstacle in the road 7

8. Database-based User- based Architecture 8

9. Routes Processing 9 A fragment of GPS Log tctc tata tbtb tdtd Route 1 Route 2 Route 3 T thresh Stay region

10. Routes Grouping 10 One user’s routes during one month

11. Frequent Directed Edges (FDE) Finding DE.fre> f threh  FDE 11

12. One simple example --- FDEs finding 12 AM->AN 2 AM->BM 1 AN->BN 3 BM->CM 2 BN->CN 3 CM->DM 2 CN->CO 1 CN->DN 2 CO->CP 3 CP->DP 3 DM->EM 2 DN->DO 2 …

13. Regular Routes Finding 13 Route: If most of its DEs are FDEs  a candidate of an RR f c (R) = m/n n ： number of DEs in R m ： number of FDEs in R FDE: If most of its support routes are candidate routes  part of an RR (RFDE) Regular route: a link of RFDEs

14. Mining Travel Modes of Regular Routes Feature of Fixed Stop Rate (FSR) Stop rate: number of points with low velocity [Zheng,Ubicomp 2008] ( accuracy: 0.6) Stop region: a user usually passed this region with a low velocity Fixed stop rate: the number of stop regions in a route 14

15. Ridesharing recommendations 15

16. Experiments Testing Data (from Geolife project*) 178 users‘ real logs from 2007 to 2011 17+thousand trajectories 48+ thousand hours 1+ million kilometers the majority of the data was created in Beijing, China. * http://research.microsoft.com/en-us/downloads/b16d359d-d164-469e-9fd4-daa38f2b2e13/default.aspx 16

17. Results on Regular route mining 17

18. All regular routes from Testing Data 18

19. Some results in ridesharing recommendations 19

20. Conclusion A method for ridesharing recommendations Finding more opportunities from GPS data Giving more reliability of the ride Providing more information about the riders and the routes An algorithm for Mining regular routes Distinguishing regular routes from frequent routes Calculating the similarity of a group of routes A feature for Distinguish private driving and public transportation 20

21. Thank you! Wen He he-w09@mails.tsinghua.edu.cn 21