Improving Fuzzy-Logic based Map-Matching Method with Trajectory Stay-Point Detection

Transcript

1. Improving Fuzzy-Logic based Map-Matching Method with Trajectory Stay-Point Detection Authors: Minoo Jafarlou, Omid Mahdi Ebadati, and Hassan Naderi
2. Introduction —  Moving object databases have some irregularity, we need to preprocess the trajectory —  Vehicle GPS trajectory datasets include stay-points abnormality, which defines as noise in dataset —  Stay-points make matching algorithms mismatch trajectories to irrelevant roads
3. The map-matching process
4. Fuzzy-logic system blocks
5. Initial map-matching
6. Subsequent map-matching 1 (SMP1) ​θ↑′  is the vehicle's direction at previous point. Δd is d−d1. Abs (θ−​θ↑′ ) is heading increment.
7. Subsequent map-matching 2 (SMP2) d is the traveled distance by vehicle, d2= AO+OM, d3= AO+ON, d4= AO+OO’+OQ
8. Pseudo-code for fuzzy map-matching algorithm
9. Map-matching process
10. Different density levels
11. Stay-Point sample
12. Stay-Point •  Stay-point region misleads the map-matching process
13. Digital road network and tested GPS trajectory
14. Proposed method follow-chart
15. Three nearest neighbor distance curves
16. Number of clustered and non-clustered points for different epsilons
17. Clustered stay-points data with DBSCAN
18. Accuracy performance evaluation •  Number of correct links detected among 399 links
19. Time efficiency evaluation •  Overall processing time comparison between two approaches
20. Volume efficiency evaluation •  The proposed approach decreased the data volume
21. Speed efficiency evaluation •  Average execution time speed for each point is calculated
22. Map-matching sample on the dataset
23. References —  [1] Jafarlou, Minoo, Omid Mahdi Ebadati E, and Hassan Naderi. "Improving Fuzzy-Logic based Map- Matching Method with Trajectory Stay-Point Detection." arXiv e-prints (2022): arXiv-2208. —  [2] Schubert, Erich, et al. "DBSCAN revisited, revisited: why and how you should (still) use DBSCAN." ACM Transactions on Database Systems (TODS) 42.3 (2017): 1-21. —  [3] Quddus, Mohammed A., Robert B. Noland, and Washington Y. Ochieng. "A high accuracy fuzzy logic based map matching algorithm for road transport." Journal of Intelligent Transportation Systems 10.3 (2006): 103-115.