Abstract
This paper presents algorithms for vision-based monitoring of weaving sections. These algorithms have been developed for the Minnesota Department of Transportation in order to acquire data for several weaving sections in the Twin Cities area. Unlike commercially available systems, the proposed algorithms can track and count vehicles as they change lanes. Furthermore, they provide the velocity and the direction of each vehicle in the weaving section. Experimental results from various weaving sections under various weather conditions are presented. The proposed methods are based on the establishment of correspondences among blobs and vehicles as the vehicles move through the weaving section. The blob tracking problem is formulated as a bipartite graph optimization problem.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 18-25 |
| Number of pages | 8 |
| Journal | IEEE Transactions on Intelligent Transportation Systems |
| Volume | 2 |
| Issue number | 1 |
| DOIs | |
| State | Published - Mar 2001 |
Bibliographical note
Funding Information:Dr. Masoud is a recipient of a Research Contribution Award from the University of Minnesota, the Rosemount Instrumentation Award from Rosemount Inc., and the Matt Huber Award for Excellence in Transportation Research.
Funding Information:
Manuscript received March 7, 2000; revised July 10, 2000 and September 1, 2000. This work was supported by the ITS Institute, University of Minnesota, the Minnesota Department of Transportation under Contract MNDOT/74708-W.O. 14, the Center for Transportation Studies under Contract USDOT/DTRS 93-G-0017-01, and the National Science Foundation under Contracts IRI-9410003 and IRI-9502245.
Keywords
- Vehicle detection
- Vision-based vehicle tracking
- Weaving sections