Name
Title | ||
|---|---|---|
Real time lane detection and tracking system evaluated in a hardware-in-the-loop simulator |
Abstract | ||
|---|---|---|
This paper presents a new real time lane detection and tracking system which succeeds in sharp curved roads. The Warp Perspective Mapping (WPM) method was used to change the video image perspective to top view. A two dimensional Gabor filter and vertical pixel density calculation method was used to find initial lane regions. Second derivative approach of Composite Bezier spline fitting method calculates the exact coordinates of the control points. Score function based on pixel matching was used for determining lanes in curved roads. A template lane matching method with ease of implementation was used for tracking the detected lanes. The proposed system was tested using offline and real time hardware-in-the-loop simulations. The detected and tracked lane information is used in a lane keeping control system, realized in a hardware-in-the-loop setting. The high fidelity, high order, realistic and nonlinear vehicle model in Carmaker HIL is used in hardware-in-the-loop testing. The lane keeping controller works as code in a dSpace microautobox general purpose electronic control unit which obtains the lane data from the vision system running on a laptop PC and Carmaker vehicle data from a dSpace compact simulator for calculating the required steering actions. The system performance was evaluated on different scenarios which contain straight and sharp curved roads, obstacle vehicles and different lane marking types. Average success rate is calculated as % 98.7. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/ITSC.2010.5625111 | ITSC |
Keywords | Field | DocType |
gabor filters,image matching,real-time systems,road vehicles,traffic engineering computing,video signal processing,bezier spline fitting method,gabor filter,wpm,hardware-in-the-loop simulator,hardware-in-the-loop testing,nonlinear vehicle model,real time lane detection,sharp curved roads,template lane matching method,tracking system evaluation,vertical pixel density calculation method,video image perspective,warp perspective mapping,hardware in the loop simulation,tracking system,real time systems,simulation,control system,feature extraction,vision system,mathematical model,hardware in the loop,fitting,system performance,computer vision,electronic control unit,curve fitting,digital maps,hardware in the loop testing,algorithms,pixel,intelligent transportation systems,score function,real time | Computer vision,Pixel density,Control theory,Machine vision,Simulation,Computer science,Tracking system,Electronic control unit,Hardware-in-the-loop simulation,Artificial intelligence,Pixel,Intelligent transportation system | Conference |
ISSN | ISBN | Citations |
2153-0009 | 978-1-4244-7657-2 | 6 |
PageRank | References | Authors |
0.73 | 6 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Coşkun, F. | 1 | 6 | 0.73 |
| Tunçer, O. | 2 | 6 | 0.73 |
| M. Elif Karsligil | 3 | 73 | 13.69 |
| Guvenc, L. | 4 | 6 | 0.73 |