Probabilistic lane detection and lane tracking for autonomous vehicles using a cascade particle filter

Abstract

This paper proposes a robust lane detection algorithm with a cascade particle filter that incorporates a model decomposition approach. Despite the sophisticated tracking mechanism of a particle filter, the conventional particle-filter-based lane detection system suffers from an estimation accuracy problem and a high computational load. In order to improve the robustness and the computation time for lane detection systems, the proposed cascade particle filter decomposes a lane model into two submodels: a straight model and a curve model. By dividing the lane model, not only can the computation time be decreased, but also the accuracy of the lane state estimation system can be increased. The proposed lane detection algorithm and the cascade particle filter were evaluated on various roads and environmental conditions with the autonomous vehicle A1, which was the winner of the 2010 and 2012 Autonomous Vehicle Competition in the Republic of Korea organized by the Hyundai motor group. The proposed algorithm proved to be sufficiently robust and fast to be applied to autonomous vehicles as well as to intelligent vehicles for improving the vehicle safety.

Keywords

Lane detection cascade particle filtering tracking autonomous vehicle

Get full access to this article

View all access options for this article.

References

NHTSA. National motor vehicle crash causation survey. Report DOT HS 811 059, US Department of Transportation, National Highway Traffic Safety Administration, Washington, DC, USA, 2008.

Chu

Sunwoo

Interacting multiple model filter-based sensor fusion of gps with in-vehicle sensors for real-time vehicle positioning. IEEE Trans Intell Transpn Systems 2012; 13: 329–343.

Wang

Libin Zhao

. A vision-based road edge detection algorithm. In: 2002 IEEE intelligent vehicles symposium, Versailles, France, 17–21 June 2002, Vol 1, pp. 141–147. New York: IEEE.

Lopez

Serrat

Canero

. Robust lane markings detection and road geometry computation. Int J Automot Technol 2010; 11: 395–407.

Cafiso

Di Graziano

Di Silvestro

. Development of comprehensive accident models for two-lane rural highways using exposure, geometry, consistency and context variables. Accid Analysis Prevention 2010; 42: 1072–1079.

Bertozzi

Bombini

Broggi

. VIAC: an out of ordinary experiment. In: 2011 IEEE intelligent vehicles symposium, Baden-Baden, Germany, 5–9 June 2011, pp. 175–180. New York: IEEE.

Pohl

Birk

Westervall

A driver-distraction-based lane-keeping assistance system. Proc IMechE Part I: J Systems and Control Engineering 2007; 221: 541–552.

Shin

D-H

Joo

B-Y.

Design of a vision-based autonomous path-tracking control system and experimental validation. Proc IMechE Part D: J Automobile Engineering 2010; 224(7): 849–864.

Shim

Adireddy

Yuan

Autonomous vehicle collision avoidance system using path planning and model-predictive-control-based active front steering and wheel torque control. Proc IMechE Part D: J Automobile Engineering 2012; 226(6): 767–778.

10.

Bertozzi

Broggi

GOLD: a parallel real-time stereo vision system for generic obstacle and lane detection. IEEE Trans Image Processing 1998; 7: 62–81.

11.

Bertozzi

Broggi

Fascioli

VisLab and the evolution of vision-based UGVs. Computer 2006; 39: 31–38.

12.

Broggi

Cappalunga

Caraffi

. TerraMax vision at the urban challenge 2007. IEEE Trans Intell Transpn Systems 2010; 11: 194–205.

13.

Cerri

Soprani

Zani

. Computer vision at the Hyundai Autonomous Challenge. In: 2011 14th international IEEE conference on intelligent transportation systems, Washington, DC, USA, 5–7 October 2011, pp. 777–783. New York: IEEE.

14.

Sehestedt

Kodagoda

Alempijevic

Dissanayake

. Efficient lane detection and tracking in urban environments. In: 3rd European conference on mobile robots, Freiburg, Germany, 19–21 September 2007, pp. 126–131. Freiburg: University of Freiburg.

15.

Jiang

Reinhard

Tobi

Wang

Lane detection and tracking using a new lane model and distance transform. Mach Vision Applic 2011; 22: 721–737.

16.

Danescu

Nedevschi

Meinecke

. Lane geometry estimation in urban environments using a stereovision system. In: 2007 IEEE Intelligent transportation systems conference, Seattle, Washington, USA, 30 September–3 October 2007, pp. 271–276. New York: IEEE.

17.

Tian

Liu

. Single camera 3D lane detection and tracking based on EKF for urban intelligent vehicle. In: 2006 IEEE International conference on vehicular electronics and safety, Beijing, People’s Republic of China, 30 September–3 October 2006, pp. 413–418. New York: IEEE.

18.

Borkar

Hayes

Smith

. Robust lane detection and tracking with RANSAC and Kalman filter. In: 2009 16th IEEE international conference on image processing, Cairo, Egypt, 7–10 November 2009, pp. 3261–3264. New York: IEEE.

19.

Vacek

Schimmel

Dillmann

. Road-marking analysis for autonomous vehicle guidance. In: 3rd European conference on mobile robots, Freiburg, Germany, 19–21 September 2007, pp. 1–6. Freiburg: University of Freiburg.

20.

Danescu

Nedevschi

Probabilistic lane tracking in difficult road scenarios using stereovision. IEEE Trans Intell Transpn Systems 2009; 10: 272–282.

21.

Dickmanns

Mysliwetz

. Recursive 3-D road and relative ego-state recognition. IEEE Trans Pattern Analysis Mach Intell 1992; 14: 199–213.

22.

Ristic

Arulampalam

Gordon

Beyond the Kalman filter – particle filters for tracking applications. Norwood, Massachusetts: Artech House, 2004.

23.

Thrun

Burgard

Fox

Probabilistic robotics. Cambridge, Massachusetts: The MIT Press, 2005.

24.

Han

Kim

Lee

Sunwoo

Enhanced road boundary and obstacle detection using a downward-looking LIDAR sensor. IEEE Trans Veh Technol 2012; 61: 971–985.

25.

Park

Sunwoo

FlexRay network parameter optimization method for automotive applications. IEEE Trans Ind Electron 2011; 58: 1449–1459.

26.

Lee

. Probabilistic lane detection and tracking for autonomous vehicles using a cascade particle filter, https://www.youtube.com/watch?v=azkoJMGIZEI&feature=youtu.be (2012).