Camera-based Forward Collision and lane departure warning systems using SVM

This paper presents a unique camera-based Forward Collision Warning (FCW) and Lane Departure Warning (LDW) system to improve the safety of road vehicle transportation. The video used in the algorithm is captured by an in-car camera. Initially, a Support Vector Machine (SVM) classifier is applied to the first frame of the video to locate the moving vehicle of interest in front of the host vehicle. Following this step, two separate warning systems, namely FCW and LDW are designed. For the FCW, the Time to Collision (TTC) is determined through the scale change method, and the FCW system will be activated when TTC is less than a predefined threshold value. For the LDW system, the lane position information is analyzed and the warning is triggered if there is a lane departure without the use of blinkers. The proposed camera based system can provide advantages over the traditional radar/laser based warning systems, in which both the LDW and the FCW information cannot be provided with the same system. Furthermore, the proposed system provides additional flexibility at a lower cost.

[1]  Raja Sengupta,et al.  Cooperative Collision Warning: Enabling Crash Avoidance with Wireless Technology , 2005 .

[2]  Raymond J. Kiefer,et al.  Development of a Camera-Based Forward Collision Alert System , 2011 .

[3]  P A Hancock,et al.  Alarm effectiveness in driver-centred collision-warning systems. , 1997, Ergonomics.

[4]  Chengcui Zhang,et al.  Adaptive background learning for vehicle detection and spatio-temporal tracking , 2003, Fourth International Conference on Information, Communications and Signal Processing, 2003 and the Fourth Pacific Rim Conference on Multimedia. Proceedings of the 2003 Joint.

[5]  J.B. de Sousa,et al.  A control architecture for integrated cooperative cruise control and collision warning systems , 2001, Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228).

[6]  Christian Wallraven,et al.  Multi-class SVMs for Image Classification using Feature Tracking , 2002 .

[7]  Han-Shue Tan,et al.  DGPS-Based Vehicle-to-Vehicle Cooperative Collision Warning: Engineering Feasibility Viewpoints , 2006, IEEE Transactions on Intelligent Transportation Systems.

[8]  Joon Woong Lee,et al.  A Machine Vision System for Lane-Departure Detection , 2002, Comput. Vis. Image Underst..

[9]  Raja Sengupta,et al.  Cooperative Collision Warning Systems: Concept Definition and Experimental Implementation , 2006, J. Intell. Transp. Syst..

[10]  Huei Peng,et al.  Evaluation of automotive forward collision warning and collision avoidance algorithms , 2005 .

[11]  Qingfeng Huang,et al.  An adaptive peer-to-peer collision warning system , 2002, Vehicular Technology Conference. IEEE 55th Vehicular Technology Conference. VTC Spring 2002 (Cat. No.02CH37367).

[12]  C. Thorpe,et al.  Development of the side component of the transit integrated collision warning system , 2004, Proceedings. The 7th International IEEE Conference on Intelligent Transportation Systems (IEEE Cat. No.04TH8749).

[13]  Daniel V. McGehee,et al.  Collision Warning Timing, Driver Distraction, and Driver Response to Imminent Rear-End Collisions in a High-Fidelity Driving Simulator , 2002, Hum. Factors.