Vehicle Braking Performance Improvement By SVM Based Road Surface Detection
Author : T. Anbalagan, C. Gowrishankar and A. ShanmugamVolume 2 No.2 July-December 2013 pp 14-21
Abstract
Advance information about the road surface a vehicle is going to encounter can improve the performance of Antilock Braking System (ABS). For e.g. the initial slip cycles caused by the ABS could be avoided, if it is already known that the vehicle is on a surface having a low coefficient of friction (μ). In this paper, an algorithm is developed that detects different road surfaces using streaming video acquired from a camera mounted on the hood of the vehicle. The road surfaces detected here are asphalt road, cement road, sandy road, rough asphalt road (asphalt road which is deteriorating), grassy road and rough road. The value of coefficient of friction (μ) is also given out with the detected surfaces to obtain additional information about the road surfaces. Split μ (a road having different μ conditions on the left and right side of the vehicle) and μ jump (different μ conditions on the front and rear of the vehicle) are also pre detected. One method was not sufficient to achieve the goals of this algorithm. Here several simple techniques like the Canny edge algorithm, intensity histogram, contours, Hough transform and image segmentation were employed and compared with the Support Vector Machine (SVM). To prevent misdetections, the road surface detection during high motion blur is prohibited.
Keywords
Computer vision; Vehicle dynamics; Vehicle safety system; Signal processing; Automotive systems; Electronics in industry and transport