An Efficient Algorithm for Forward Collision Warning Using Low Cost Stereo Camera & Embedded System on Chip

  • Manoj Rajan Tata Consultancy Services
  • Prabhudev Patil
  • Sravya Vunnam
Keywords: ADAS, FCW, NCAP, HOG, radar, camera sensor, vision, stereo matching, sub-pixel interpolation

Abstract

Forward Collision Warning (FCW) systems in automobiles provide alerts to assist drivers in avoiding the rear-side crashes. These devices currently use, radars as the main sensor. The increasing resolution of imaging sensors, processing capability of hardware chipsets and advances in machine vision algorithms, have pushed ahead the camera-based features. This paper discusses about a stereo camera-based FCW algorithm that uses a pair of cameras for sensing forward collision situations. Stereo camera based devices overcomes the disadvantages of using single camera for distance measurements and at the same time with lesser cost compared to radar sensors. This paper provides an overview of the system, sensors used, and details including novel state of the art algorithms that detects vehicles and calculates distance from it, and how the algorithms are designed to be affordable for low cost multi core embedded hardware platform meeting stringent real time performance parameters. Novel, Enhanced Histogram of Gradients algorithm detects the presence of vehicle at different scales and postures. Highly efficient stereo matching algorithm which operates at dynamic sub-pixel level granularity provides accurate depth which helps to predict the time for collision accurately. Long testing proves that system would meet the New Car Assessment Program test requirements

References

(1) Pre-Crash Scenario Typology for Crash Avoidance Research. National Highway Transportation Safety Administration. - Najm, W.G., Smith, J.D., and Yanagisawa, M.

(2) Development and validation of functional definitions and evaluation procedures for collision warning/avoidance systems. Highway Transportation Safety Administration. - Kiefer, R., LeBlanc, D., Palmer, M., Salinger, J., Deering, R., and Shulman, M.

(3) Histogram of Oriented Gradients (HOG) for Object Detection -Navneet Dalal and Bill Triggs

(4) FORWARD COLLISION WARNING SYSTEM CONFIRMATION TEST, February 2013 - US Department of Transportation

(5) Empowering automotive vision with TI’s Vision Acceleration Pac – Texas Instruments

Published
2016-03-11