On the image sensor processing for lane detection and control in vehicle lane keeping systems

C. Y. Kuo, Y. R. Lu, S. M. Yang

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

Lane keeping systems for a keeping a vehicle in the desired lane is key to advanced driving assistance system in autonomous vehicles. This paper presents a cost-effective image sensor with efficient processing algorithm for lane detection and lane control applications to autonomous delivery systems. The algorithm includes (1) lane detection by inverse perspective mapping and random sample consensus parabola fitting and (2) lane control by pure pursuit steering controller and classical proportional integral speed controller based on a nonholonomic kinematic model. The image sensor experiments conducted on a 1/10 scale model car maneuvering in a straight–curve–straight lane validate the better processing performance before, during, and after the turning section over previous work. The image sensor with the processing algorithm achieves the average lane detection error within 5% and maximum cross-track error within 9% in real-time. The development shall pave the way to cost-effective autonomous delivery systems.

Original languageEnglish
Article number1665
JournalSensors (Switzerland)
Volume19
Issue number7
DOIs
Publication statusPublished - 2019 Apr 1

All Science Journal Classification (ASJC) codes

  • Analytical Chemistry
  • Biochemistry
  • Atomic and Molecular Physics, and Optics
  • Instrumentation
  • Electrical and Electronic Engineering

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