Cognitive vision for driving environment categorization using network-type fusion

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

For the next-generation automotive technology in advanced driver assistance systems, it is important that automobile itself understands driving environments autonomously. Therefore, we have been examining a type of cognitive vision system which categorizes the driving environments using an on-board vision system. Our approach is not the environment categorization by the complicated image processing, but by the network state from simple image processing modules. We modularize some simple image processing methods and make a fusion network by mutual evaluation between these modules from immune network point of view. Then, we associate the network state and the driving environment. In this paper, we show the validity of this proposed method by interpretation of a preceding vehicle lane change as an example of an experiment.

Original languageEnglish
Title of host publication20th ITS World Congress Tokyo 2013
PublisherIntelligent Transportation Society of America
Publication statusPublished - 2013
Event20th Intelligent Transport Systems World Congress, ITS 2013 - Tokyo, Japan
Duration: 2013 Oct 142013 Oct 18

Other

Other20th Intelligent Transport Systems World Congress, ITS 2013
CountryJapan
CityTokyo
Period13/10/1413/10/18

Keywords

  • Categorization
  • Cognitive vision
  • Immune network

ASJC Scopus subject areas

  • Artificial Intelligence
  • Automotive Engineering
  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Transportation
  • Computer Networks and Communications
  • Computer Science Applications

Fingerprint Dive into the research topics of 'Cognitive vision for driving environment categorization using network-type fusion'. Together they form a unique fingerprint.

Cite this