抄録
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.
本文言語 | English |
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ホスト出版物のタイトル | 20th ITS World Congress Tokyo 2013 |
出版社 | Intelligent Transportation Society of America |
出版ステータス | Published - 2013 |
イベント | 20th Intelligent Transport Systems World Congress, ITS 2013 - Tokyo, Japan 継続期間: 2013 10 14 → 2013 10 18 |
Other
Other | 20th Intelligent Transport Systems World Congress, ITS 2013 |
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Country | Japan |
City | Tokyo |
Period | 13/10/14 → 13/10/18 |
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