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 language | English |
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| Title of host publication | 20th ITS World Congress Tokyo 2013 |
| Publisher | Intelligent Transportation Society of America |
| Publication status | Published - 2013 |
| Event | 20th Intelligent Transport Systems World Congress, ITS 2013 - Tokyo, Japan Duration: 2013 Oct 14 → 2013 Oct 18 |
Other
| Other | 20th Intelligent Transport Systems World Congress, ITS 2013 |
|---|---|
| Country/Territory | Japan |
| City | Tokyo |
| Period | 13/10/14 → 13/10/18 |
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