International Conference on Advances in Computation, Communications and Services (ACCSE) 2018, pp.46-48
Language
English
Type
Conference Paper
Abstract
This paper describes an inference engine used in a system and semantic representation for the system which automatically adjusts the positions of vehicle parts based on rules. The inference engine has rules stored in a knowledge base, which describe the relation between the position of the vehicle part and the driver’s body size. The inference engine receives the driver’s body sizes in real time, and finds a rule associated with the input values by matching a pattern between them. According to the value defined in the rule, the position of the vehicle part is changed automatically. This rule is automatically modified by learning the relation between the driver’s preferred position and body size. The number of selected rules and reasoning time are selected as performance indicators of the inference engine. Also, an ontology is designed to share the development results with others. Automated vehicle parts control system can be used as a method that improves the driver’s satisfaction by automatically recommending the driver’s preferred position in an environment where many unknown people use the same vehicle like a shared car or a rental car.
KSP Keywords
Automated vehicles, Body size, Control system, Inference engine, Knowledge Base, Performance indicators, Real-time, Semantic Representation, vehicle part
Copyright Policy
ETRI KSP Copyright Policy
The materials provided on this website are subject to copyrights owned by ETRI and protected by the Copyright Act. Any reproduction, modification, or distribution, in whole or in part, requires the prior explicit approval of ETRI. However, under Article 24.2 of the Copyright Act, the materials may be freely used provided the user complies with the following terms:
The materials to be used must have attached a Korea Open Government License (KOGL) Type 4 symbol, which is similar to CC-BY-NC-ND (Creative Commons Attribution Non-Commercial No Derivatives License). Users are free to use the materials only for non-commercial purposes, provided that original works are properly cited and that no alterations, modifications, or changes to such works is made. This website may contain materials for which ETRI does not hold full copyright or for which ETRI shares copyright in conjunction with other third parties. Without explicit permission, any use of such materials without KOGL indication is strictly prohibited and will constitute an infringement of the copyright of ETRI or of the relevant copyright holders.
J. Kim et. al, "Trends in Lightweight Kernel for Many core Based High-Performance Computing", Electronics and Telecommunications Trends. Vol. 32, No. 4, 2017, KOGL Type 4: Source Indication + Commercial Use Prohibition + Change Prohibition
J. Sim et.al, “the Fourth Industrial Revolution and ICT – IDX Strategy for leading the Fourth Industrial Revolution”, ETRI Insight, 2017, KOGL Type 4: Source Indication + Commercial Use Prohibition + Change Prohibition
If you have any questions or concerns about these terms of use, or if you would like to request permission to use any material on this website, please feel free to contact us
KOGL Type 4:(Source Indication + Commercial Use Prohibition+Change Prohibition)
Contact ETRI, Research Information Service Section
Privacy Policy
ETRI KSP Privacy Policy
ETRI does not collect personal information from external users who access our Knowledge Sharing Platform (KSP). Unathorized automated collection of researcher information from our platform without ETRI's consent is strictly prohibited.
[Researcher Information Disclosure] ETRI publicly shares specific researcher information related to research outcomes, including the researcher's name, department, work email, and work phone number.
※ ETRI does not share employee photographs with external users without the explicit consent of the researcher. If a researcher provides consent, their photograph may be displayed on the KSP.