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An Ontology-Based Recommendation System for ADAS Design

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Genetic and Evolutionary Computing (ICGEC 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 834))

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Abstract

Advanced driver-assistance systems (ADAS) are an important component in a vehicle for these systems to actively improve driving safety. Although technical development for ADAS is already mature, there are still a few areas that can be improved. In particular, the design of newer ADASs are mainly based on the experience and imagination of car designers and their tests are usually based on hypothetical situations and field models. Without user experience data, it is difficult for car makers to refine and improve their ADAS designs effectively and systematically. In order to help designers optimize their designs and shorten design cycles, a framework of collaborative filtering recommendation is proposed, in which domain ontologies, text mining, and machine learning techniques are used to produce multimedia summaries from data repositories for queries of real accidents, or design issues. The recommendation system framework aims to help designers and car makers improve their efficiency and produce safer vehicles. The data and knowledge bases constructed can be used as the basis of tutorial programs for new entrants and the car makers can reduce their managerial cost and manpower needs.

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Acknowledgements

This work is supported by Top-notch Academic Programs Project of Jiangsu Higher Education Institutions (TAPP) under Grant No. PPZY2015A090.

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Authors and Affiliations

  1. Tajen University, No. 20, Weixin Rd., Yanpu Township, Pingtung County, 90741, Taiwan, ROC

    Hsun-Hui Huang

  2. National Taitung University, Taitung City, Taiwan, ROC

    Horng-Chang Yang

  3. School of Software, Changzhou College of Information Technology, Changzhou, China

    Yongjia Yu

Authors
  1. Hsun-Hui Huang
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  2. Horng-Chang Yang
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  3. Yongjia Yu
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Corresponding author

Correspondence to Hsun-Hui Huang .

Editor information

Editors and Affiliations

  1. Fujian Provincial Key Laboratory of Big Data Mining and Applications, Fujian University of Technology, Fuzhou, Fujian, China

    Jeng-Shyang Pan

  2. Department of Computing, Mathematics, and Physics, Western Norway University of Applied Sciences, Bergen, China

    Jerry Chun-Wei Lin

  3. Changzhou College of Information Technology, Changzhou, Jiangsu, China

    Bixia Sui

  4. College of Smart Living and Management, Tajen University, Pingtung, Taiwan

    Shih-Pang Tseng

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Huang, HH., Yang, HC., Yu, Y. (2019). An Ontology-Based Recommendation System for ADAS Design. In: Pan, JS., Lin, JW., Sui, B., Tseng, SP. (eds) Genetic and Evolutionary Computing. ICGEC 2018. Advances in Intelligent Systems and Computing, vol 834. Springer, Singapore. https://doi.org/10.1007/978-981-13-5841-8_71

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