Vol. 14, No. 10, October 31, 2020
10.3837/tiis.2020.10.002,
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Abstract
Due to the significant increase in the use of autonomous car technology, it is essential to
integrate this technology with high-precision digital map data containing more precise and
accurate roadway information, as compared to existing conventional map resources, to ensure
the safety of self-driving operations. While existing map technologies may assist vehicles in
identifying their locations via Global Positioning System, it is however difficult to update the
environmental changes of roadways in these maps. Roadway vision algorithms can be useful
for building autonomous vehicles that can avoid accidents and detect real-time location
changes. We incorporate a hybrid architectural design that combines unsupervised
classification of vision data with supervised joint fusion classification to achieve a better
noise-resistant algorithm. We identify, via a deep learning approach, an intelligent hybrid
fusion algorithm for fusing multimodal vision feature data for roadway classifications and
characterize its improvement in accuracy over unsupervised identifications using image
processing and supervised vision classifiers. We analyzed over 93,000 vision frame data
collected from a test vehicle in real roadways. The performance indicators of the proposed hybrid fusion algorithm are successfully evaluated for the generation of roadway digital maps
for autonomous vehicles, with a recall of 0.94, precision of 0.96, and accuracy of 0.92.
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Cite this article
[IEEE Style]
J. Jung, M. Park, K. Cho, C. Mun, J. Ahn, "Intelligent Hybrid Fusion Algorithm with Vision Patterns for Generation of Precise Digital Road Maps in Self-driving Vehicles," KSII Transactions on Internet and Information Systems, vol. 14, no. 10, pp. 3955-3971, 2020. DOI: 10.3837/tiis.2020.10.002.
[ACM Style]
Juho Jung, Manbok Park, Kuk Cho, Cheol Mun, and Junho Ahn. 2020. Intelligent Hybrid Fusion Algorithm with Vision Patterns for Generation of Precise Digital Road Maps in Self-driving Vehicles. KSII Transactions on Internet and Information Systems, 14, 10, (2020), 3955-3971. DOI: 10.3837/tiis.2020.10.002.
[BibTeX Style]
@article{tiis:23914, title="Intelligent Hybrid Fusion Algorithm with Vision Patterns for Generation of Precise Digital Road Maps in Self-driving Vehicles", author="Juho Jung and Manbok Park and Kuk Cho and Cheol Mun and Junho Ahn and ", journal="KSII Transactions on Internet and Information Systems", DOI={10.3837/tiis.2020.10.002}, volume={14}, number={10}, year="2020", month={October}, pages={3955-3971}}