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High Definition Corridor Mapping From Images Sequences
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Author(s): Mert Gurturk (Yildiz Technical University, Turkey), Yalçın Yılmaz (Yildiz Technical University, Turkey), Baris Suleymanoglu (Yildiz Technical University, Turkey), Arzu Soycan (Yildiz Technical University, Turkey)and Metin Soycan (Yildiz Technical University, Turkey)
Copyright: 2020
Volume: 9
Issue: 1
Pages: 14
Source title:
International Journal of Digital Innovation in the Built Environment (IJDIBE)
Editor(s)-in-Chief: Jason Underwood (University of Salford, United Kingdom), Sisi Zlatanova (University of New South Wales, Sydney, Australia)and Umit Isikdag (Mimar Sinan Fine Arts University, Turkey)
DOI: 10.4018/IJDIBE.2020010102
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Abstract
The density, high accuracy, and rapid collection of geographical data for road surface and surrounding objects and the extraction of meaningful information from these data increases its importance in line with technological developments. Artificial intelligence studies and developments in cloud technology have affected the automotive industry as well as every sector and have enabled the development of driverless vehicle technology. In order to safely drive with autonomous vehicles, high definition maps that contain detailed information for road surface and its surrounding objects with high precision at centimeter-level must be used. In this context, in recent years, the development of mobile mapping systems (MMS) consisting of low-cost sensors and the development of algorithms for the evaluation of the data obtained from these systems have become increasingly popular. In this study, it was investigated whether HD maps can be obtained by using low-cost imaging sensors.
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