Design and development of a computer-assisted Road Physical Feature Extraction (RFEX)

Clicks: 1
ID: 285510
2023
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal

Ranked #3,104 of 3,757 articles by views in Malay Journal

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 3,757 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract
The concept of livability plays a crucial role in urban planning, development, and maintenance. Analyzing and interpreting physical road features is essential for assessing the livability of an area. However, there is currently no existing database available that contains the road physical features of Metro Manila. To address this gap, the proposed Computer-Assisted Road Physical Feature Extraction System (RFEX) aims to create a database of road characteristics. The system focuses on detecting road physical features, including the presence of road lanes, bike lanes, sidewalks, fences, obstructions and constructions. The system incorporates modules for lane detection and object detection, along with a user-friendly website. The core object detection of the system achieved an average precision, recall, and mAP of 0.72, 0.46, and 0.52, respectively. For both bike lane detection and road lane counting, the average accuracy achieved 0.64, and the average mean absolute error achieved 0.37, respectively, by utilizing the unit factor k=1 in median absolute deviation. Our proposed work provided a computer vision approach to detecting bike lines and counting road lanes as well as developing a system capable of storing and visualizing the extracted road physical features. By establishing this, people can gain valuable insights regarding road infrastructures.
Reference Key
persistent_1760655818_68f179ca37203 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Noroña, Yeohan Lorenzo M.
Journal Malay Journal
Year 2023
DOI
DOI not found
URL
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.