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An evaluation of stereo vision for distance estimation using the SGBM algorithm in the CARLA simulator.

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Title: An evaluation of stereo vision for distance estimation using the SGBM algorithm in the CARLA simulator.
Authors: Sakti, Rizky Hamdani1 rizkyhamm@upi.edu, Venica, Liptia1, Hadi Putri, Dewi Indriati1, Kosmaga, Shinta Rohmatika2, Rijanto, Estiko2
Source: Mechatronics, Electrical Power & Vehicular Technology. 2025, Vol. 16 Issue 2, p158-168. 11p.
Subject Terms: *Stereo vision (Computer science), *Smart parking systems, *Regression analysis, *Root-mean-squares, *Detection algorithms, *Simulation software, *Euclidean distance
Abstract: This paper presents an evaluation of stereo vision based on the semi-global block matching (SGBM) algorithm for distance estimation in an autonomous parking scenario using the CARLA simulator. Distance-disparity regression functions are explored to enhance distance estimation accuracy. The proposed distance estimation model was evaluated using the design science research methodology (DSRM) framework, with experimental validation conducted in CARLA's promenade environment. The evaluation employed root mean square error (RMSE) and relative error metrics to assess performance. Experiments were performed within a range of 40-350 cm, which is relevant for autonomous parking applications. The experimental results show that the algorithm achieves an overall RMSE of 1.69 cm and an average relative error of 1.1 %. The findings contribute to the advancement of perception systems for autonomous vehicles, particularly in challenging environments. [ABSTRACT FROM AUTHOR]
Database: Energy & Power Source
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Header DbId: enr
DbLabel: Energy & Power Source
An: 191038908
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Label: Title
  Group: Ti
  Data: An evaluation of stereo vision for distance estimation using the SGBM algorithm in the CARLA simulator.
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  Data: <searchLink fieldCode="AR" term="%22Sakti%2C+Rizky+Hamdani%22">Sakti, Rizky Hamdani</searchLink><relatesTo>1</relatesTo><i> rizkyhamm@upi.edu</i><br /><searchLink fieldCode="AR" term="%22Venica%2C+Liptia%22">Venica, Liptia</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Hadi+Putri%2C+Dewi+Indriati%22">Hadi Putri, Dewi Indriati</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Kosmaga%2C+Shinta+Rohmatika%22">Kosmaga, Shinta Rohmatika</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Rijanto%2C+Estiko%22">Rijanto, Estiko</searchLink><relatesTo>2</relatesTo>
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  Data: <searchLink fieldCode="JN" term="%22Mechatronics%2C+Electrical+Power+%26+Vehicular+Technology%22">Mechatronics, Electrical Power & Vehicular Technology</searchLink>. 2025, Vol. 16 Issue 2, p158-168. 11p.
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: *<searchLink fieldCode="DE" term="%22Stereo+vision+%28Computer+science%29%22">Stereo vision (Computer science)</searchLink><br />*<searchLink fieldCode="DE" term="%22Smart+parking+systems%22">Smart parking systems</searchLink><br />*<searchLink fieldCode="DE" term="%22Regression+analysis%22">Regression analysis</searchLink><br />*<searchLink fieldCode="DE" term="%22Root-mean-squares%22">Root-mean-squares</searchLink><br />*<searchLink fieldCode="DE" term="%22Detection+algorithms%22">Detection algorithms</searchLink><br />*<searchLink fieldCode="DE" term="%22Simulation+software%22">Simulation software</searchLink><br />*<searchLink fieldCode="DE" term="%22Euclidean+distance%22">Euclidean distance</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This paper presents an evaluation of stereo vision based on the semi-global block matching (SGBM) algorithm for distance estimation in an autonomous parking scenario using the CARLA simulator. Distance-disparity regression functions are explored to enhance distance estimation accuracy. The proposed distance estimation model was evaluated using the design science research methodology (DSRM) framework, with experimental validation conducted in CARLA's promenade environment. The evaluation employed root mean square error (RMSE) and relative error metrics to assess performance. Experiments were performed within a range of 40-350 cm, which is relevant for autonomous parking applications. The experimental results show that the algorithm achieves an overall RMSE of 1.69 cm and an average relative error of 1.1 %. The findings contribute to the advancement of perception systems for autonomous vehicles, particularly in challenging environments. [ABSTRACT FROM AUTHOR]
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=enr&AN=191038908
RecordInfo BibRecord:
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      – Type: doi
        Value: 10.55981/j.mev.2025.1284
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 11
        StartPage: 158
    Subjects:
      – SubjectFull: Stereo vision (Computer science)
        Type: general
      – SubjectFull: Smart parking systems
        Type: general
      – SubjectFull: Regression analysis
        Type: general
      – SubjectFull: Root-mean-squares
        Type: general
      – SubjectFull: Detection algorithms
        Type: general
      – SubjectFull: Simulation software
        Type: general
      – SubjectFull: Euclidean distance
        Type: general
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      – TitleFull: An evaluation of stereo vision for distance estimation using the SGBM algorithm in the CARLA simulator.
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            NameFull: Sakti, Rizky Hamdani
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            NameFull: Venica, Liptia
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            NameFull: Hadi Putri, Dewi Indriati
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            NameFull: Kosmaga, Shinta Rohmatika
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            NameFull: Rijanto, Estiko
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          Dates:
            – D: 01
              M: 07
              Text: 2025
              Type: published
              Y: 2025
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              Value: 16
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              Value: 2
          Titles:
            – TitleFull: Mechatronics, Electrical Power & Vehicular Technology
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