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Detection of precursory changes of road structure damages using vision and vibration data of vehicles

Research Project

Project/Area Number 21H01587
Research Category

Grant-in-Aid for Scientific Research (B)

Allocation TypeSingle-year Grants
Section一般
Review Section Basic Section 25030:Disaster prevention engineering-related
Research InstitutionThe University of Tokyo

Principal Investigator

Nagayama Tomonori  東京大学, 大学院工学系研究科(工学部), 教授 (80451798)

Co-Investigator(Kenkyū-buntansha) 蘇 迪  東京大学, 大学院工学系研究科(工学部), 特任准教授 (40535796)
西川 貴文  長崎大学, 工学研究科, 准教授 (50512076)
Project Period (FY) 2021-04-01 – 2024-03-31
Project Status Completed (Fiscal Year 2023)
Budget Amount *help
¥17,160,000 (Direct Cost: ¥13,200,000、Indirect Cost: ¥3,960,000)
Fiscal Year 2023: ¥5,330,000 (Direct Cost: ¥4,100,000、Indirect Cost: ¥1,230,000)
Fiscal Year 2022: ¥6,500,000 (Direct Cost: ¥5,000,000、Indirect Cost: ¥1,500,000)
Fiscal Year 2021: ¥5,330,000 (Direct Cost: ¥4,100,000、Indirect Cost: ¥1,230,000)
Keywords画像解析 / 差分解析 / ひび割れ / 機械学習 / 振動
Outline of Research at the Start

危険な変状を早期に捉える仕組みが求められる.車内設置された汎用カメラの画像を収集して広域のひび割れを効率的に抽出する取り組みはあるものの,道路網に無数に存在するひび割れを網羅的に検出するだけでは意味を無さない.そこで,車載カメラの動画像に対する精緻な画像処理と,車両動揺データ分析を活用した2段階の位置推定技術に基づいて,災害前後や平時のひび割れ変化量,つまり差分を算出し,重大な道路構造物被害の前兆となり得る進行性のある変状を抽出する.地震や大雨等の災害時には危険な兆候を迅速に把握し,平時には進行性をもつ変状を効率的に捉えることで,二次災害の軽減や効率的な予防保全に資するものである.

Outline of Final Research Achievements

We conducted a study to extract progressive road surface damages that could indicate significant infrastructure deterioration by using in-vehicle cameras to capture road surface images, accurately identify positions, and analyze the images. We developed methods to estimate vehicle speed and position using vehicle dynamics analysis, even in environments where GPS is unavailable, such as tunnels, mountainous areas, and urban canyons. For crack evaluation, we employed semantic segmentation to extract cracks and examined the effects of sunlight conditions. Additionally, we achieved precise alignment of individual cracks using feature matching with machine learning on bird's-eye view images, enabling the assessment of crack progression.

Academic Significance and Societal Importance of the Research Achievements

道路舗装表面に現れる変状には、土砂崩れや大規模な沈下の前兆となる危険なひび割れや、事故を誘発する大きなポットホールの発生に至るものがある。重大な道路構造物被害につながるこれらの危険な変状を早期に捉える仕組みが求められる。車内設置カメラの画像を収集して広域のひび割れを効率的に抽出する試みはあるが、網羅的検出だけでは意味をなさない。本研究で開発した手法は、進行性を有する危険なひび割れ変状を車載カメラから効率的に抽出可能にするものである。また、Transformerモデルを用いた特徴マッチングにより、舗装表面の高度な位置合わせを実現し、今後の劣化評価や予測モデル構築の礎を築くものである。

Report

(4 results)
  • 2023 Annual Research Report   Final Research Report ( PDF )
  • 2022 Annual Research Report
  • 2021 Annual Research Report
  • Research Products

    (7 results)

All 2023 2022 2021

All Journal Article (1 results) (of which Peer Reviewed: 1 results,  Open Access: 1 results) Presentation (6 results) (of which Int'l Joint Research: 2 results)

  • [Journal Article] Estimation of pavement crack ratio by top-view transformation of in-vehicle smartphone camera and deep learning-based classification2022

    • Author(s)
      Jose Maria Guyamin GEDA, Kai XUE, Tomonori NAGAYAMA, Boyu ZHAO, Michihiro NAKA
    • Journal Title

      Intelligence, Informatics and Infrastructure

      Volume: 3 Issue: 3 Pages: 26-39

    • DOI

      10.11532/jsceiii.3.3_26

    • ISSN
      2435-9262
    • Related Report
      2022 Annual Research Report
    • Peer Reviewed / Open Access
  • [Presentation] Rut depth estimation by distortion analysis of images taken by an in-vehicle camera2023

    • Author(s)
      Wenchao Gao
    • Organizer
      THE EIGHTH INTERNATIONAL SYMPOSIUM ON LIFE-CYCLE CIVIL ENGINEERING (IALCCE 2023)
    • Related Report
      2023 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Vehicle trajectory estimation in GPS-blocked environments using inertial measurement units, estimated drive speed, and bidirectional Kalman filters2023

    • Author(s)
      Jingzi Chen
    • Organizer
      The 10th Japan Conference on Structural Safety and Reliability
    • Related Report
      2023 Annual Research Report
  • [Presentation] 車載カメラ撮影画像の歪み解析による路面わだち掘れ評価2023

    • Author(s)
      高文超
    • Organizer
      土木学会全国大会第78回年次学術講演会
    • Related Report
      2023 Annual Research Report
  • [Presentation] スマートフォンを用いて推定された路面の平坦性とひび割れの経時的分析手法の提案2022

    • Author(s)
      長山智則
    • Organizer
      令和4年度土木学会全国大会年次学術講演会
    • Related Report
      2022 Annual Research Report
  • [Presentation] 車両動揺解析による路面評価のための軸距・センサ位置および走行速度の推定2021

    • Author(s)
      垣内優希
    • Organizer
      令和3年度土木学会全国大会
    • Related Report
      2021 Annual Research Report
  • [Presentation] AUTOMATIC TOP-VIEW TRANSFORMATION AND IMAGE STITCHING OF IN-VEHICLE SMARTPHONE CAMERA FOR ROAD CRACK EVALUATION2021

    • Author(s)
      Jose Maria Guyamin Geda
    • Organizer
      9th international conference on experimental vibration analysis for civil engineering structures
    • Related Report
      2021 Annual Research Report
    • Int'l Joint Research

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Published: 2021-04-28   Modified: 2025-01-30  

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