成果報告書詳細
管理番号20150000000607
タイトル*平成26年度中間年報 SIP(戦略的イノベーション創造プログラム) インフラ維持管理・更新・マネジメント技術 インフラの多種多様なセンシングデータを処理・蓄積・解析する技術の開発 インフラ維持管理・更新に関する多種多様なデータの蓄積・管理・活用技術の研究開発
公開日2015/8/4
報告書年度2014 - 2014
委託先名株式会社日立製作所
プロジェクト番号P14031
部署名電子・材料・ナノテクノロジー部
和文要約
英文要約The purpose of this project is to develop the sensor DBMS for centralized storage, management and application of broad social infrastructure data.
For this purpose, the research and development of the sensor DBMS will be conducted to subject the road operation and management in cooperation with Hanshin Expressway Group.

Although the sensor data handled by the sensor DBMS include data from equipment dedicated for road inspection, data from vibroscopes fixed on a bridge, and probe data from smartphones (location, acceleration, images), this project focuses specifically on portable sensors, especially probe data.

(1) Cross-section analytical technology by the distance parameter

We designed the system architecture and implement effective cross-section analysis function which integrates and analyzes multiple series data from various probe cars using the data placement method which used block management of series data and distributed them to nodes according to each distance parameter. Furthermore, we developed the distributed processing function to confirm the effectiveness of this method featuring the road surface condition estimation from the acceleration data and GPS data during vehicle operation. It was confirmed that this proposed method can achieve the processing performance that is twice as fast as Hadoop.

(2) Location correction technology

The location correction technology using the vertical acceleration data of a moving vehicle was developed in order to correlate the sensor data measured by a portable sensor equipped with the moving vehicle to the infrastructure. Driving tests were conducted to verify the effectiveness of the location correction technology. It was confirmed that the target value for the location correction technology (error within 3m of the vehicle moving direction) was achieved.

(3) Acceleration correction technology for different vehicle models

The correction method for vertical acceleration data dependent on vehicle characteristics was developed to estimate International Roughness Index (IRI). Driving tests was conducted to verify the effectiveness of the acceleration correction technology for different vehicle models. It was confirmed that our proposed method can estimate IRI more accurately than the conventional method which corrects the acceleration when both wheels ride across known bumps.

(4) Handling technology for missing GPS data

We developed the handling technology for missing GPS data in order to detect the period of missing GPS data which are difficult to interpolate caused by obstacles such as tunnels, and delete the sensor data measured during the respective period. To verify the effectiveness of the handling technology for missing GPS data, we conducted the driving tests on several highways with tunnels which missing GPS data are invariably observed. It was confirmed that the detection rate of missing GPS data during the period of tunnel driving was 100% and the target value(>80%) has been achieved.
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