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2019 | OriginalPaper | Buchkapitel

6. Next Generation of Transportation Infrastructure Management: Fusion of Intelligent Transportation Systems (ITS) and Bridge Information Modeling (BrIM)

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Abstract

Bridges are one of the most important elements of the sustainable transportation infrastructure network that require significant care and consideration. Aging and deterioration are two main complications in their operation and maintenance that require precise data and efficient technologies to improve the quality of their lifecycle management. Intelligent transportation systems (ITS) have been altering the infrastructure management process by converting it into an automated process to capture, store, analyze, and manage the data. While the data have helped the management process, the issues of heterogeneity of the data and non-interoperable databases are still challenges for fully integrated management of the infrastructure. Thus, there is a crucial need for an integrated database that can help in consolidation of data management. Building Information Modeling (BIM) is one of the recent technologies that its benefits have motivated its utilization in the transportation infrastructure, and their specific use for bridges is known as Bridge Information Modeling (BrIM). Currently bridges are being inspected biannually and only structural data are being recorded for their assessment. This paper suggests the inclusion of traffic data in lifecycle management of bridges and introduces ITS as a great source of data, and BrIM as a great visual database that can help in enhancing the integration and management of databases. Fusion of ITS data with BrIM can provide many benefits for efficient operation and management of bridges that eventually improves the quality of facility management and helps as a reliable tool for decision making and budget allocation. In this paper, BIM and ITS capabilities have been discussed and finally a framework has been suggested to illuminate the dataflow process.

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Literatur
3.
Zurück zum Zitat Maeda, K., Takahashi, S., Ogawa, T., Haseyama, M.: Distress classification of class imbalanced data for maintenance inspection of road structures in express way. In: Proceedings of the International Conference on Computing in Civil and Building Engineering (ICCCBE), pp. 182–185, April 19–21, Taipei, Taiwan (2017) Maeda, K., Takahashi, S., Ogawa, T., Haseyama, M.: Distress classification of class imbalanced data for maintenance inspection of road structures in express way. In: Proceedings of the International Conference on Computing in Civil and Building Engineering (ICCCBE), pp. 182–185, April 19–21, Taipei, Taiwan (2017)
7.
Zurück zum Zitat Al-Shalabi, F.A., Turkan, Y., Laflamme, S. BrIM implementation for documentation of bridge condition for inspection. In: Proceedings of the 5th International/11th Construction Specialty Conference, June 8–10, Vancouver, British Columbia, vol. 262, pp. 1–8 (2015) https://doi.org/10.14288/1.0076437 Al-Shalabi, F.A., Turkan, Y., Laflamme, S. BrIM implementation for documentation of bridge condition for inspection. In: Proceedings of the 5th International/11th Construction Specialty Conference, June 8–10, Vancouver, British Columbia, vol. 262, pp. 1–8 (2015) https://​doi.​org/​10.​14288/​1.​0076437
8.
Zurück zum Zitat Badrinath, A., Chang, Y., Lin, E., Hsien, S., Zhao, B.: A preliminary study on BIM enabled design warning analysis in T3A Terminal of Chongqing Jiangbei International Airport. In: Proceedings of the International Conference on Computing in Civil and Building Engineering (ICCCBE), pp. 485–491, July 6–8, Osaka, Japan (2016) Badrinath, A., Chang, Y., Lin, E., Hsien, S., Zhao, B.: A preliminary study on BIM enabled design warning analysis in T3A Terminal of Chongqing Jiangbei International Airport. In: Proceedings of the International Conference on Computing in Civil and Building Engineering (ICCCBE), pp. 485–491, July 6–8, Osaka, Japan (2016)
9.
Zurück zum Zitat Miao, T.J., Chan T.H.T.: Bridge live load models from WIM data. Eng. Structures. 24(8), 1071–1084 (2002)CrossRef Miao, T.J., Chan T.H.T.: Bridge live load models from WIM data. Eng. Structures. 24(8), 1071–1084 (2002)CrossRef
10.
Zurück zum Zitat Mahmoud Khan, S., Atamturktur, S., Chowdhury, M., Rahman, N.: Integration of structural health monitoring and intelligent transportation systems for bridge condition assessment: current status and future direction. IEEE Trans. Intell. Transp. Syst. 17(8), 2107–2122 (2016)CrossRef Mahmoud Khan, S., Atamturktur, S., Chowdhury, M., Rahman, N.: Integration of structural health monitoring and intelligent transportation systems for bridge condition assessment: current status and future direction. IEEE Trans. Intell. Transp. Syst. 17(8), 2107–2122 (2016)CrossRef
11.
Zurück zum Zitat Lan, C., Li, H., Ou, J.: Traffic load modeling based on structural health monitoring data. Struct. Infrastruct. Eng. 7(5), 379–386 (2011)CrossRef Lan, C., Li, H., Ou, J.: Traffic load modeling based on structural health monitoring data. Struct. Infrastruct. Eng. 7(5), 379–386 (2011)CrossRef
15.
Zurück zum Zitat Sweet, M.: Does traffic congestion slow the economy? J. Plann. Lit. 26(4), 391–404 (2011)CrossRef Sweet, M.: Does traffic congestion slow the economy? J. Plann. Lit. 26(4), 391–404 (2011)CrossRef
16.
Zurück zum Zitat Schrank, D., Eisele, B., Lomax, T., Bak, J.: “2015 Urban Mobility Score Card”. Texas A&M Transportation Research Institute and INRIX Inc., Texas, USA (2015) Schrank, D., Eisele, B., Lomax, T., Bak, J.: “2015 Urban Mobility Score Card”. Texas A&M Transportation Research Institute and INRIX Inc., Texas, USA (2015)
17.
Zurück zum Zitat Cheng, H., Gau, V., Huang, C., Hwang, J.: Advanced formation and delivery of traffic information in intelligent transportation systems. Expert Syst. Appl. 39, 8356–8368 (2012)CrossRef Cheng, H., Gau, V., Huang, C., Hwang, J.: Advanced formation and delivery of traffic information in intelligent transportation systems. Expert Syst. Appl. 39, 8356–8368 (2012)CrossRef
18.
Zurück zum Zitat Pradhan, R., Bagchi, T.: Effect of transportation infrastructure on economic growth in India: the VECM approach. Res. Transp. Econ. 38(1), 139–148 (2013)CrossRef Pradhan, R., Bagchi, T.: Effect of transportation infrastructure on economic growth in India: the VECM approach. Res. Transp. Econ. 38(1), 139–148 (2013)CrossRef
19.
Zurück zum Zitat Zeyu, J., Shuiping, Y., Mingduan, Z., Yongqiang, C., Yi, L.: Model study for intelligent transportation systems with big data. In: International Congress of Information and Communication Technology, pp. 418–426, Sanya, China (2017)CrossRef Zeyu, J., Shuiping, Y., Mingduan, Z., Yongqiang, C., Yi, L.: Model study for intelligent transportation systems with big data. In: International Congress of Information and Communication Technology, pp. 418–426, Sanya, China (2017)CrossRef
Metadaten
Titel
Next Generation of Transportation Infrastructure Management: Fusion of Intelligent Transportation Systems (ITS) and Bridge Information Modeling (BrIM)
verfasst von
Alireza Adibfar
Aaron Costin
Copyright-Jahr
2019
DOI
https://doi.org/10.1007/978-3-030-00220-6_6