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Modeling Liability Data Collection Systems for Intelligent Transportation Infrastructure Using Hyperledger Fabric

Abstract : Distributed ledger technology is transforming environments where the participating entities have low trust. Employing distributed ledgers for intelligent transportation infrastructure communications and operations enables decentralized collaboration between entities that do not fully trust each other. This chapter models a transportation event data collection system as a Hyperledger Fabric blockchain network and simulates it using a transportation environment modeling tool. Data structures model the data collected about accidents involving vehicles and witness reports from nearby vehicles and road-side units that observed the events. The chaincode developed for the collection, validation and corroboration of the reported data is presented. Network performance results for various configurations are discussed. Optimization of the network configuration parameters resulted in a 48.1% improvement in transaction throughput. The experiments demonstrate that a distributed ledger technology such as Hyperledger Fabric holds promise for the collection of transportation data and the collaboration of applications and services that consume the data.
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https://hal.inria.fr/hal-03364560
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Submitted on : Monday, October 4, 2021 - 5:49:07 PM
Last modification on : Wednesday, November 3, 2021 - 7:05:58 AM
Long-term archiving on: : Wednesday, January 5, 2022 - 7:05:52 PM

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Distributed under a Creative Commons Attribution 4.0 International License

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Luis Cintron, Scott Graham, Douglas Hodson, Barry Mullins. Modeling Liability Data Collection Systems for Intelligent Transportation Infrastructure Using Hyperledger Fabric. 13th International Conference on Critical Infrastructure Protection (ICCIP), Mar 2019, Arlington, VA, United States. pp.137-156, ⟨10.1007/978-3-030-34647-8_8⟩. ⟨hal-03364560⟩

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