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Ensuring Fuel Economy Performance of Commercial Vehicle Fleets Using Blockchain Technology
ISSN: 2641-9637, e-ISSN: 2641-9645
Published April 02, 2019 by SAE International in United States
Citation: Anwar, H., Arasu, M., and Ahmed, Q., "Ensuring Fuel Economy Performance of Commercial Vehicle Fleets Using Blockchain Technology," SAE Int. J. Adv. & Curr. Prac. in Mobility 1(4):1510-1516, 2019, https://doi.org/10.4271/2019-01-1078.
In the past, research on blockchain technology has addressed security and privacy concerns within intelligent transportation systems for critical V2I and V2V communications that form the backbone of Internet of Vehicles. Within trucking industry, a recent trend has been observed towards the use of blockchain technology for operations. Industry stakeholders are particularly looking forward to refining status quo contract management and vehicle maintenance processes through blockchains. However, the use of blockchain technology for enhancing vehicle performance in fleets, especially while considering the fact that modern-day intelligent vehicles are prone to cyber security threats, is an area that has attracted less attention. In this paper, we demonstrate a case study that makes use of blockchains to securely optimize the fuel economy of fleets that do package pickup and delivery (P&D) in urban areas. We implement a consortium blockchain infrastructure, as opposed to a fully public blockchain (similar to the blockchain underlying Bitcoin) which is arguably not real-time or well suited for this safety-critical application. By leveraging in real-time a fleet vehicle’s powertrain status, geospatial traffic data, along with driver information, the fleet vehicle acts as a node ready for data transactions in the blockchain network. Each such vehicle in the fleet communicates with its local central hub, and these secure exchanges of data and information act as immutable blockchain transactions. Consensus within the fleet is established when multiple vehicles report data updates for a given subregion in the fleet route map. The proposed infrastructure will support a fleet route planning algorithm running on the local hub, responsible for optimizing fuel economy for the fleet, increasing its reliability and credibility.