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Open AccessArticle

Crowdsourced Traffic Event Detection and Source Reputation Assessment Using Smart Contracts

1
Faculty of Electrical Engineering, University of Ljubljana, 1000 Ljubljana, Slovenia
2
Shandong Provincial Key Laboratory of Network Based Intelligent Computing, University of Jinan, Jinan 250022, China
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(15), 3267; https://doi.org/10.3390/s19153267
Received: 30 June 2019 / Revised: 20 July 2019 / Accepted: 23 July 2019 / Published: 25 July 2019
Real-time data about various traffic events and conditions—offences, accidents, dangerous driving, or dangerous road conditions—is crucial for safe and efficient transportation. Unlike roadside infrastructure data which are often limited in scope and quantity, crowdsensing approaches promise much broader and comprehensive coverage of traffic events. However, to ensure safe and efficient traffic operation, assessing trustworthiness of crowdsourced data is of crucial importance; this also includes detection of intentional or unintentional manipulation, deception, and spamming. In this paper, we design and demonstrate a road traffic event detection and source reputation assessment system for unreliable data sources. Special care is taken to adapt the system for operation in decentralized mode, using smart contracts on a Turing-complete blockchain platform, eliminating single authority over such systems and increasing resilience to institutional data manipulation. The proposed solution was evaluated using both a synthetic traffic event dataset and a dataset gathered from real users, using a traffic event reporting mobile application in a professional driving simulator used for driver training. The results show the proposed system can accurately detect a range of manipulative and misreporting behaviors, and quickly converges to the final trust score even in a resource-constrained environment of a blockchain platform virtual machine. View Full-Text
Keywords: truth discovery; road traffic; event detection; reputation assessment; blockchain; smart contract truth discovery; road traffic; event detection; reputation assessment; blockchain; smart contract
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MDPI and ACS Style

Mihelj, J.; Zhang, Y.; Kos, A.; Sedlar, U. Crowdsourced Traffic Event Detection and Source Reputation Assessment Using Smart Contracts. Sensors 2019, 19, 3267.

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