Crowdsourced traffic event detection and source reputation assessment using smart contracts

Mihelj, Jernej (author), Zhang, Yuan (author), Kos, Andrej (author), Sedlar, Urban (author)

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.

• Language: English
• Keywords: truth discovery, road traffic, event detection, reputation assessment, blockchain, smart contract
• Work type: Article
• Typology: 1.01 - Original Scientific Article
• Organization: FE - Faculty of Electrical Engineering
• Publication status: Published
• Publication version: Version of Record
• Year: 2019
• Number of pages: 17 str.
• Numbering: Vol. 19, iss. 15, art. 3267
• PID: 20.500.12556/RUL-132831
• UDC: 004:351.811
• ISSN on article: 1424-8220
• DOI: 10.3390/s19153267
• COBISS.SI-ID: 12587860
• Publication date in RUL: 04.11.2021

Record is a part of a journal

• Title: Sensors
• Shortened title: Sensors
• Publisher: MDPI
• ISSN: 1424-8220
• COBISS.SI-ID: 10176278

Licences

• License: CC BY 4.0, Creative Commons Attribution 4.0 International
• Link: http://creativecommons.org/licenses/by/4.0/
• Description: This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
• Licensing start date: 01.08.2019

Secondary language

• Language: Slovenian
• Keywords: odkrivanje resnice v podatkih, cestni promet, detekcija dogodkov, ocenjevanje ugleda, veriženje podatkovnih blokov, pametne pogodbe

Projects

• Funder: ARRS - Slovenian Research Agency
• Project number: P2-0246
• Name: ICT4QoL - Informacijsko komunikacijske tehnologije za kakovostno življenje

• Funder: Other - Other funder or multiple funders
• Funding programme: National Natural Science Foundation of China
• Project number: 61572231