Data-Driven Federated Autonomous Driving

Ahmad Hammoud, Azzam Mourad, Hadi Otrok, Zbigniew Dziong

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations


Intelligent vehicles optimize road traveling through their reliance on autonomous driving applications to navigate. These applications integrate machine learning to extract statistical patterns and sets of rules for the vehicles to follow when facing decision-making scenarios. The immaturity of such systems, caused by the lack of a diverse dataset, can lead to inaccurate on-road decisions that could affect road safety. In this paper, we devise a decentralized scheme based on federating autonomous driving companies in order to expand their access to data and resources during the learning phase. Our scheme federates companies in an optimal manner by studying the compatibility of the federations’ dataset in the federations formation process, without exposing private data to rivalries. We implement our scheme for evaluation against other formation mechanisms. Experiments show that our approach can achieve higher model accuracy, reduce model loss, and increase the utility of the individuals on average when compared to other techniques.

Original languageBritish English
Title of host publicationMobile Web and Intelligent Information Systems - 18th International Conference, MobiWIS 2022, Proceedings
EditorsIrfan Awan, Muhammad Younas, Aneta Poniszewska-Marańda
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages12
ISBN (Print)9783031143908
StatePublished - 2022
Event18th International Conference on Mobile Web and Intelligent Information Systems, MobiWIS 2022 - Virtual, Online
Duration: 22 Aug 202224 Aug 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13475 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference18th International Conference on Mobile Web and Intelligent Information Systems, MobiWIS 2022
CityVirtual, Online


  • Autonomous driving
  • Federations
  • Intelligent vehicles
  • IoV
  • Machine learning


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