Privacy-Preserving Intersection Management for Autonomous Vehicles

Nadin Kokciyan, Mustafa Erdogan, Tuna Han Salih Meral, Pinar Yolum

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

Traffic lights are a common instrument to regulatethe traffic in junctions. However, when a vehicle has an urgency, it may violate the traffic lights. Since the other vehicles do not expect this, such violations lead to road accidents. Connected and autonomous vehicles can coordinate their actions and decide on the priority of passing without the need of traffic lights if they can share information about their current situation. That is, a vehicle with an urgency can communicate this with justifications toothers and ask to go first. However, the shared information can potentially yield privacy violations while helping vehicles attain priority. We propose a privacy-preserving decision making framework for managing traffic at junctions. The vehicles are represented as autonomous agents that can communicate with each other and make priority-based decisions using auctions. The bids in the auctions are not monetary but contain information that each vehicle is willing to declare. Our experiments on real-world accident data show that our proposed bidding strategies help vehicles preserve their privacy while still enabling them to receive priority at junctions.
Original languageEnglish
Title of host publicationProceedings of the Tenth International Workshop on Agents in Traffic and Transportation (ATT 2018)
PublisherCEUR Workshop Proceedings (
Number of pages8
Publication statusPublished - 14 Jul 2018
Event10th International Workshop on Agents in Traffic and Transportation 2018 - Stockholm, Sweden
Duration: 14 Jul 201814 Jul 2018

Publication series

PublisherCEUR Workshop Proceedings (
ISSN (Electronic)1613-0073


Workshop10th International Workshop on Agents in Traffic and Transportation 2018
Abbreviated titleATT 2018
Internet address


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