Deep Reinforcement Learning-based Context-Aware Redundancy Mitigation for Vehicular Collective Perception Services

Beopgwon Jung, Joonwoo Kim, Sangheon Pack

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

Abstract

Collective perception service (CPS) is one of the most fundamental services in intelligent transportation systems. Since it can incur significant overhead in exchanging perceived object containers (POCs), european telecommunications standards institute (ETSI) introduced several redundancy mitigation schemes; however, there are several limitations in application to the vehicular environment. In this paper, we propose a deep reinforcement learning (DRL)-based context-Aware redundancy mitigation (DRL-CARM) scheme where various vehicular contexts (i.e., location, speed, heading, and perception area) are employed for redundancy mitigation. To derive the optimal policy on redundancy mitigation, the DRL-CARM scheme employs a deep Q-network (DQN) with a reward function on the usefulness of POC. Evaluation results demonstrate that the DRL-CARM scheme can improve the average usefulness of POC by 254% and reduce the network load by 49.4%, compared with conventional redundancy mitigation schemes.

Original languageEnglish
Title of host publication36th International Conference on Information Networking, ICOIN 2022
PublisherIEEE Computer Society
Pages276-279
Number of pages4
ISBN (Electronic)9781665413329
DOIs
Publication statusPublished - 2022
Event36th International Conference on Information Networking, ICOIN 2022 - Virtual, Jeju Island, Korea, Republic of
Duration: 2022 Jan 122022 Jan 15

Publication series

NameInternational Conference on Information Networking
Volume2022-January
ISSN (Print)1976-7684

Conference

Conference36th International Conference on Information Networking, ICOIN 2022
Country/TerritoryKorea, Republic of
CityVirtual, Jeju Island
Period22/1/1222/1/15

Keywords

  • Collective Perception Service
  • Deep Reinforcement Learning
  • ETSI Redundancy Mitigation Scheme
  • Intelligent Transportation System

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems

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