Efficient Multi-Maneuver Platooning Framework for Autonomous Vehicles on Multi-Lane Highways

Yun Hao Ye, Zhi Yang Lin, Chih Chiung Yao, Lan Huong Nguyen, Jian Jhih Kuo, Ren Hung Hwang

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

1 Scopus citations

Abstract

Recently, autopilot-like vehicles have become more pervasive. To maintain inter-vehicle distance stably, Cooperative Adaptive Cruise Control (CACC) is then proposed to make each autonomous vehicle exchange its dynamic state with neighboring vehicles via vehicle-to-vehicle (V2V) communication. However, longitudinal platooning via CACC systems alone is not enough to improve traffic throughput since each vehicle has its own desired speed and only considers itself to optimize its traveling. Therefore, we develop a novel framework MANA to determine the suitable platoon-merge maneuver, lane-change maneuver, and space-reserve maneuver. Extensive simulation results manifest that MANA can avoid collisions effectively, converge fast, and save fuel consumption and CO emissions by 24% and 20%.

Original languageEnglish
Title of host publication2021 IEEE 94th Vehicular Technology Conference, VTC 2021-Fall - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665413688
DOIs
StatePublished - 2021
Event94th IEEE Vehicular Technology Conference, VTC 2021-Fall - Virtual, Online, United States
Duration: 27 Sep 202130 Sep 2021

Publication series

NameIEEE Vehicular Technology Conference
Volume2021-September
ISSN (Print)1550-2252

Conference

Conference94th IEEE Vehicular Technology Conference, VTC 2021-Fall
Country/TerritoryUnited States
CityVirtual, Online
Period27/09/2130/09/21

Keywords

  • autonomous vehicle
  • multi-maneuver
  • Platooning

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