Optimization-Based Approach for Resilient Connected and Autonomous Intersection Crossing Traffic Control Under V2X Communication

Qiang Lu, Hojin Jung, Kyoung Dae Kim

Research output: Contribution to journalArticlepeer-review

25 Scopus citations

Abstract

In this paper, we present an optimization-based approach for safe, efficient, and resilient autonomous intersection traffic control in realistic vehicle-to-everything (V2X) communication environment. The proposed framework produces the fastest discrete-time trajectory for vehicles who want to cross an intersection. Constraints for safety are designed carefully in the optimization problem formulation to prevent potential collisions during intersection crossings. A novel vehicle-to-intersection (V2I) interaction mechanism is designed to handle imperfect communication characteristics such as packet delivery delay and loss. The proposed intersection management framework is evaluated by running extensive simulations using an open source vehicular network and microscopic traffic simulation software, Veins. The results show that the overall traffic control performance of the proposed framework is substantially better than conventional traffic light control framework, in particular when traffic volume is light and medium, even in situations with a realistic wireless vehicular network setting where packet delivery delays and drops occasionally occur.

Original languageEnglish
Pages (from-to)354-367
Number of pages14
JournalIEEE Transactions on Intelligent Vehicles
Volume7
Issue number2
DOIs
StatePublished - 1 Jun 2022

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Keywords

  • Connected and autonomous vehicle
  • V2X communication
  • mixed integer programming (MIP)
  • resilient intelligent intersection management

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