On-Road Safety Prompt Framework for Platoon

Research output: Contribution to journalConference articlepeer-review

2 Scopus citations

Abstract

In recent years, researchers are very interested in the development of autonomous vehicle platoons that can be commercialized on a large scale. The research progress in this field raises the new demand for real-time traffic flow information and safety prediction. Therefore, an On-road Safety Prompt Framework (OSPF) that combines the free space detection and lane change prediction has beed developed by this paper. This OSPF can predict the lane-change decision and lane-change trajectory around in a short period of time in the future according to the current state and historical trajectory of the surrounding vehicles, and combine these prediction information to provide the autonomous vehicle platoon with the predicted free space in the near future. The free space provided by this OSPF includes three types: continuing driving according to the current state or changing lanes to the left or right. At the same time, it also provides the required recommended driving trajectory. The evaluation test of this ADAS has been done through a simulation testbed of the NGSIM dataset built with Eclipse SUMO (Lopez et al. (2018)).

Original languageEnglish
Pages (from-to)155-160
Number of pages6
JournalIFAC-PapersOnLine
Volume55
Issue number11
DOIs
StatePublished - 1 Jul 2022
Externally publishedYes
Event2022 IFAC Workshop on Control for Smart Cities, CSC 2022 - Proceedings - Sozopol, Bulgaria
Duration: 27 Jun 202230 Jun 2022

Keywords

  • Autonomous Vehicles
  • Guidance and Control
  • Human and vehicle interaction
  • Learning and adaptation in autonomous vehicles
  • Navigation
  • Path Planning
  • Trajectory

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