An Optimized Car-Following Behavior in Response to a Lane-Changing Vehicle: A Bézier Curve-Based Approach

Gihyeob An, Jun Han Bae, Alireza Talebpour

Research output: Contribution to journalArticlepeer-review

Abstract

Sudden lane-changing maneuvers can disrupt the traffic flow. In this paper, we introduce an approach to optimize car-following behavior in response to a lane-changing vehicle in a connected driving environment. Our approach utilizes a quadratic Bézier curve in the time-space diagram to represent the car-following behavior. The algorithm adapts to sudden interruptions from the leading vehicle (i.e., the lane-changing vehicle on the road) while considering driving comfort, traffic impacts, and safety. We derive the acceleration term and factor in initial braking and speed reduction along the curve to generate a safe trajectory for car-following behavior. Our approach was simulated using MATLAB and tested against real-world lane-changing trajectory data collected in Chicago, IL. Results show that our approach produces a safe trajectory curve that adjusts according to the preferred driving pattern when provided with a lane-changing trajectory. This approach provides a useful means of designing safe car-following behavior while considering the impact on upstream traffic in a connected driving environment.

Original languageEnglish (US)
Pages (from-to)682-689
Number of pages8
JournalIEEE Open Journal of Intelligent Transportation Systems
Volume4
DOIs
StatePublished - 2023

Keywords

  • Automated vehicles
  • car-following behavior
  • collision avoidance
  • traffic shockwave
  • trajectory generation

ASJC Scopus subject areas

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications

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