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August 3, 2026Mechatronics Electrical Power and Vehicular TechnologyOpen Access

An efficient motion planning framework for four-wheel steering autonomous vehicles using Lazy Edge-Based A* and adaptive RK4-MPC

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Authors

DSDeyndrawan SutrisnoSSSubiyanto SubiyantoAHArimaz Hangga

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Overview

Randomized trial demonstrates improved motion planning efficiency in autonomous vehicles, suggesting enhanced performance in complex environments.

Key Points

  • This work aims to develop an efficient motion planning framework for four-wheel steering (4WS) autonomous vehicles.
  • Employs lazy edge-based A* algorithm for global path planning.
  • Utilizes adaptive fourth-order Runge–Kutta model predictive control for trajectory tracking.
  • Implements wheel force distribution control for stable steering maneuvers.
  • LEA* reduces planning time by 87.5% and edge evaluations by 96.1% compared to conventional A*.
  • Adaptive RK4-MPC with WFDC reduces tracking error by 34.8% and yaw acceleration by 50% compared to both OMNI and S-4WS.
  • Overall search time is 0.5234 s, 83.1% faster than OMNI and 37.1% faster than S-4WS.

Cite This Study

Sutrisno et al. (2026) studied this question.

synapsesocial.com/papers/6a703fe175942ff7265e4959https://doi.org/10.55981/j.mev.2026.1073
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