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May 16, 2026Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering

Trajectory tracking for low-speed autonomous vehicles based on MPC and ADRC

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Authors

HLHui LiCSCaixia SongSLShengqin Li

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Overview

Randomized trial demonstrates improved trajectory tracking in autonomous vehicles, indicating enhanced stability and performance.

Key Points

  • This research aims to develop a trajectory tracking controller for low-speed autonomous vehicles that minimizes lateral tracking errors.
  • Implemented a model predictive control (MPC) framework coupled with active disturbance rejection control (ADRC) feedback.
  • Conducted simulations using Simulink/CarSim on circular and sinusoidal paths at varying speeds.
  • Compared the performance of MPC-ADRC against conventional MPC and MPC-PID controllers.
  • MPC-ADRC reduced mean lateral error by 10.6%–13.4% on circular trajectories and 8.7%–23.5% on sinusoidal paths.
  • Compared to MPC-PID, reductions were 6.1%–9.3% on circular paths and 3.1%–14.8% on sinusoidal paths.
  • MPC-ADRC demonstrated robustness, achieving the smallest mean lateral error during Monte Carlo tests under random disturbances.

Cite This Study

Li et al. (2026) studied this question.

synapsesocial.com/papers/6a080ae2a487c87a6a40cda7https://doi.org/10.1177/09544070261447566
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