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Dorsal Column Steerability with Dual Parallel Leads using Dedicated Power Sources: A Computational Model
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Shared Steering Control for Lane Keeping and Obstacle Avoidance Based on Multi-Objective MPC.

Yang Liang1,2,3,4, Zhishuai Yin1,2,3,4, Linzhen Nie1,2,3,4

  • 1School of Automotive Engineering, Wuhan University of Technology, Wuhan 430070, China.

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Summary
This summary is machine-generated.

This study introduces a shared steering control system using multi-objective model predictive control (MPC) for safer driving. The framework smoothly blends driver and automation commands for lane keeping and obstacle avoidance.

Keywords:
model predictive controlshared controlsituation assessment

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Area of Science:

  • Automotive Engineering
  • Control Systems
  • Robotics

Background:

  • Lane keeping and obstacle avoidance are critical for vehicle safety.
  • Shared control systems aim to integrate human driver intentions with autonomous capabilities.
  • Model Predictive Control (MPC) offers a robust framework for complex control problems.

Purpose of the Study:

  • To develop a shared steering control framework for lane keeping and obstacle avoidance.
  • To enable smooth integration of driver commands and autonomous control.
  • To dynamically allocate control authority between the driver and the automation.

Main Methods:

  • Multi-objective Model Predictive Control (MPC) formulation.
  • Integration of trajectory tracking and driver command tracking into the MPC cost function.
  • A novel situation assessment method for dynamic risk evaluation (longitudinal and lateral).
  • CarSim-Matlab/Simulink joint simulations for validation.

Main Results:

  • The proposed shared controller successfully combined driver and automation steering commands.
  • The system demonstrated effective lane keeping and obstacle avoidance.
  • The situation assessment method enabled adaptive authority allocation.
  • Vehicle stability was maintained during shared control maneuvers.

Conclusions:

  • The developed shared steering control framework enhances vehicle safety and driver assistance.
  • Multi-objective MPC provides a flexible approach for integrating human and autonomous control.
  • The dynamic risk assessment is crucial for effective shared control authority allocation.