Risk-aware model predictive control for autonomous vehicle platoons under uncertain cut-in scenarios based on Gaussian mixture models

Key Points

• Enhanced control strategies improve vehicle platoon stability during uncertain cut-in scenarios.
• A Gaussian mixture model effectively captures uncertainties in traffic conditions for predictive control.
• Utilizing model predictive control allows proactive adjustments in vehicle behavior, enhancing overall safety.
• Overall, the findings support the integration of advanced predictive strategies in autonomous vehicle technology.