Head-on Collision Avoidance Path Planning with Model Predictive Control

Document Type : Research Article

Authors

Faculty of Mechanical Engineering, K.N.Toosi University of Technology, Tehran, Iran

Abstract

Due to the high fatalities of head-on accidents, the design of intelligent systems to prevent such severe collisions is essential. In this study, path planning for head-on collision avoidance with a deviated vehicle from the opposite lane has been investigated. The main approach is based on a model predictive controller with 2 seconds of prediction horizon and a linearized prediction model with low errors near the operational conditions. A conservative method is used for lateral motion prediction of the deviated vehicle and based on that, the collision avoidance constraints of the model predictive planner are simply modeled by a new approach. Moreover, a novel method to choose the proper swerve direction of evasive maneuver is proposed. This method is based on keeping the ego vehicle away from dangerous directions and has different criteria for far and close encounters. The final algorithm is capable to control the steering of the prediction model with a constrained lateral acceleration and calculates safe and maneuverable paths for the aforementioned scenario. Four simulations are conducted to validate the algorithm in far and close encountering, and critical conditions of choosing swerve direction. Results show the robustness of the path planner, even to sudden deviations at close distances and with high lateral accelerations.

Keywords

References

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Amirkabir Journal of Mechanical Engineering
Volume 54, Issue 8
November 2022
Pages 1737-1760

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