Driver behaviors assisted by different human machine interfaces to avoid rear-end collisions during level 2 automated driving

To address the problems of intelligent vehicles navigating obstacles on rainy and snowy road surfaces, this study establishes a two-layer model comprising of an upper-level local path planning layer and a lower-level trajectory tracking control layer. The aim is to enhance the safety and stability of intelligent vehicles during lane changes and obstacle avoidance. In the local path planning layer, an obstacle avoidance function is introduced and optimized using the repulsive force function of the artificial potential fields method, followed by analysis using nonlinear model predictive control. In the trajectory tracking control layer, constraints are designed on front-wheel steering angle, steering angle increment, center of mass lateral deviation angle, lateral acceleration, yaw angle, and yaw angular velocity based on model predictive control and two-degree-of-freedom vehicle dynamics constraints. To validate the effectiveness of the model, this study utilized the CarSim/Simulink joint simulation platform to establish three different vehicle speeds of 36, 72, and 108 km/h, and designed two typical experimental scenarios of single obstacle avoidance and multiple obstacle continuous avoidance. The results indicate that optimizing the obstacle avoidance function using the repulsive force function of the artificial potential field method can reduce the lateral displacement of the intelligent vehicle by an average of 0.079 and 0.118 m in both scenarios, resulting in smoother trajectories. Additionally, the yaw angle is reduced by an average of 0.392° and 0.407°, making the vehicle more stable.

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Driver behaviors assisted by different human machine interfaces to avoid rear-end collisions during level 2 automated driving

Cited by 3 publications

References 19 publications

Do automation and digitalization distract drivers? A systematic review

Do automation and digitalization distract drivers? A systematic review

In-vehicle displays for driving automation: a scoping review of display design and evaluation using driver gaze measures

Trajectory planning for intelligent vehicle obstacle avoidance in rainy and snowy conditions

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