Reactive Online Motion Re-Planning for Crash Mitigation in Autonomous Vehicles Using Bezier Curve Optimization

Abstract Crash avoidance and mitigation is still one of the major challenges faced by the autonomous vehicles industry. Path planning in autonomous vehicles is a crucial phase during crash avoidance with other vehicles. It is important for the path planning algorithm to be reactive in uncertain situations which usually arise in urban road scenarios. This study proposes a reactive online path planning strategy for obstacle avoidance and crash mitigation for an imminent collision with another vehicle. A cubic Bezier curve trajectory generation method is used for creating a maneuver around the obstacle vehicle. Relative hitting heading angle is considered to account for the crash severity between two vehicles. Two cases are considered where one is an imminent crash scenario and the other is where an obstacle can be avoided with a minimum safety distance. This obstacle avoidance problem is then converted to an optimization problem where potential crash severity, vehicle kinematic constraints and path smoothness are considered as constraints. The resulting cost function consists of a quadratic convex function and a piecewise defined function. This is further solved using a novel methodology where the piecewise function is included in the inequality constraints, so that the problem can be solved using quadratic programming method. This will also lead to a quick real time implementation. It is shown that the proposed method is able to avoid collisions and also minimizes the crash severity in case of an imminent collision.

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Reactive Path Planning for Autonomous Vehicle Using Bézier Curve Optimization

2019 IEEE Intelligent Vehicles Symposium (IV) ◽

10.1109/ivs.2019.8813904 ◽

2019 ◽

Author(s):

Julien Moreau ◽

Pierre Melchior ◽

Stephane Victor ◽

Mathieu Moze ◽

Francois Aioun ◽

...

Keyword(s):

Path Planning ◽

Autonomous Vehicle ◽

Bézier Curve ◽

Bezier Curve ◽

Curve Optimization

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A NURBS transition between a Bézier curve and its control polygon

Journal of Computational and Applied Mathematics ◽

10.1016/j.cam.2021.113626 ◽

2021 ◽

pp. 113626

Author(s):

Imre Juhász

Keyword(s):

Bézier Curve ◽

Bezier Curve ◽

Control Polygon

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Optimal Bezier Curve Modification Function for Contrast Degraded Images

IEEE Transactions on Instrumentation and Measurement ◽

10.1109/tim.2021.3073320 ◽

2021 ◽

Vol 70 ◽

pp. 1-10

Author(s):

Bharath Subramani ◽

Ashish Kumar Bhandari ◽

Magudeeswaran Veluchamy

Keyword(s):

Bézier Curve ◽

Bezier Curve ◽

Degraded Images

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Automatic Lane-Changing Decision Based on Single-Step Dynamic Game with Incomplete Information and Collision-Free Path Planning

Actuators ◽

10.3390/act10080173 ◽

2021 ◽

Vol 10 (8) ◽

pp. 173

Author(s):

Hongbo Wang ◽

Shihan Xu ◽

Longze Deng

Keyword(s):

Path Planning ◽

Dynamic Game ◽

Single Step ◽

Bézier Curve ◽

Vehicle Safety ◽

Bezier Curve ◽

Lane Change ◽

Hardware In The Loop ◽

Power Performance ◽

Lane Changing

Traffic accidents are often caused by improper lane changes. Although the safety of lane-changing has attracted extensive attention in the vehicle and traffic fields, there are few studies considering the lateral comfort of vehicle users in lane-changing decision-making. Lane-changing decision-making by single-step dynamic game with incomplete information and path planning based on Bézier curve are proposed in this paper to coordinate vehicle lane-changing performance from safety payoff, velocity payoff, and comfort payoff. First, the lane-changing safety distance which is improved by collecting lane-changing data through simulated driving, and lane-changing time obtained by Bézier curve path planning are introduced into the game payoff, so that the selection of the lane-changing start time considers the vehicle safety, power performance and passenger comfort of the lane-changing process. Second, the lane-changing path without collision to the forward vehicle is obtained through the constrained Bézier curve, and the Bézier curve is further constrained to obtain a smoother lane-changing path. The path tracking sliding mode controller of front wheel angle compensation by radical basis function neural network is designed. Finally, the model in the loop simulation and the hardware in the loop experiment are carried out to verify the advantages of the proposed method. The results of three lane-changing conditions designed in the hardware in the loop experiment show that the vehicle safety, power performance, and passenger comfort of the vehicle controlled by the proposed method are better than that of human drivers in discretionary lane change and mandatory lane change scenarios.

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