Bézier curve‐based trajectory planning for autonomous vehicles with collision avoidance

Zheng, Ling; Zeng, Pengyun; Yang, Wei; Li, Yinong; Zhan, Zhenfei

doi:10.1049/iet-its.2020.0355

Cited by 52 publications

(35 citation statements)

References 41 publications

(45 reference statements)

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“…The way-points are generated to address the different constraints related to the vehicles and the vehicle's environment. Different interpolation techniques were proposed that use, as a basis, the following curves: lines and circles, clothoids, polynomials, Bézier curves, and splines [100][101] [115][118][119][121]- [125]. The advantage of these techniques is their minimal computational cost [127].…”

Section: ) Interpolating Curve Plannersmentioning

confidence: 99%

Platoon Transitional Maneuver Control System: A Review

et al. 2021

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Connectivity and autonomy are considered two of the most promising technologies to improve mobility, fuel consumption, travel time, and traffic safety in the automated transportation industry. These benefits can be realized through vehicle platooning. A vehicle platoon is composed of a group of connected automated vehicles (CAVs) traveling together at consensual speed, following the leading vehicle (leader) while maintaining a prespecified inter-vehicle distance. This paper reviews the different existing control techniques associated with the transitional platoon maneuvers such as merge/split and lane change. Different longitudinal and lateral vehicle dynamics that are mainly used in the transitional platoon maneuvers are discussed. The most used control algorithms for both longitudinal and lateral control used for transitional platoon maneuvers are reviewed and the advantages and limitations of each control strategy are discussed. The most recent articles on platoon control maneuvers have been analyzed based on the proposed control algorithm, homogeneously or heterogeneously of platoon members, type of platoon maneuver, the aim of control problem, type of implementation, and used simulation tools. This paper also discusses different trajectory planning techniques used in lateral motion control and studies the most recent research related to trajectory planning for automated vehicles and summarizes them based on the used trajectory planning technique, platoon or/and lane change, the type of traffic, and the cost functions. Finally, this paper explores the open issues and directions for future research.

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Section: ) Interpolating Curve Plannersmentioning

confidence: 99%

Platoon Transitional Maneuver Control System: A Review

et al. 2021

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“…We use a polynomial (19) to generate a collision-avoidance curve including the value of the optimal yaw ϕ re f and lateral coordinate ζ re f which are both the function of X, where p y1 ∼ p y5 , p ϕ1 ∼ p ϕ5 are fitting coefficients calculated by the predictive sequence Y n,k as shown in (18).…”

Section: Path Planning Controller Based On Nonlinear Mpcmentioning

confidence: 99%

“…The optimization problem expressed in Equation ( 26) is similar to the nMPC problem, where Y h,k − ζ ref,k represents the prediction sequence tracking error between current lateral displacement and the replanning path value obtained by (19), ∆u h,k is the prediction sequence of inputs' increment between (k − 1) th and k th sample. Under the constraints analyzed in Section 2, the optimal value of the MIQP problem shown in (26) can be calculated by the hMPC algorithm at each receding horizon.…”

Section: Path Tracking Controller Based On Hybrid Mpcmentioning

confidence: 99%

“…In [16], social behaviors were taken into consideration when solving the MPC problem. However, effectively solving an optimization problem is extremely dependent on high-computing performance, consequently the interpolation curve-based methods such as Polynomial Curves [17,18], Bezier Curves [19], etc., are widely used to reduce the computation.…”

Section: Introductionmentioning

confidence: 99%

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Hierarchical Model Predictive Control for Autonomous Collision Avoidance of Distributed Electric Drive Vehicle with Lateral Stability Analysis in Extreme Scenarios

Wang

Lin

Liang

et al. 2021

WEVJ

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This paper proposes an active collision avoidance controller based on a hierarchical model predictive control framework for distributed electric drive vehicles (4IDEV) considering extreme conditions. In this framework, a two-layer strategy is developed. The upper layer is the path replanning controller based on nonlinear MPC (nMPC), from which a collision-free path including the optimal lateral displacement and yaw angle can be obtained in real-time while encountering the obstacles. The lower layer is the path tracking controller based on hybrid MPC (hMPC), and the coordinated control inputs (yaw moment and the front wheel steering angle) are solved by a Mixed-Integer Quadratic Programming (MIQP) with the piecewise affine (PWA) tire model considering tire saturation region. Moreover, to improve the lateral stability when tracking, the stable zone of lateral stability in the high-risk condition is analyzed based on the phase portrait method, by which the constraints of vehicle states and inputs are derived. The verification is carried out on the MATLAB and CarSim co-simulation platform, and the simulation results show that the proposed active collision avoidance controller can track the reference path accurately and prevent vehicle instability in extreme scenarios.

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“…A method based on the Frenet coordinate system is proposed under more complex driving scenarios such as curving roads. To balance the driving comfort ability and safety of the path candidate, a sequential quadratic programming algorithm is employed [12]. A scene-dependent B-spline parallel parking path planning algorithm meets vehicle kinematics model constraints well.…”

Section: Introductionmentioning

confidence: 99%

Path Planning Optimization for Driverless Vehicle in Parallel Parking Integrating Radial Basis Function Neural Network

Wang

Hou

et al. 2021

Applied Sciences

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To optimize performances such as continuous curvature, safety, and satisfying curvature constraints of the initial planning path for driverless vehicles in parallel parking, a novel method is proposed to train control points of the Bézier curve using the radial basis function neural network method. Firstly, the composition and working process of an autonomous parking system are analyzed. An experiment concerning parking space detection is conducted using an Arduino intelligent minicar with ultrasonic sensor. Based on the analysis of the parallel parking process of experienced drivers and the idea of simulating a human driver, the initial path is planned via an arc-line-arc three segment composite curve and fitted by a quintic Bézier curve to make up for the discontinuity of curvature. Then, the radial basis function neural network is established, and slopes of points of the initial path are used as input to train and obtain horizontal ordinates of four control points in the middle of the Bézier curve. Finally, simulation experiments are carried out by MATLAB, whereby parallel parking of driverless vehicle is simulated, and the effects of the proposed method are verified. Results show the trained and optimized Bézier curve as a planning path meets the requirements of continuous curvature, safety, and curvature constraints, thus improving the abilities for parallel parking in small parking spaces.

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Bézier curve‐based trajectory planning for autonomous vehicles with collision avoidance

Cited by 52 publications

References 41 publications

Platoon Transitional Maneuver Control System: A Review

Platoon Transitional Maneuver Control System: A Review

Hierarchical Model Predictive Control for Autonomous Collision Avoidance of Distributed Electric Drive Vehicle with Lateral Stability Analysis in Extreme Scenarios

Path Planning Optimization for Driverless Vehicle in Parallel Parking Integrating Radial Basis Function Neural Network

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