A path and velocity planning method for lane changing collision avoidance of intelligent vehicle based on cubic 3-D Bezier curve

Chen, Long; Qin, Dongfang; Xu, Xing; Cai, Yingfeng; Xie, Ju

doi:10.1016/j.advengsoft.2019.03.007

Cited by 77 publications

(38 citation statements)

References 27 publications

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“…Bézier curves are parameterised curves controlled by Bézier points. These points, which are of a finite number, can convey a trajectory containing an infinite number of points, while accurately controlling the trend, continuity, and differential characteristics of the curve [26, 27]. A Bézier curve is a proper choice for implementing a parameterisation of the trajectories.…”

Section: Collision‐avoidance Condition For High‐speed Scenariomentioning

confidence: 99%

Methodology of hierarchical collision avoidance for high‐speed self‐driving vehicle based on motion‐decoupled extraction of scenarios

Liu

Chen

Lan

et al. 2020

IET intell. transp. syst

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Section: Collision‐avoidance Condition For High‐speed Scenariomentioning

confidence: 99%

Methodology of hierarchical collision avoidance for high‐speed self‐driving vehicle based on motion‐decoupled extraction of scenarios

Liu

Chen

Lan

et al. 2020

IET intell. transp. syst

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“…Wan et al [17] showed a trajectory planning strategy based on the trapezoidal acceleration curve, which ensured that the curvatures of the initial point and end point were not too large. Chen et al [18] developed a modified Bezier trajectory planning model by adjusting the position of the control point. Funke and Gerdes [19] employed the clothoid curve to describe the continuous and smooth lane‐changing trajectory.…”

Section: Introductionmentioning

confidence: 99%

Lane‐changing trajectory planning method for automated vehicles under various road line‐types

et al. 2020

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This study proposes a lane-changing trajectory planning method for automated vehicles under various road linetypes. The method uses the polynomial regression model to describe the road line-types, and then a non-linear optimisation model is constructed to generate the lane-changing trajectory based on the road polynomial functions. The process of connecting the lane-changing manoeuvre with the car-following manoeuvre is discussed in this study, which ensures the ride comfort of the ego vehicle after the lane-changing manoeuvre. Moreover, considering that the lag vehicle on the target lane may be affected by the lane-changing manoeuvre, the situation that the lag vehicle maintains the car-following manoeuvre with the ego vehicle is taken into account in the authors' model. Another small innovation is that they have designed a simple and effective method to find the suitable initial guess for the proposed non-linear optimisation model. The simulation results show that the lane-changing trajectory generated by the proposed model is smooth and continuous, and the automated vehicle can avoid potential collisions efficiently during the lane-changing process. In emergent conditions, the proposed model can also plan the corrected trajectory to ensure safety.

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“…7 In this case, however, it might not be reasonable for maneuver overtaking. Generally, velocity planning appears in the applications of longitudinal control, such as collision avoidance system 8,9 and maneuver turning at junction. 10 Cao et al 11 use the quadruplicate function to design a path following architecture with a velocity planning module.…”

Section: Introductionmentioning

confidence: 99%

Overtaking control strategy based on model predictive control with varying horizon for unmanned ground vehicle

Zhao

2020

Proceedings of the Institution of Mechanical Engineers, Part D:

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In this paper, a synthesized novel strategy of varying predictive horizon-based model predictive control is proposed for the overtaking control of unmanned ground vehicle. The whole control strategy includes path planning and path tracking. First, the preferred path in presence of diverse constraints of states, inputs, and collision avoidance can be calculated using Gauss pseudospectral method where expected position, velocity, and attitude are provided. Correspondingly, the continuous optimal control problem is converted to discrete nonlinear programming. Second, model predictive control is developed for tracking the optimized path. Considering the effect of the predictive horizon and the Gauss points’ distribution on tracking performance, the varying predictive horizon is introduced to improve the tracking accuracy in non-smooth path. By the varying predictive horizon-based model predictive control method, less computation burden and better control performance are achieved. For the difference between the mathematical expressions and the real unmanned ground vehicle dynamics, genetic algorithm is utilized to identify the parameters of tire model. Simulations in MATLAB and CarSim are both implemented to illustrate the effectiveness of the proposed method.

show abstract

A path and velocity planning method for lane changing collision avoidance of intelligent vehicle based on cubic 3-D Bezier curve

Cited by 77 publications

References 27 publications

Methodology of hierarchical collision avoidance for high‐speed self‐driving vehicle based on motion‐decoupled extraction of scenarios

Methodology of hierarchical collision avoidance for high‐speed self‐driving vehicle based on motion‐decoupled extraction of scenarios

Lane‐changing trajectory planning method for automated vehicles under various road line‐types

Overtaking control strategy based on model predictive control with varying horizon for unmanned ground vehicle

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