Path Planning Based on B&amp;#x0E9;zier Curve for Autonomous Ground Vehicles

Choi, Ji-wung; Curry, Renwick E.; Elkaim, Gabriel Hugh

doi:10.1109/wcecs.2008.27

Cited by 182 publications

(111 citation statements)

References 3 publications

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“…Instead of using the curvature profile, as in the previous scenario, we use Bézier curves of degree four to model the planned path [24] as shown in Fig. 10.…”

Section: ) Scenariomentioning

confidence: 99%

On time-memory trade-off for collision detection

Rizaldi

Sontges

Althoff

2015

2015 IEEE Intelligent Vehicles Symposium (IV)

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Abstract-Future collision avoidance systems, which are capable of fully controlling the vehicle, have to make critical decisions in a very short time. To do this, they need to check constantly if their own vehicle's occupancy collides with the other traffic participants' occupancy. Those collision checks consume a substantial amount of time and consequently, the collision avoidance systems could fail to intervene in complex scenarios. We propose a new approach to reduce the computation time for collision checks significantly. Instead of using geometric methods, we store finitely many possible collision scenarios between two objects in a table and thus collision checks become a matter of lookup table queries. To ensure that the finite number of configurations cover all possible scenarios, we use a novel abstraction technique which guarantees that every collision will be detected. The approach works for arbitrarily many traffic participants by applying the approach pairwise (own vehicle and other object) to each traffic participant. Randomly generated scenarios show that the new approach can be several times faster than geometric intersection techniques thanks to the trade-off between memory consumption and computation time.

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“…Instead of using the curvature profile, as in the previous scenario, we use Bézier curves of degree four to model the planned path [24] as shown in Fig. 10.…”

Section: ) Scenariomentioning

confidence: 99%

On time-memory trade-off for collision detection

Rizaldi

Sontges

Althoff

2015

2015 IEEE Intelligent Vehicles Symposium (IV)

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“…The vehicle uses path following with feedback corrections. 9 A position and orientation error is computed every T second. A point z is computed one sample ahead with the current longitudinal velocity and heading of the vehicle from the current position.…”

Section: V(t) ω(T)mentioning

confidence: 99%

“…The Cornell University Team for the 2005 DARPA Grand Challenge 8 used a path planner based on Bézier curves of degree 3 in a sensing/action feedback loop to generate smooth paths that are consistent with vehicle dynamics. Choi 9 has presented path planning algorithms based on Bézier curves for autonomous vehicles with waypoints and corridor constraints. The algorithms join Bézier curve segments smoothly to generate the path.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Obstacle-Avoiding Path Planning for Mobile Robots

Choi

Curry

Elkaim

2010

AIAA Guidance, Navigation, and Control Conference

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In this paper a computationally effective trajectory generation algorithm of mobile robots is proposed. The algorithm plans a reference path based on Voronoi diagram and Bézier curves, that meet obstacle avoidance criteria. Bézier curves defining the path are created such that the circumference convex polygon of their control points miss all obstacles. To give smoothness, they are connected under C 1 continuity constraint. In addition, the first Bézier curve is created to satisfy the initial heading constraint and to minimize the maximum curvature of the curve. For the mission, this paper analyzes the algebraic condition of control points of a quadratic Bézier curve to minimize the maximum curvature. The numerical simulations demonstrate smooth trajectory generation with satisfaction of obstacle avoidance in an unknown environment by applying the proposed algorithm in a receding horizon fashion.

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“…Since overtaking behaviour can be regarded as two occurrences of lane changing, lane-changing trajectory planning has become one of the key components of automated vehicles. Bézier [5,6], spline [7,8], and polynomial curves [9,10] are currently the must utilized lane-changing trajectory planning methods for automated vehicles. The Bézier curve can continuously generate a lane-changing trajectory using the radius of curvature but is only applicable for static planning because it requires the selection of control points and cannot achieve real-time obstacle avoidance.…”

Section: Introductionmentioning

confidence: 99%

Accelerated Lane-Changing Trajectory Planning of Automated Vehicles with Vehicle-to-Vehicle Collaboration

Bai

Shen

Wei

et al. 2017

Journal of Advanced Transportation

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Considering the complexity of lane changing using automated vehicles and the frequency of turning lanes in city settings, this paper aims to generate an accelerated lane-changing trajectory using vehicle-to-vehicle collaboration (V2VC). Based on the characteristics of accelerated lane changing, we used a polynomial method and cooperative strategies for trajectory planning to establish a lanechanging model under different degrees of collaboration with the following vehicle in the target lane by considering vehicle kinematics and comfort requirements. Furthermore, considering the shortcomings of the traditional elliptical vehicle and round vehicle models, we established a rectangular vehicle model with collision boundary conditions by analysing the relationships between the possible collision points and the outline of the vehicle. Then, we established a simulation model for the accelerated lane-changing process in different environments under different degrees of collaboration. The results show that, by using V2VC, we can achieve safe accelerated lane-changing trajectories and simultaneously satisfy the requirements of vehicle kinematics and comfort control.

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Path Planning Based on Bézier Curve for Autonomous Ground Vehicles

Cited by 182 publications

References 3 publications

On time-memory trade-off for collision detection

On time-memory trade-off for collision detection

Real-Time Obstacle-Avoiding Path Planning for Mobile Robots

Accelerated Lane-Changing Trajectory Planning of Automated Vehicles with Vehicle-to-Vehicle Collaboration

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