TargetTree-RRT*: Continuous-Curvature Path Planning Algorithm for Autonomous Parking in Complex Environments

Kim, Minsoo; Ahn, Joonwoo; Park, Jaeheung

doi:10.1109/tase.2022.3225821

Cited by 6 publications

(2 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It obtained optimized, smooth, and curvature continuous programming path curve expressions by taking the weighted sum of maximum curvature and the absolute value of the horizontal coordinate of the starting position of parking as the objective function. However, due to the large number of parameters, the path search efficiency is low Kim, M et al [6] proposed a Target Tree RRT* algorithm in complex environments, which uses the clothoid path to design the target tree to deal with curvature discontinuity. To further reduce the planning time, a cost function is defined to initialize an appropriate target tree considering obstacles.…”

Section: Introductionmentioning

confidence: 99%

Research on Automatic Vertical Parking Path Planning Algorithm for Narrow Parking Spaces

Wu,

Li,

Gao

et al. 2023

Preprint

View full text Add to dashboard Cite

The narrow parking space will result in difficulties in path planning and spot turning caused by sudden changes and discontinuities in path curvature. To address the problem, this paper investigates the performance of three path planning algorithms and proposes a path optimization algorithm. First, the narrow parking space is defined based on single-step parking of the arc-line combination parking algorithm. Second, to compare the arc-line combination algorithm, Hybrid A* algorithm, and particle swarm optimization parking algorithm under different narrow parking spaces, a multi-objective evaluation function is proposed, including three evaluation indicators, namely, the path length, the number of positive and negative conversions of vehicle speed, and the smoothness of the path. Their performance is compared by simulation conducted in MATLAB, the results show that the Hybrid A* algorithm is the better than others for narrow parking spaces. Third, to smooth the planning path, a path optimization algorithm based on the cubic B-spline curve and gradient descent is proposed. Finally, the simulation is conducted between the proposed algorithm and Hybrid A* algorithm, the result shows that the proposal can effectively eliminate the curvature mutation point and constrain the path curvature to meet the requirements of a smooth path.

show abstract

Section: Introductionmentioning

confidence: 99%

Research on Automatic Vertical Parking Path Planning Algorithm for Narrow Parking Spaces

Wu,

Li,

Gao

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Sampling-based methods usually generate various candidate trajectories based on predefined patterns and then select the best trajectory that is safe, comfortable, and minimum cost (Zhang et al, 2022). Kim et al (2022) introduced an improved Rapidly-exploring Random Tree (RRT) algorithm for complex environments, which uses a clothoid path design target tree in order to address the curvature- discontinuity. And to further reduce the planning time, a cost function is defined to initialize a proper target tree that considers obstacles.…”

Section: Introductionmentioning

confidence: 99%

Hierarchical collision-free trajectory planning for autonomous vehicles based on improved artificial potential field method

Qin

Liu

Guo

et al. 2023

Transactions of the Institute of Measurement and Control

View full text Add to dashboard Cite

To enable autonomous vehicles to generate smooth and collision-free trajectories and improve their driving performance on structured roads, this paper proposes a hierarchical trajectory planning algorithm based on an improved artificial potential field method. To improve the applicability of the algorithm to complex scenarios, the Frenet coordinate system was established to address these limitations. First, the safety distance model is applied to the risk assessment of the improved artificial potential field method. Then, the hierarchical solution is carried out, and the road solvable convex space and the rough path solution are solved by combining the artificial potential field method. On this basis, the potential field term and the smoothing term cost function are established, and the sequential quadratic programming (SQP) algorithm is used to solve the exact path that meets the requirements of safety and smoothness. Hierarchical planning shortens the solution time by quickly determining the bounds of the convex space. Finally, in the speed planning, in order to take into account the comfort and safety of the occupants, the speed curve is solved by considering the dynamic constraints of the vehicle. The obstacle avoidance effects of the algorithm on static and dynamic obstacles are tested in different simulation scenarios. The results of the simulation experiment show that the proposed algorithm can successfully achieve obstacle avoidance on complex structured roads.

show abstract

RDT-RRT: Real-time double-tree rapidly-exploring random tree path planning for autonomous vehicles

Yu,

Chen,

Arab

et al. 2024

Expert Systems with Applications

View full text Add to dashboard Cite

TargetTree-RRT*: Continuous-Curvature Path Planning Algorithm for Autonomous Parking in Complex Environments

Cited by 6 publications

References 35 publications

Research on Automatic Vertical Parking Path Planning Algorithm for Narrow Parking Spaces

Research on Automatic Vertical Parking Path Planning Algorithm for Narrow Parking Spaces

Hierarchical collision-free trajectory planning for autonomous vehicles based on improved artificial potential field method

RDT-RRT: Real-time double-tree rapidly-exploring random tree path planning for autonomous vehicles

Contact Info

Product

Resources

About