Scipediacontent: Scipediacontent moved page Draft Content 325444868 to Chen et al 2020c

2021-02-12T11:41:56Z

Scipediacontent moved page Draft Content 325444868 to Chen et al 2020c

Scipediacontent: Created page with " == Abstract == The autonomous vehicle consists of perception, decision-making, and control system. The study of path planning method has always been a core and difficult pro..."

2021-02-12T11:41:52Z

Created page with " == Abstract == The autonomous vehicle consists of perception, decision-making, and control system. The study of path planning method has always been a core and difficult pro..."

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== Abstract ==

The autonomous vehicle consists of perception, decision-making, and control system. The study of path planning method has always been a core and difficult problem, especially in complex environment, due to the effect of dynamic environment, the safety, smoothness, and real-time requirement, and the nonholonomic constraints of vehicle. To address the problem of travelling in complex environments which consists of lots of obstacles, a two-layered path planning model is presented in this paper. This method includes a high-level model that produces a rough path and a low-level model that provides precise navigation. In the high-level model, the improved Bidirectional Rapidly-exploring Random Tree (Bi-RRT) based on the steering constraint is used to generate an obstacle-free path while satisfying the nonholonomic constraints of vehicle. In low-level model, a Vector Field Histogram- (VFH-) guided polynomial planning algorithm in Frenet coordinates is introduced. Based on the result of VFH, the aim point chosen from improved Bi-RRT path is moved to the most suitable location on the basis of evaluation function. By applying quintic polynomial in Frenet coordinates, a real-time local path that is safe and smooth is generated based on the improved Bi-RRT path. To verify the effectiveness of the proposed planning model, the real autonomous vehicle has been placed in several driving scenarios with different amounts of obstacles. The two-layered real-time planning model produces flexible, smooth, and safe paths that enable the vehicle to travel in complex environment.

Document type: Article

== Full document ==
<pdf>Media:Draft_Content_325444868-beopen43-5876-document.pdf</pdf>

== Original document ==

The different versions of the original document can be found in:

* [http://dx.doi.org/10.1155/2020/6649867 http://dx.doi.org/10.1155/2020/6649867] under the license https://creativecommons.org/licenses/by/4.0/

* [http://downloads.hindawi.com/journals/jat/2020/6649867.pdf http://downloads.hindawi.com/journals/jat/2020/6649867.pdf],
: [http://downloads.hindawi.com/journals/jat/2020/6649867.xml http://downloads.hindawi.com/journals/jat/2020/6649867.xml],
: [http://dx.doi.org/10.1155/2020/6649867 http://dx.doi.org/10.1155/2020/6649867]

under the license https://creativecommons.org/licenses/by/4.0/

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Scipediacontent: Scipediacontent moved page Draft Content 325444868 to Chen et al 2020c

Scipediacontent: Created page with " == Abstract == The autonomous vehicle consists of perception, decision-making, and control system. The study of path planning method has always been a core and difficult pro..."