The Path Planning Algorithm Research Based on Cost Field for Autonomous Vehicles

Author

Yu Yong ; Wang Meiling

Author_Institution

Sch. of Autom., Beijing Inst. of Technol., Beijing, China

Volume

2

fYear

2012

fDate

26-27 Aug. 2012

Firstpage

38

Lastpage

41

Abstract

This path planning algorithm is used for the autonomous vehicle driving in the unstructured road. The gradient grid which is obtained from the point cloud data is used as the cost field. Considering the traffic-ability of autonomous vehicle, the cost field needs to be corrected by the High-resolution gradient and elevation grid in this paper. Then transforming the grid model into the network-node model. In this way, the cost field model can be used for the optimal path algorithm, such as the Dijkstra algorithm.

Keywords

control engineering computing; geographic information systems; gradient methods; path planning; road vehicles; traffic engineering computing; Dijkstra algorithm; GIS; autonomous vehicle driving; cost field; elevation grid; gradient grid; high-resolution gradient; network-node model; optimal path algorithm; path planning algorithm research; point cloud data; traffic-ability; unstructured road; Algorithm design and analysis; Geographic information systems; Mobile robots; Navigation; Path planning; Roads; Transforms; GIS; autonomous vehicle; cost field; optimal path;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2012 4th International Conference on

Conference_Location

Nanchang, Jiangxi

Print_ISBN

978-1-4673-1902-7

Type

conf

DOI

10.1109/IHMSC.2012.105

Filename

6305719