Research Status of Vehicle Trajectory Planning

As autonomous driving technology has advanced, it has drawn attention from all around the world. The implementation of autonomous driving technology has the potential to enhance traffic safety, minimize traffic accidents, boost efficiency, facilitate travel, conserve energy, and lower emissions. Autonomous driving technology includes environmental perception, path planning, behavioral decision-making and other technologies. Among them, trajectory planning and control technology is the key technology to realize autonomous driving of automobiles and is the concrete embodiment of automobile intelligence. Graph search algorithms, numerical optimization algorithms, curve fitting algorithms, artificial potential field algorithms, random sampling algorithms, etc. are currently in widespread usage in the field of autonomous driving research. This article will introduce vehicle trajectory planning based on these commonly used algorithms. The necessity of autonomous driving technology research is not only reflected in technological progress, but also covers social security, economic benefits, environmental protection, travel convenience and global competition. By studying autonomous driving technology, humans can better cope with the current challenges of traffic and environment, and at the same time provide strong support for future intelligent transportation and urban planning.

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Publication Details

Journal
Applied and Computational Engineering
Published
2024-11-29
DOI
https://doi.org/10.54254/2755-2721/111/2024ch0093
Citations
1
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
0.25
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article

Research Status of Vehicle Trajectory Planning

Wang Du
1 citations
Applied and Computational Engineering
Robotic Path Planning Algorithms
0.25
article

Research Status of Vehicle Trajectory Planning

Wang Du
article en
1 citations

Abstract

As autonomous driving technology has advanced, it has drawn attention from all around the world. The implementation of autonomous driving technology has the potential to enhance traffic safety, minimize traffic accidents, boost efficiency, facilitate travel, conserve energy, and lower emissions. Autonomous driving technology includes environmental perception, path planning, behavioral decision-making and other technologies. Among them, trajectory planning and control technology is the key technology to realize autonomous driving of automobiles and is the concrete embodiment of automobile intelligence. Graph search algorithms, numerical optimization algorithms, curve fitting algorithms, artificial potential field algorithms, random sampling algorithms, etc. are currently in widespread usage in the field of autonomous driving research. This article will introduce vehicle trajectory planning based on these commonly used algorithms. The necessity of autonomous driving technology research is not only reflected in technological progress, but also covers social security, economic benefits, environmental protection, travel convenience and global competition. By studying autonomous driving technology, humans can better cope with the current challenges of traffic and environment, and at the same time provide strong support for future intelligent transportation and urban planning.

Applied and Computational EngineeringVol. 111(1)
Beihua University (CN)
Sustainable cities and communities
Openalex Percentile: Top 44%
Robotic Path Planning Algorithms
0.25
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Research Status of Vehicle Trajectory Planning — Wang Du · Applied and Computational Engineering (2024) | TGRS Research Map | TGRS