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.
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